 e-mail, phones, all of that stuff, and everybody's cool. The world is turning still. OK. One thing I wanted to point out is over here is our data request line, the total number 709623870. So Denver, I didn't give you this little background, but Denver is now handling Texas, the Dallas region. We have reorganized from 12 regions to six, which meant for Texas, which used to be handled under the Dallas region, is now handled under Denver, amongst other states. So that's why this number is a 720 number, but it's 720 9623870. And it is a service to use our data inquiry line. So whoever answers that phone, if you're, say, working on a project, on your health assessment, on a grant, whatever. And you said, you know, I remember that we geocoded an address, but I've been looking at this fact finder, and I can't find it. Or I got there, and I can't go further. Then we'll unstuck you. And we'll say, OK, let's follow along, and let's go where you want to. So that's a good use of that service. And then Celia's going to talk to you about some local services available here. Are we ready to go for American Community Survey? Yay, yes we are. OK, so we're going to change hats a little bit. We're not looking at simple searches or searches based on 2010. We're looking at another data set. And we're looking at other data products within that data set. So the data set we're looking at is ACS, American Community Survey. Now what is it? Well, in 2000, we did the short form and the long form. OK? And some of you may have gotten the long form in 2000. Who knows? Some of you have been born in 2000. No, not really. But I just said that to wake you up, in case you didn't get any job on the break. But from 2000 to 2010, there was a transformation change that states were telling the Census Bureau, we can't wait 10 years to get data. It gets updated. Oh my god, in our states, our communities are changing. So then the Census Bureau was funded by Congress in 2005 to do the American Community Survey every year. So that long form was changed to the American Community Survey. It became the American Community Survey. So what do we do? We go out and we send a very detailed questionnaire to a sample of a random sample. But it's a systematic sample of households throughout the country of Puerto Rico. And if they do not answer by mail, we have a call center in different parts of the United States that follows up with phone calls. They're still ignoring us. Then they get into a follow up through someone going to your home. So it's a very closely monitored survey. They get it in the 90% response rate. So it's very powerful, which means for you as the data used as a researcher grant writer, that you've got this tool of a household survey. Because there's really none other like it. And the answers to it, answering the American Community Survey is mandated by law. That you as a citizen must, like you must answer the census, you must answer the American Community Survey. Now will you go to jail? I'm not sure. I haven't heard of anyone, but it is mandated by law. OK. So data, and then we're going to go down to the American Community Survey. So I'm just going to give you a few orientation points. Because they're helpful in working through the data. So this is our reference point here, and all you want to know about American Community Survey. Here's navigation tabs again. Let's click on them about the survey. And here we go. Let's click on, so I clicked on about the survey. Let's click on questions on the form and why we ask. OK. So questions on the form and why we ask. As you can see, if I can find my little drop down, very detailed. We organize them into social, financial, which would be housing, physical housing, and then economic, very important. So you see here that as a household survey, we're really asking for a lot of stuff. So say, for example, if we're wanting to know anything about veterans, we ask information for veterans. How do we know about educational attainment of the population, undergraduate field of degree? We ask a lot of things as far as income, food stamps, benefit on physical. So people in housing like that, how much do they pay for rent? Because then you'll see how it translates into the data. So for example, if I'm wanting to learn about veteran status, which I remember I was working with, Webb County from Laredo. And Webb County was working on a grant for veterans. So they might want to know, well, what kind of questions do you ask to ascertain veteran status? So you can click on one of the questions and they'll give you the actual question. So sometimes that's important. For example, I was working with EPA in Denver and they wanted to know what year was a structure built on an Indian reservation because if they were looking at lead, lead paint on the houses, OK? So before 1950, that's important. And so they wanted to see the clusters of homes in the reservation. So we looked at how the question was asked so that we knew that we could get the data for it. Sometimes you need that, OK? So you can just click on the question and it'll bring you to that. So that's questions of why we ask. So you see it's very detailed. Now then, as you can see also, sometimes people come up to me and they said, did you get crime data? And I said, no, it's a household survey. So that would have to be local, you know, your local police department or what have you. But we do ask a number of questions and it's classified in different ways and organized in different ways. Guidance to data users, OK. When to use what and how is it organized? What do we do? So I clicked on guidance for data users. Everybody there? So these are three tips and they're well placed. So you know like yesterday after talking about this, someone said, well, I can't get numbers. And I said, no, you get numbers like what we just looked at, the 2010 census. That's the numbers count, population estimates. Those are numbers count. When you want to get household income, if you want to get poverty rates, school enrollment, you go to the American Community Survey. It shows how people live. Now then, all American Community Survey data are estimates. What does that mean? That means that we're pulling from a sample. So if you're pulling from a sample, what happens? You want to make sure that sample looks like the general population. You don't want to say, well, in this community, a high percentage of grandparents are taking care of their children if the numbers you use are not reliable, right? You want to really have reliable data. So we publish a margin of error, MOE, very ACS estimate. And I'll talk about that more when we get into the table. And then the third one, the third tip is a good one, it has a lot of information in it. So ACS collects and releases data by the calendar year for geographic areas that meet specific population thresholds, a lot of data, a lot of information. So releases data for the calendar year. So earlier, I said that tomorrow, the one year estimate is going to be updated, September 20th. So we'll have 2011 one year estimates. In October, the three year estimates will be updated. And then in December, the five year estimates will be updated. So why is that important to you? You want to have the most current data, OK? And so you all work on deadlines. So you need to know when it's when and what data to use because the person asking you for that will know this information. So if you go in October and you're using five year estimates, but the deadline is October 30th, and you're looking at census tracks, then you'll be fine because the Census Bureau hasn't published the update. But if they're asking you for city data or whatever, which this is available and you didn't know this, then luckily it'll be there when you're looking for data. So you don't have to carry it in your head. So the one year data, one year estimates are only for populations of 65,000. So that's what we mean that we release data and we collect data for population thresholds. So for city of San Antonio, no problem. I can get one year estimates. Can I get them for Chill Hills? Is this 65,000 rover? Probably not, pretty small. Populations of 20,000 are three year estimates and populations of almost any size is five year estimates. So we're gonna do a search with census tracks, looking at neighborhoods, and so five year estimates would be it. If you're looking at rural areas, also we usually use five year estimates because they're smaller populations. So we use, as you can see a lot, population thresholds. Like remember what I said in the quick facts, you can get quick facts for communities 5,000 above. So we use the population thresholds are important to us as far as what kind of data you can get. It's related, all right? Then at the end, American Community Survey, one three and five year estimates are period estimates, which means they represent the characteristics of the population housing over a specific data collection period. So we collect 12 months, 36 months, 60 months. Okay, so if we advertised a lot during census 2010 about doing a portrait of America, a snapshot. So it's that date, April 1st, 2010, we took a snapshot of who was in America, who was in the United States of Puerto Rico. However, with American Community Survey, it's a data collection period, it's a video. It's like, you know, my cousin just had a quinceanera in New York, who knew? And so it was a video of her life, of Catalina's life, it's a video. It's a data collection period. It's not that snapshot, okay? So it's 12 months, 36 months, and 60 months. It takes a while to get that aggregate of data concept together, but just think of it as baskets of data. Now there's one other thing about that, and that is currency and reliability. Two other words we love to use. So, when do you use one three-year and five-year estimates? I'm just going to click on it, but I'll go through it quickly. Currency and reliability. We consider the one-year data the most current data. Okay, this is in between, and then the least current, but most reliable. Well, okay, but what does that mean? So for example, usually if I'm looking at social data, social characteristics, I had a school from that was the Montessori school. In Denver had population threshold 600 and more, and they wanted a Spanish-speaking Montessori school. For their purposes, they wanted the 60 months of data because they considered it the most reliable. So we're looking at this, I have this big basket of data, I have the most data to look at, so I want to get the most reliable. So for language-spoken at home, which they were looking at, they wanted 60 months of data to look at. However, if I'm looking at medium household income or poverty rates, which is based on financial, I'm going to look at the more current data. Okay, does that make sense? To look at currency versus reliability. So that's what that means is we look at the most data, it's most reliable. But I want to look at change year to year, financial, then if the population threshold allows me, okay? That's the clinker, so to speak, okay? All right, so if you'll look at a handout that has data products, one thing we always do is we organize our data into tables, all right? So do you see key ACS data products? Oh, I have the handouts here. Actually, I want you to look at two handouts. First let's look at, it should say key ACS data products, okay? So key ACS data products is an updated chart, so to speak, of the data products that we organize the data, data profiles, narrative profiles, selected population profiles, ranking tables, subject tables. For today's purposes, we're going to look at data profiles, and a narrative profile that has concise non-technical texts. We'll look at a subject table as well as a detailed table. There's other tables there, like quick tables are very popular in 2010 data, but we don't have time to cover all of them, so I'm giving you the highlights, all right? And I'll show you for their reference on American FactFinder. Okay, so let's do our first search with ACS. Any questions so far? Does that help you get some grounding as to what ACS is? Okay, so let's go to data, and we're going where to search for data. What's our data tool? American FactFinder? Is that what was on your mind? Yes, okay, good. So American FactFinder, here we go. So it takes us to this main page, all right? So then I have a little study I put together, a little case, dedicated to the United Way. So I'll tell you, make sure you tell Mary Ellen I dedicated something to the United Way. The United Way right now is going through an East Side Promise Neighborhood Initiative. And so they have, they're looking at different schools within this East Side Promise Neighborhood Initiative. They actually got funding for this. So part of the schools that are involved with that are Tainan Early Childhood Center, Bowdoin, Bowdoin, excuse me, Bowdoin, and Pershing Elementary and Huitli Middle School. Okay, we're not going to look at all those neighborhoods, but they're closely related. So say for example, because I'm understanding that you all still look at small areas. You look at neighborhoods and service areas, correct? Okay, so we'll do this exercise. So first of all, let's look at the neighborhood. You know, we're first starting this East Side Promise Neighborhood, we've got this grant. We want to understand what's happening with the neighborhood around this Tainan, is that correct? Tainan Early Childhood Community Center, or Childhood Center, okay. So then, let's go to May, and let's do an advert. Oh, wait a minute, before we do that, let's first look at the narrative profile. I always get right into that research. Let me first show you narrative profile before we get down lower, okay. Sorry, er, back up. So, let's look at a narrative profile. We'll come back to that in just a minute. Let's look at a narrative profile because this is very important when you're writing a grant, and I think you're really going to enjoy this product. It's really a popular one among grant writers. So, we're going to look at our filters. We're first going to go to geographies to filter San Antonio City. This particular product, the narrative profile, is only available for populations 20,000 and above. Okay, so, click on geographies, and then you know the drill. You can go through name and put San Antonio City. You can also look at Bear Count if you want to, if you prefer that. I'm going to look at San Antonio City, and we hit go. And then it filters down, and we're in San Antonio City, and we add it to our selection. Yay. Okay. So, that's the way your screen should look. Good, is everybody good? Okay. I like that you guys nod, because then it tells me that you're there. It really helps me. Okay, so then I'm going to close it, because I have it in my selection. Then I have just, because I want to get to the narrative profile, and I don't want to look through all of this, I go to topics. And I want to show you this. So, see, later on we'll see people. We're going to look at that. So, these are actually other filters. Okay. Product type. And this is another way you can filter. And then data set. And you can always, if you know you're just going to look at five year estimates, you can always just put that up there, and it'll just bring you to five year estimates. Okay. And what's available there. In our case, we're going to look at a product type. So, do you see where all those products are that are on that sheet? And it explains what these are. In this case, we're going to look at narrative profile. As product type. Okay. So, click on it. And boom, it goes up there. So, you should have on your screen, narrative profile. Then you just select it there. It'll take it away from here. And then you just close it. Good? Okay. So, let's pick the first one. I know that for San Antonio, there's one in three year estimates available. But I just want the one year. Because I'm going to look at the most current data for poverty and for income. And then we view it. Are we there? Can we view it? Okay. So, take a little bit to load. And yours might be faster than mine. Or is it? She's got an apple back there, so she's cheating. I don't know. You got an error? Did everybody get an error? You didn't? You got it? You got it? I was afraid of that. Because I remember this happened. Because it's, I think it's Java. I don't have it loaded on there. Who doesn't have it? You don't have it? And who else? Carol, do you? Ta-da. You're way back? Well, the only problem is that, no, I'll help you get there. Do you mind looking at theirs? Because it's what's loaded on the computer, what's wrong? But you can't just go back? You can. You can. But it wouldn't just, so that's what I got lost. Oh, okay. Well, let me help you. Hopefully you'll get yours. And then, what I want you to do for those of you who have it or are sharing it, just look through it and see the quality of data that you get. And then I'll go over the tables with you vicariously. How's that? Okay, so where were you? So if you were, oh, you're already there? Well, I had San Antonio, so I tried to click on it to bring it back up. Okay. But it wouldn't. Let's see. So then, do topics? Yeah, don't sit there. I'll come and help you. This, you know, I don't want anybody. So then, look through product type. So this is pulling up for San Antonio. Mm-hmm, mm-hmm. Yeah, because remember, you filter, think about your filtering for that, you're already told fact finder, I want to look at Texas and I want to look at El Paso. Okay. And it's going to show you. And so it's going to go to the lowest. Mm-hmm. Right. San Antonio, not Texas. Well, it'll give you both, actually. Yeah. All right. So then narrative profile? Okay. I'm just wanting to see if it's in there. Okay, then you close that box and then you do MP1. Check it and view it. And I'm hoping yours works. I'm scared because it's on the same row. But it's JavaScript. So yours is able to, they'll be able to see the narrative profile in yours when you're good. Yeah, you got it. Yay. Okay, so I'm going to use you if you don't mind. So do you see the graphics on this? How powerful they are? I apologize, but it is a JavaScript thing because I'm using my Della like you. So what I like about this product is it has non-technical text. In other words, it has the story there for you of what's going on, the graphics. And you know that if you're looking like, unfortunately though, like for the smaller communities, you won't be able to pull this up. Okay, like if you were going to look at Lackland as the CDP, it won't, because it has to have 20,000 and above. But you can see that's a nice starting point for you. For, and any, and again, if you're writing within, if you're serving clients within San Antonio, this is a good starting point. Because what it also has, because I think very powerful is the use of graphics and the use of, you know, because right there, if you'll go down and it has educational attainment, if you go down, it tells you the percentage of bachelor's degree, people have completed a high school diploma or have not completed high school diploma. So that tells you something. So walk through each of the segments and see what it will tell you. There's a table on poverty, a participation in federal programs. There's, and you'll see there, there's medium household income. So that it's very rich in data. So I want you to digest that. So in activity informed, born, and this is based on the American Community Survey. Have us surveyed households in the city of San Antonio. And so it's based on, what did you see? Oh, okay. I like that you pointed. And remember that in those economic ones, they're not my favorite because if, well, because I also teach an economic course, it's not really considered like, we're asking people, where do they work? Remember that that's the case rather than jobs in a community. We have another program that does that, okay? But look down further. There is an age distribution chart. And there's also like the Parvium program. And so then looking at this, what my question is for you is, is there anything unique or what would you pull out of this to talk about San Antonio? Just look at it because I like people to look at this and kind of digest this to see and think about, how am I gonna use this? How can I position this? Because it's a great tool. Because this is public data. Carol asked me, well, do you buy things? But there was another question. But it's public data. The only thing is at the end of it, remember your citation. It will say US Census Bureau American Community Survey. And the limitation of this, besides that it's only available at 20,000 and above, is that on that graphic, on any of your graphics, make sure if you're just gonna cut and paste it, you're just interested, say, for example, poverty participation in programs. If you just want that graphic, make sure you type or cut and paste the source, so that you have very clearly for you got that chart. And I don't know why they didn't put it because I expect people cut and paste all the time. Also with the text, you do that. It's right there written for you. In city of San Antonio, blah, blah, it was a medium household income. Okay, so the citation is there, cut and paste at will. Do you like it? Yeah, it's really nice. It's such a nice product. And again, this one will be updated tomorrow because it's 2011. This will be updated tomorrow as part of the one year estimate. Three year won't be updated until October. So if you see how that affects, so then we'll have the most current one tomorrow. So by Friday, I'll have the 2011 narrative profile. Okay, but can you tell me about San Antonio? That's what you read. Because you guys are gonna have to interpret this. What's unique, what's, or about a population? You guys are studying, so what are you reading? 20%? Okay, is that significant? See, that goes back to Carol's question. Is that significant? And then what you would do is then compare, maybe you go to Texas and you might wanna look at the United States. To see how does San Antonio stand within the national and within the state of Texas. But good, okay, so that's what I'm wanting you to see. Like, if you look at a percentage, it doesn't kinda mean anything until you start comparing, right? You see, wow, we're really low for whoever. You see a lot of differences when you start comparing parts of the city. You will see differences, I guarantee you. Okay, as in all cities. Oh, I know, someone brought that up yesterday and I said, oh, don't tell me, but I'm gonna tell you something. Within the state of Texas, that ain't unusual. You know, that really isn't. And in the United States, that's not unusual. Cause I've seen a lot of these that I've worked in different states. Some are better than others. Denver has been working for years on that and it's actually very good, but we have a lot of industry downtown. You all have tourism. You know, we have industries, a lot of industries, a lot of people work downtown. And so there's the light rail system. And I don't think you guys have a rail system, right? Yeah, we have a light rail system and all of that. So, you know, you're gonna improve that. So what else? One other characteristic that you might write it in about or it has surprised you. Okay, it's a household, what's your chart? Okay, so you're looking at the chart of poverty and participation in government programs. Okay, so remember how we said that earlier? That in that particular type of household, female householder family that's head by female householders, what's the percentage of poverty? 31.7, okay? I'm like, okay, 31.7. She was just like, yeah. I don't, yeah, okay, Paulina, like the answer is? Fill in the blank, okay. One of the things that I use when I do that is we work with a lot of females in our program. And we serve a more head of household for the river large population. So I usually grab the participant statistics, capture all that information to the area we service. And we come in early in the West and South Side but there's certain zip codes that are still hard with others. Exactly. And then to the sound player community, especially it's in the local area that we're working with in this country. That's kind of how we, so to us, that's still very significant because of the population. And then you can see also, if you're looking at on a census check level, you can also do a map around that. Okay, it won't be a chart like this but we do have maps that you can do, okay? Any other questions? Or comments? I like comments too, Carol. Yes. Oh, which one are you looking? I hope, what does that look like, Carol? Is it? That would be, no, no, look at the, me, okay, tell me why. Yeah, do you think that's very equal? Mm-hmm. 36, 280 minus 31, 634. That's a difference. 5,000 as far as medium, so in other words. But that's a medium, so I mean that's. It's a medium. 500 is expected to be much, much bigger. Okay, you all can have a discussion afterwards to say what's significant. But of course, always people advocates are always trying to make it more equal. No, no, no, it's not. No, read it, read what it says. It's for, you know, women who work and male who work, no matter. It could be, it could be in the same household. It's basically looking at workers. I liked her expression back there, I'm sorry. She went like, I don't want to gain 5,000 less for doing the same job. Exactly. So that was her expression back there. She goes, doesn't that look that same? What does it say? But what does it compare? Read it, it'll say on there. Okay, so it says the medium of households was 43,758. Okay, 16% of households in San Antonio had income below 15,000 a year and 6% had income over, okay? So then it says medium earnings for full-time year-round workers by sex in San Antonio city. Just full-time year-round workers. So for males, there's 36,280, medium earnings. For female earnings, are 31,634. So it's not really household incomes, it's earnings. No, it's not saying the same job, but $500 difference between the female and the underage is the difference. I agree with that. I'm just saying, I'm surprised it's not a greater difference. Got it. I'm not saying I'm happy with that. Okay. I'm surprised that it's not a whole lot. Yeah. That's why my face was just different because I was backed out of this completely and I didn't narrow it down to San Antonio. I was living in the whole country and there is a $10,000 difference. So that is why I'm like, what? Of course there's no... Oh, so you went back to see how national? Yes. And so I... Okay. And I wanted to make sure that I needed another drill down myself and I knew where I was to be so. When you said it's different, I'm like, wait, that's okay. What you were saying here is just that time. I had to make sure that I looked at the drill down. Good. Okay. But that's what I want you to... Once you get the data, that's what I want you to start thinking about because... And also what we did right there, Carol, was real important because we looked and it did not say, that's so important. And you guys all have to deal with this. With income, earnings, what does that mean and what is it saying? You've got to understand that because different grants, what is it, grantors, foundations, agencies ask you for different information. And so there's earnings information like what we looked at right there. There's medium household income information. There's family income and sometimes they just want to say families with earnings of 35,000 and below. Okay. And you guys know as grant writers that different strokes are different folks, so to speak. So you've got to understand and you've got to read. What are they saying? Like in this case, what Carol was looking at was earnings, okay? Different from household income. Because household income, you can have the abuelita, the grandmother living with you. You can have adopted children living with you or whatever. Hopefully they've adopted children earning money. We don't know. But you know what I'm saying? Or there could be retired people or whatever. So household income is the whole picture, okay? Family income always is looking at related people, okay? But people will ask you different things. And especially for grant writers, you need to understand the different categories and read what's being asked in the grant and then match it so you can answer that correctly, okay? Good exercise. How did you guys like the narrative profile? It's a nice one. Yeah, just remember that one of the limitations is that you've got to, whenever you cut in pace, you know, feel free to do that, but just make sure that you know where you got it from and what your source is, all right? So let's do another search. Now back to our case. Now I have to find my little casita. Oh, there it is. Yay. Okay, so let's go to Maine because we're gonna do an address search. Uh-oh. I'm not planning my thing. Okay, go to Maine. Yay. Okay, now I want to just practice this. You could leave San Antonio if you wanted to, but we're practicing clearing all our selections because I don't want you to go back and you're starting to work on your grant or whatever and you're there going, oh, why can't I get this? If your selection box will make a difference because it confuses American FactFind. If you have something else and then you're trying to find another geography, it will go back to that, okay? So make sure what's in your selection box is what you want. Let's do an address search. Okay, now we're going back to our case study of Tainan Early Childhood Center. And we're gonna search for that because we wanted to know the neighborhoods around it. I'm hoping that this will work for me as well as for you all because it didn't do the graphic before. Okay, so then let's do the street address and then let's put 925 Gulf Street. Okay, city. Yes, San Antonio. And then Texas. And if you're not with us, make sure you tell me. There was Fort Carroll Struggling. Da, da, da, da, da. Didn't that sound pitiful? There was Fort Carroll Struggling. Okay, so then, so what happened? So do you got my address? 925 Gulf Street, San Antonio, Texas. And I hit go and then it geocodes it. So then am I looking at a neighborhood? So census tracts, we don't necessarily anchor, we do have like a lot of times people say we'll zip code. We don't anchor a lot of data on every zip code in the city because they change so much because they're at the whim of the postmaster. Okay, where's the census tract? We're right on target with it because as communities change census tracts because it is a local decision, then we change our geography based on local and it's a very coordinated effort, okay, where zip codes are not. So here we have census tract, okay, it's in Bair County. And then see the ZIPCA, which is the ZIPCA means the most common zip code that is in that area, so 7-8-2-0-2. Okay, so the census tract usually is around between 2,000 and 8,000 people, okay. So we're gonna look at the census tract and it's usually designed around a neighborhood, okay. And the way we look at geography is census tract, then it's in a county and then also in a place. So let's look at census tract in 1306, can't see. Is it 1306, yeah, it's census tract 1306. So I selected that. I told fact finder I want data for that census tract that is located for Tynan Early Childhood Centerists. Everybody there? Okay, good, yay, we're nodding, we're awake. Okay, so then, let me look over here. You see where it says map? Click on map, okay. So it'll give me a map, a kind of wild map of this location, right. So that's a census tract, that's a neighborhood around the Tynan Early Childhood Center, okay. Do you see that? So it gives you boundaries. And if I was really doing this exercise, I would also be looking at the different census tracts around there, okay. So in this case, let's do this. And they're all kind of around. There's two ways to attack this. We're gonna look at different addresses, okay. Let's look at the address for Bowdoin. So let's go back to address, because we're looking at, let's look at three of the schools, let's be noted. Okay, so then I'm going to do, now the second school is Bowdoin, which is that 515 Willow, bless you. And then hit go. So this, what I'm showing you here is how to find different parts of the community. Okay, so in census tract, 1919, right, okay. So it added that. So I'm doing one more, Pershing Elementary. Pershing Elementary, is everybody getting the addresses? I'm not going too fast. Okay, Pershing Elementary is 600 San Mayer, okay. And then we hit go. They'll geocode that. Okay, so then it says census tract, 1307, who knew? All right, and as a matter of fact, another school in the cluster of East Side Promise neighborhood is that the same census tract as this one, because it's a middle school and usually middle schools are feeders or elementary schools feed through to that. So we're looking at three schools. We're getting our research going out. What's going on with East Side Promise neighborhood initiative? Okay, so let's look at the map and see where are they in the city. You see that? Cool, huh? Another way you could do this is if you were just wanting to look at this here, I don't know if we'll have time to do that. You may not. But if I started off with this census tract, I could use this graphic and click on this, click on that, click on that. I would have to have census tract on here, not state, and it would show me the census tracts around there. So that's another way to get data like this around a neighborhood. In this particular case, I'm looking at some schools in a cluster that the United Way actually is doing. So we're gonna look at three different neighborhoods that are around these schools. Okay, that's part of this East Side Promise neighborhood initiative. It doesn't market anywhere like this. All you're getting is that census tract. Census tract. You don't know if it's on the corner. No, but you can look at the streets and stuff like that so you can kind of do that. So, oh, I see, I think what you can do as far as you wanna know where the address is. Right. I think you can point it to put the image. I think you can look for the location. But if not, what I would do is do it manually. Okay. So that if that's important to you, to know that or to kind of figure it. What you can do also is you can look at boundaries through here, and you can even put the census tract. If you wanna put the numbers of the census tract, you do that by boundaries and features. Do you see that? And so if you wanted to add like, say for example, oh, the census tract's on there, if that would be important, then you could do that. However, I will caution you, when you do that, it kind of makes for a busier. And then at the bottom, it says update. So you can add that. Those are the boundaries and features you can add to customize it. So let's look at my new location. On features, you can go to school. Which one of that? Yeah, then you could do that. Let's do that, try to see where it is. But it has state legislative, next year in England, if you have to go to the next gas. So then let's click on that and see if it'll tell us. In school district elementary, we'll use to see what happens. Yeah, I'm just clicking on school, see what it does. I'm gonna look at schools again. And I updated it, okay? Is it anything? It might just do the boundaries. I'm not seeing that it's doing anything. Yeah, I didn't see where it did anything. Did yours do anything for the schools once you updated it? No, it might have been just that it does the boundaries. And we're in the boundaries that we know. Okay, and you may have to play with this to actually see it, but it should have done something. I don't know. So anyway, so those are the census tracks that we're looking at. So another thing that I wanted to go back to is now that I know my area, let's go back to address this one time. And I'm gonna add, oh, here we go. I wanna add Texas and I wanna add the city of San Antonio. Okay, so go ahead and click on Texas and click on, because that's my compare to what? I'm looking at census tracks. If I can ever find my mouse, okay, here we go. Here's Texas. Uh-oh, what happened? Oh no, I'm an advertisement. I'm an advertisement. I was doing so well. Can I go to history, but it won't get me to my census tracks, I know. It's so hard to, do you know how hard it is to do that? There, no. There's then book elaboration. Search. Did it lose my stuff? This is real life restriction. I found it, yay, we're happy. Okay, so then I didn't lose my census track. Okay, so on here, you should have census track 1306, 1307, 1919, and you guys probably have state of Texas and city of San Antonio, correct? I'm hoping, yes, so I'm gonna add Texas at least to mine. And then I'm gonna add San Antonio. But you already got that by just clicking on it, right? I like that you're always there, so, yes, that's correct. So let me just do this so that I can catch up with you all and add. Okay, yay, but does everybody have the same geography? So what I have here is I still like that three neighborhoods on the east side, I wanna compare it for Texas and I wanna compare it for them the city, okay? But it also gives you an example that you can work all the time with multiple geographies to be comparing. So the first thing I wanted to look at is medium household income. Just wanna get a taste for this neighborhood, what's going on. So one of the ways you can filter and I really want you to remember this, narrow your search. So this narrow your search can work very well for you because it's more an intuitive search. So say, I need to, they're asking me in this grant for medium household income. So that's what I'm gonna type. Medium, and hopefully you never have to do it this way. Far. Medium household income and then I just hit go. Then what it does, it filters through and gives me everything corresponding to medium household income. And this is the table I want, okay? So B19, 13. Is there anybody there? If not, let me know, cause I can go help you. Good? Oh, she's putting on her glasses. Okay, good. So is there anybody there? Can we look at that table? Okay. So then let's view it and see what's going on. All right, so you can see in the American Community Survey, you can get side by side geography comparisons, all right? So this is a very simple table for, so I asked it for a medium household income and then I put down my different geographies. So I have my three census tracks. Of course, in real life, if I was really working on this, I'd probably want to put all the census tracks of these schools and maybe cluster them and decide on how many neighborhoods I wanted to look around there. So for Texas, so what can you tell me about these census tracks that the United Way is gonna target? So this is our first fleshed look. What can you tell me? So this is medium household income, right? An inflation of just the dollars. So the income is here, these are dollar figures. That means half of the population is above, half below, right, that's a medium household income. So if you were saying something about this, what would you say? Carol, help me out here. I have about 40. Does your screen look like mine? No. Who else does it? It almost does, but then my, you know, it has the same attack. Okay. The census track and then it would be drawn out. Oh, you must have done all census tracks or something. What does your selection look like? Oh, my microphone. You didn't put medium, you were looking at a subject table. You didn't click on B-19-0-1-3. So go back to search. And so, oh, not medium, medium. M-E-D-I-A-N, that's what I, and then make sure you turn that off right there. Yeah, that, right there. That one, right there. Ah, make that out. And then put medium, M-E-D, medium household income, middle. And then click on, it should pull up B-19-0-1-3. Is everybody there? Okay. So, Trina, Trina, Trina, Trina, Trina, Trina, Trina. Oh, that's it, that's it. Okay, so what can you tell me? What's going on here? Compared to the state of Texas, compared to the city of San Antonio. How are these census tracks? What can you give me an idea of? Did you get it, Carol? Yeah. Okay, good. Did everybody hear that? They're significantly lower than the state of Texas or the state of San Antonio. Even San Antonio is less than Texas. Right. So within Texas, San Antonio, very less. Okay? Then, when you keep in mind San Antonio and Texas, when we compare these, what do we know of? What do we have? Half of the population of these census tracks that the United Way is targeting lives below 17,795, okay? So, wow, yeah. So right away, you're seeing there's some challenges in these neighborhoods where these schools exist. Right? Well, we know within the recent which you had, there's quite a bit. Right. Did I mess up here? Okay. Sorry, my microphone. Am I okay? Yes. Okay, all right. Not only am I having challenges here. Okay. So do you see how that already starts telling you a story and starts really guiding you through what's going on? What are the challenges? Right now we know incomes, medium household incomes can be low. Right? Okay, so there's already a red flags coming up for us, wow. All right, so then let's go to some more tables. Now I'm going to look at party data on this because that's one of my indicators that I'm looking at for the East Side Initiative. And I have to find my mouse again and I found it, yay. Okay, so then remember, Narrier Search is a good filter. This time what I'm going to do, I am not messing at all. I'm keeping my geography intact. But I'm going to eliminate this medium household income and cross it out. And now what I'm wanting to look at is I'm going over here with topics. Okay, that's another one of my filters, topics. Okay, so let's click on that and see remember those other filters and it goes on to people housing. In this case, poverty, let's see if poverty is under here. It is, but then what about poverty? Let's look. So perhaps if I was looking at the food lunch program, I may be looking at food stamps now. Or if I was looking at maybe how people live as far as if I'm doing a rehab program, I may be interested in beating a cooling system. Or I may be looking at poverty as far as children and whatever in this initiative. Okay, just depends how the question and what our funders have asked us to look at and what we're interested in looking at to see how we service those neighborhoods, correct? So I first just do something different. Let's look at the food stamps because I found this table really important. So I'm just going to look at food stamps, do you see that? And I'm just going to look at one subject table there. So I'm looking for this two people one right here. So I preselected this, you would be, so I'm going to look at, I'm looking at food stamps because I'm also looking at food lunch programs, okay? So I'm wanting to see, and in fact I heard this this morning on NPR, how much more families are using food stamps because that's an indicator, okay? So click on the subject table 2201, okay? So again you're saying probably what's the subject table? S2201, S221, got that Carol? No, they're separate tables because the data products here, we organize the tables differently. Do I look like I'm an advertisement here? That's what it feels like. So there's different products. So that's what I want you to understand is that when you look at the tables, they're like can be overwhelmed like, ah. So what I want you to understand, there's a method to the madness. I'm believing there's madness. But like for example, the subject table is what? The subject table is similar to data profiles but they are classified by subject. So in this case, we're going to look at a subject table that is the subject is what, food stamps. And then characteristics related to it. So let's look at it so you can kind of get the gist of it. Right? So click on that one, just on that one, and then view it. S2201, subject table on food stamps. Because I think subject tables are good for grant writers to use because they organize characteristics around a certain subject. For example, there's the subject table related to poverty, there's subject table related to veterans, related to children. So it's a nice way to look at it. So look at the table, okay? And it's subject table 2201, food stamps, snap. And then it's only on, so a state of Texas, that's our benchmark, and then the different census tract. So then what does the subject table do? It's saying this is my subject, these are my geographies, and it tells you households with one or more people 60 years and over, and also with children under 18 years, who use food stamps. That's how that works, okay? If this was povertyist, my subject could be, what, how does age influence? So how does having a household with 60 years or over influence having food stamps, okay? And then how does that relate to poverty status? If I receive food stamps, do I have a higher percentage of being in poverty? So do you see how to read that? So what can you tell me? There's a real market change, that's why I want you to look at table, because this table is kind of dramatic. So when we look at these census tracts, what can you tell me? Someone said, well, but look at, I just want you to see the difference between the households with one or more people 60 years and over, and with children under 18 years. What can you tell me? And it follows the trend of state of Texas, actually. So you see how it's total, and then households receiving food stamps, households not receiving food stamps. What's that? And it's quite significant, right? Look at that. And again, this is isolated to this particular census tract. You guys agree with what Carol said? Or how would you phrase that? I'm trying to get over, I can't get all my table. Do you guys see the rest of the table, which is San Antonio? I can see all of this, so I can move over. There we go. Am I moved over? Yeah, here we go. The other census tract. Sorry, I have to play with this a little bit. Luckily, the video is in the following. This is crazy. Okay, so do you see that? I don't know. What else did you find? How else would you describe this? She's looking real hard at, how else would you describe this? So another indicator, right? We saw that first indicator when we looked at medium household income in these neighborhoods. We already saw a red flag. Now we're seeing something else in these families. So those with children, which are, basically if we're looking at schools, that's our market, so to speak, or that's our clientele. So it tells us something about that. Okay, so that's a subject table. Let's look at a detail table and let's look at a profile. So you can see, you can appreciate the difference in the different way we organize data. So let's use poverty now. Okay, so let's go back to search. Go back to search since you guys have a mouse that works and I don't. So go back to search, I don't know if it'll do that. I'm scared to do that. Okay, so hit the back to search. I think you have to play with it. You can play with putting first selecting Texas and San Antonio, St. Nepper's, and then searching for yours. Yeah. Okay, let's back to search. Okay, so now I'm going, I don't want to look at food stamps anymore. I want to look at poverty. So that's one thing, a limitation, is that if I leave that food stamps on, when I look at my poverty tables, it won't give me the full enchilada, so to speak. Okay, so then eliminate that so that we have a clean search. I'm going to close that. I'm removing it. I'm going back to topics, okay? Just for grins. So I'm going back to people and I really want to look at poverty and I'm going to go look at poverty under poverty. So do you see where it now, we looked at food stamps and we looked at a subject table that the subject was food stamps. So let's click on poverty and it goes up to my selection. Okay, and then we close out our filter because we already filtered. We were looking at different tables for poverty. Okay, so I'm going to look at, I want to show you what a DP03 is, demographic profile. Let's go ahead and compare that subject table with this one, 1701. And then I'm going to look at a detailed table. So I'm looking for actually a detailed table. Okay, right here. Just by age and sex and age. So you should have three tables checked off. You should have selected economic characteristics. You should have poverty status in the past 12 months. And then SM, so this is demographic profiles, DP03, so DP, subject table 1701. And then the basic table, I want 1701, right. 1701, poverty status in the past 12 months by sex by age. So three different tables, three different ways to organize data. Okay, so based on this, I'm just showing you three different ways to organize. We already looked at one subject table. So then you just view that, okay. So then this is the DP03. Now it is a lot of data, DP03, a lot, a lot of data. So I showed you a simple table and this is a lot of information. But it's selected economic characteristics. So it's a profile of these neighborhoods. And this might be a way to start looking at, because they're looking at all these neighborhoods in the cluster. So this might be a good way to just get some handle on what's happening, because it's a summary. It's an overview of what these neighborhoods are based on, because the DP03 is economic, the DP02 is social, which involves school enrollment and educational attainment. And the DP04, demographic profile is focused on housing. So you see how even having a summary could really help you look thoroughly at these neighborhoods just by these three different profiles, okay. So then you have, so all of these go through community to work and industry, class of worker, because again, it's everything related to economic. But then it starts giving you what I like about these tables and I recommend not getting overwhelmed by them, but kind of seeing how they could work for you. Is that it first, it starts going through income and it starts going through total households, okay. So it's here. The income and benefits, so why does it look different? Well, because I think it filled my geography. Yours probably looks different than mine, because for some reason I have the United States on here. Uh-oh, yes, okay. Well, keep on with those tables. Mine just lost all my geography. Oh well. So, but do you guys still have your census tracks? Okay, so then are you at DP03? Okay, so do you see how first of all, if you scroll down, it goes through all the household income? See that's what I'm saying also, like remember we talked about earlier how it's important to know the difference between earnings, between household, between family. It all is there at that table. That's what I love about it. So if I'm doing, you know, I have very limited time and I need to know family income and I'm looking at specific neighborhoods, this might be the way to go. And you don't have to go further than this. But also what I like about this is it has percentages. So if you scroll down, you see household, you see family, and you see there's also per capita. If they ever asked you that. Every now and then you are as per capita income. So it's all there in this profile. I like that a lot. And then in, say if I was examining these neighborhoods, I would also look at the DP2, the social characteristics because then it's going to tell me about school enrollment and attainment, which I want to know because I'm looking at schools, okay? At the very end of that is the poverty, the percentage of poverty. And you can see that. Do you see how you could use this? It's a summary, so it's a lot of data you have to like say, oh, okay. But if you take it piece by piece, it can really work for you. Say for example, like if there was a, Brad said, we want to know how many families earn, or we want to just work with families that are, this program is only for families with incomes of, family income of 35,000 below. This table would allow you to do that, right? Okay, I see nods, which I like. My screen, I don't like. Oh, I lost all that geography. You know, this is one of those like, moments. Okay, so then the next table is your subject table. I want you to see the difference. The poverty subject table is way more complex. I'm just going to do a geography of San Antonio to follow along with you. But look at, do you see that you do the result two on top of your table? That's how you get to your other table. So result one of two, you should get to subject table 1701. You guys see that? Do I back to search? Okay, do you see that? Results of these, so you see the subject table? Yeah, so then you view it. Okay, so now, what's nice is this lab is small so I can walk around and see what people are doing. I got it, I was just seeing what you get. Oh, okay, that's no problem. Okay, so then, so do you see in the subject table and poverty, it first starts off with age. So again, it's relating, and I'll go ahead and pull one out. But it's relating everything, age, gender, like male, female, and answer this question for me. If does being a male or a female affect my poverty status in the state of Texas and these census tracks in the city of San Antonio? Just by being male or female. First tell me about Texas. Does it make a difference if I'm a male or female in the state of Texas? Will that affect my poverty status? Or am I more likely to be living in poverty status if I'm male or female? What's the answer? Female. Female. Does everybody agree with Carol? Okay, Stephanie agrees with you. Or maybe she's just saying yes. Okay, do you guys see that? How to interpret that? How about in the city of San Antonio? So in Texas you're saying yes. But how about in the city of San Antonio? Yes, okay, that's not good, what can I say? How about in the census tracks? Male or female? Does that matter? Okay, so, but is it matter if you're male or you're female? Because in some census tracks, male can be higher percentage rate. And these particular ones, what are you telling me? Female? Okay, so it's consistent. So just difference in gender. Now tell me, one last question I have on the subject table is if I'm Hispanic or Latino origin in the state of Texas, am I more likely to be living in poverty status? Yes, okay. How about in the city of San Antonio? Okay, so do you see how that works? So the subject table will relate age, will relate Hispanic or Latino origin, educational attainment back to poverty. But that's what's nice about that subject table. Say for example, if I'm doing different things on educational attainment maybe, I've worked a lot with community colleges, they always want to see what a population's educational attainment is. So they can just write on your narrower search, you can just write educational attainment. Okay, so that's, you know, I'm thinking of like, if you're writing a grant and you're doing different pieces, you can just use your narrower search that way. Okay, that's a nice tip. One last, because I have five minutes to go for Celia's showtime, is let's do the final table, which was the basic table. So it should be your third one. I was trying to catch up to you guys. So it should be the B-1701, and it should be the result three. And that is only eight. It's a simple table, it's a basic table. For some reason, I cannot get here. But does everybody have 1701? Well, you can't follow me because I'm not there. Let me see if I can do it this way. Who didn't get it? Because all you had to do was just check it out. Oh, you cleared out everything? Okay. Did you get 1701? Okay, let's see. You cleared up. Yeah, I didn't need to. Oh no, you did what I did. You weren't supposed to follow me. I didn't need to. We're finishing up. So do you want to go just sit by Carol? I don't think she bites. Because I won't get there. It's being misplaced. So then 1701, you should be on the basic table. Okay, so let's go result three of three. So click on result three of three. And are you there? Okay. So this is a real simple basic table or in your key data products, that's your detailed table. I know it should be D, but then we have the DP. So the basic table are really those sometimes where you'll probably work the most. Okay. So remember we had a profile. We had a subject table that organized things under the subject. The good things about those two tables, the profile of the subject is they have a percentages. And I love that. However, the basic table does not. So you're going to have to download it to an Excel spreadsheet. Okay. So what you look at here at B1701, I'm only looking at poverty as related to age and as related to male female. And whenever you look at this particular table, be careful when you're downloading because the top part of the table is below poverty level and the bottom is above. So if you're going crazy, you've got a deadline and then you accidentally like download the bottom, you're not going to have good figures. Okay. Because people are asking you who quite a percentage of the population lives in poverty level, correct? So then let me also take you through how do you modify your data? Okay. How do you play with your data so to speak? So do you see those modify table, bookmark, print, download, create a map? Okay. All of those are in blue, which means you can use them when they're blue. So click on modify table. What is your name? Jaclyn. Just like Jaclyn. She's my banner right now, sort of. Okay, so modify table. Do you see how it changes the table? So what's nice about that is if you're just interested in say, if we were working out that you said talent and I was just really interested in only a certain age group, say five to 12, then I could modify it and you could modify it before you download. Okay, so you could take that. If you say no, Pauline, I just like to download my table and then I do it. Okay, well, all right. But if you wanted to do it otherwise, you could do that through modify table. And sometimes by modifying the table, you look at it to see if it will help you, if that's the data you want. So that's where it would be good as far as before you download it, before you commit to it, look at it and say, yeah, I'm gonna move on to another one. The other thing is bookmark. If you go to a meeting or whatever and you've done all this work, before you cleared it out, you see, you've done all this work and then you want to bookmark it. You do not want to lose it like we did. You and I bookmark it, okay? If you want to print, you can print it to a PDF and send it to someone say, look, I know all this information. I found this out. Of course, I'll do a nice summary because you're a great rat writer and say, this is a table that I have and this is what it shows. And you'll be a star. Okay, and then, so you can download it. Okay, click on download. Let's talk a little bit about that. Mom, what's your name? I'm good? Okay, all right. So do you see download? So it says data documentation in a single file. You can do it in the PDF, Excel, and Excel, you can do, whenever you do Excel, I don't know, do you need to work in CSV format? You do, okay, so you can do this in CSV and then to Excel if you want to do multiple tables. That's the best way that I said, I don't work in CSV as much, but other people have done it, have to download that way. And you, I think, are going to be downloading a lot of different tables. Sorry, so then just, but keep in mind when you're downloading a little trick or tip is you know how deadlines are and you can get crazy downloading data, is make sure you keep the name of your table, okay? Make sure you don't like start deleting stuff or then, oh, where did I go? Or what, you know, because then if something looks funky, then you can't go back to your original data. So make sure you have that table and then make sure that you keep the table that you are referencing and keep your citation. Okay, so did you use five year, three year, whatever? And it'll always be at the bottom. So those are real important downloads. And download at will, you can do whatever, but just make sure you can get back to where you were before just in case you need to look at a number again. You know, because in those little blurry deadline times, sometimes you just need to make sure that where you had to go back, you know where to go back and where you got your data. Okay, now one last thing about March in a Bear as you're looking at a number, okay? You can close that down. Oh, I know, one other thing is whenever, and if you go back to high table, right here, it'll reset it. And don't be afraid to do that modified table. You're not going to modify the US Census Bureau tables. Oh my God, I changed the whole data set for the city of San Antonio. We'll never be able to same. Okay, that won't happen. You're powerful, I know, but not that powerful. Do you see where it says create a map? Do I have a few more minutes to say it? Okay, good, so I just want to show them this. Create a map, like you saw at the limitations on the other tables, there's not percentages. You're going to have to download your basic tables and do the percentages yourself to the formulas that excel, right? Create a map is another graphic that I think you'll be able to use, so put attention. So create a map is, just click on create a map and it'll turn all the, and you couldn't do this before with our data, but you can now. And create a map works on some tables like your basic tables and not in the others. But on your basic tables, you can create a map and if it's in blue, you can do it. If it's in blue, okay? So create a map and then click on, and I can go around to make sure that you do this since I don't have a screen. It's blue and then it says, it turns it blue. So then in the second, like the census track 1306, click on that number 4788, oh not 4788, excuse me, on 2526, which is your first income in the past 12 months. You see that? I can go around. You see that? Okay. And then it'll say show map. So go ahead and click on showing map. So this, and you'll see, but you can also, for those of you who work in a whole area like Bear County, you can also do all census tracks for then Bear County and then you can look at that, okay? But it's a whole, not Baker, so it's taking its time. Let me go over to Carol. Has anybody gone on the map yet? Yeah, you haven't. Did you do it? Can you have to get out of high table tools? Okay, so do you see what happened? Okay, I'll go, I'll go. Did you get a map yet? Okay, so you see the difference? What are you looking at? It's based on the table you just looked at. Yeah, we can create a map. Yeah, create a map, yeah. What was hanging you up was you were in high table tools. They have to get out of high table tools. And then you turn it blue and then you see that number? Not Texas, right there. Yeah, 2528, that's good. And then say show map. So this is just an example, but if you wanted just to do a certain age group and look at parry level, you would just click on that row of the table, okay? So if you wanted to drill down, you could also play with this map if you don't want Army Green in your map. You can do red, which is our neutral, and or whatever color you want. Sometimes publications, PowerPoints, or whatever, if you want to include this in there, will dictate what colors you use, because I know I've had professors saying, well, I'm printing a book and so I need it only in Graceville. Okay, worry, but you have to do it, okay? So I'll let you, so do you see what's happening here? You can really customize and really make a nice presentation. You know what, some writers have told me good data about bad things, okay? But you can tell your story this way. And I think knowing how to initiate the power of this can really help in anything you're trying to write about. So like if you're saying you're doing different communities, if you want to show different parts of them, in this particular case, they're working on a neighborhood initiative so they have a lot of neighborhoods together, right? But I'd say if you were looking at two different parts of San Antonio, you would see differences there. If you want to illustrate that, you could do this by creating a map, okay? Do you guys like this? Okay, so let's do a semi or kind of a look over and then I wanted a little bit of your comments and then I'm going to turn it over to Celia. She's like, oh, no, she's not, she's too nice. She's like, relax, like, hey, go ahead. I know what I'm going to do. And so, so first of all, so we looked at 2010, now we moved over to American Community Survey. So it has period estimates, which are 12 months, 36, 60 months based on population thresholds. There's different products that you can pull from. What we looked at today was those demographic profiles. Don't forget about those, because those are good. Those are good time savers. Your narrative profile, I just adore because you can cut and paste. And then the third one that we looked at was that basic table, which is really just when you're looking at different characteristics, I say, I want to look, I'm only interested in female householders. So the basic tables allows you to zero in on that, okay? So, and then just don't forget about when you download to make sure you do your citation, go back to your table. One other little point that I wanted to make was on MOE. Okay, let me just, okay, so MOE, margin of error. We talked about that earlier and go back to a table and let's look at an estimate number. Go back to table, because you're now at a map, which you're excited about, I'm hoping. So, it doesn't matter what table you're on, just as long as it has a number, but now I can't even find this, okay. Sheesh, isn't that terrible? Let's go to BPO, please. Anyone, it doesn't matter. I'm just going to go to any table, just to illustrate a little bit, yeah. Okay, it doesn't matter. So, see if I have estimate and estimate margin of error, okay? So, remember we talked about reliability and this is a sample. So, if this number, this estimate was 100 and my margin of error was 10, okay? So, we published a 90% margin of error, nine times out of 10 that number will appear in the population. So, if that number's 100 plus 10 minus 10. So, my confidence interval that number will appear in the general population is 90 and 110, okay? Plus or minus. I'm hearing a lot about plus and minus of the political polls, right? So, we want to be confident that number's going to appear in our general population. But what happens if this number becomes 20? Where's my confidence interval? 80 and 120, right? So, then it's expanding my confidence intervals of that number. So, is it less likely to appear in the general population if it's wider? I have a bigger chance that it may not, okay? So, rule of thumb is that if your estimate margin of error is above, above 10% of your estimate number, you may want to question the reliability, okay? So, that's just a rule of thumb to think about reliability. If it's above 10%. So, say for example, I remember in a class in Arizona, this guy said, oh my God, in this community, all these grandparents are taking care of children. When she looked at her margin of error, it was way high. So, I said, you might want to think about that and think about saying that statement. So, that's the way it would impact you and your results, okay? Because I want you to feel very secure about whatever you write or site.