 I am going to import a file that I saved and show you how you can change or manipulate that. I'm going to go ahead and import SPC. I want this one. I didn't name it, so I just saved it by the date and I can change the view. So this was looking at men and women, men between the ages of 18 and 24, men between the ages of 25 and 34, women 18 and 24, etc. While looking at this, it is showing me that women are drinking some specific brands of energy drinks. I really want to focus on men. So I want to edit this. I can do that again in a couple of ways. I can edit expression and I can search here for more categories. Personally, I prefer the composer. I am going to come here. You see this is where we have all of our categories. I'm going to work with this cross tab I already have, but I'm going to do a couple of things. I'm going to delete all of my rows and confirm. And what I'm going to do, I want to look just at men. So I'm going to look for search for gender and drop and drag that over to a base. I'm going to add that to my base. In the past, we've used the base has been the entire study. By changing the base, what this does is this only shows me information about men. The base will be men. When I want to look at age, I'm going to do, let's see, 18 to 24, 34, let's do 35 to 44. I'm going to add that. Now I also want to look at income on individual. So you'll see the different, I'm going to do less than 25,000 and then I'm going to come up here and do, I'm going to look at a range, let's go all the way up to here. Now I could do a bulk join and look at the different ages and all of these incomes, or I could look at them individually. I am actually going to do a bulk join, which means I'm going to do an and, and then I'm going to add this to my row and I'm going to run my report. So let's talk about what we are looking at. So again this total, total number of people in this sample, number of people that are, these two categories intersect. Since we are looking at total, we are looking at men. I'm actually going to scroll over so I'm looking just at energy drinks and I am going to get rid of this. I'm going to edit this so it makes it a little easier to read. So when reading this report, I'm going to scroll over, I made some edits to the column just to make it a little easier to read. I didn't do everything. So this is age 18 to 24, making less than 25,000. This is age 18 to 24, making 25 to 29,000. Now remember our cross tab, our base is men. So when we read this, we have to remember that we are looking at all men. I want to scroll over, you see we have a lot of numbers with asterisks, but it's still giving us the up arrow. Again, this is the idea that this is, might be considered unstable data. That means it's a smaller sample. When you start creating categories like this, ages and an income, you can often get fairly small samples. When we scroll over, you'll see some examples where we're actually running to seven people in the sample. It's saying this is a bad category, they're not a whole lot of people between the ages of 18 and 24, making less than 25,000 that are drinking five-hour energy drink. That's a pretty small sample, so that's something to think about, and you'll even see some categories where you're getting like one person in a sample. So I'm going to skip over some of those. Let's look at some of the, where it looks like there's a little more kind of activity. Let's look at Red Bull, so we've got Red Bull sugar-free, Red Bull regular, other Red Bull. These are still some smaller samples, ages 18 and 24, 25,000, less than 25,000, but how we would read this, remember we're looking at all men, of all men who drink regular Red Bull, 4.2% of them, this is where we read the vertical number, 4.2% of them between the ages of 18 and 24 and make less than 25,000. Of all men between the ages of 18 and 24 who make less than 25,000, 8.3% of them drink regular Red Bull, they are 40% more likely than the average. Now if we scroll down a little bit to some slightly bigger numbers where there are some changes, this is, let's see, I didn't edit all of the changes here, but you can actually see where some of these changes, let's look at an older group, let's get down to 25, this is 25 to 34, people making between 40 and 45,000, or men, I'm doing that. So of all men who drink regular Red Bull, 6% of them between the ages of 25 and 34 and make 40 to 45, is that it, yeah. Of all men between the ages of 25 and 34 who make between 40 and 45,000, 26.9% of them drink Red Bull regular. If we come over, we'll see more of that. Now this is a good way to show you the index. So this index is 797, that's huge, but that also means they are seven times more likely. In this case when you look at these numbers, the index tends to follow the horizontal number. As the horizontal number goes up, the index goes up. What I'm seeing just in general, men between the ages of 25 and 34 are drinking Red Bull. And this category in particular seems to be, they seem to be heavy energy drink users in general. Again, looking at the index, they're all pretty high, again those samples are low, but that is how you read those. Now if we want to change this and we want to go back and see a base of just everyone, I'm going to go back to Composer and I am just going to delete this base and then rerun the report. Now this changes because now we are looking at everyone. We are no longer looking at men or women, just people between the ages of 18 and 24 with a particular income. Now if we just scroll through this a little bit, let's stick with Red Bull again. We see some changes here, 18 to 24, income 25 to 34 again. This was one of the big incomes with just men. It drops a little bit because we are also looking at women. And women don't drink as many energy drinks as men, but this as an age range is still a good one. But that is how you can take a report, run it and it might be okay, but then look at something else. Now if I wanted to save that particular report related on just men before I rerun it, I would want to export it so that I would have that data myself in either an Excel file or an SPC file meaning that I can re-import it and then run it again. So this is an overview on how to do a more advanced search or build a more advanced cross tab in Simmons. If you have any questions, please let me know.