 The pattern of exam is 40 months, you all know. So, we have so many practicals, 40 months. Out of these, 10 months is for whatever which will happen, I have to know. So, 2 weeks, 4 examiners, we have 2.5 months, so 10 in week. Followed by Unico social case. Unico social case. One case, 12 months. This has a major junk. Then you have exercise, 2 exercise, 4 months each, so 8 months. Squatters, 5 squatters, 1 mark each, we view 5 months. We have 1 mark each, 5 to 5. So, totally we have 40 months in practical. So, all of this, this 22 marks, more of a subject to examiner. So, examiner decides the way how to present, performing the direct exams. These are all, this has a, this has a quality knowledge component. We have problem key, that is, you get 100% 2 marks. So, that is why in this class, we are going to see about exercise. Okay. So, we have selected 7 set of problems. And in the end of the class, I will explain about what are the problems we have missed. So, we often discuss about the problems of each exercise. So, we have first, in statistics, finishing calculation. So, this is, these are all measures of subject and unseen. These are all measures of, these 2 are measures of, that is, in the set of values. And this is the range of the values are disclosed, are varying. One variable is the varying region. So, that is called as range and standard deviation. So, that means equal to sum of equations, central value. So, you have to assign all the list of values. Arrange the values in an ascending order or in a descending order. Let me work on the middle value. If the total number of values are in odd number, then it will be easy. Suppose for example, 5 values are there, that means, the third value will be the middle value. So, the total number, you have n plus 1 by 2. If you have 10 numbers, that is even number of values. Then you have to, most number of, these 3 are the measures of central tendency, measures of central tendency. And this, measures of this question we have, range, which is given by the formula, maximum. So, this indicates all the values are spread from, then we have standard deviation. Sigma x minus x bar, the whole square, divided by n minus 1. This n minus 1 is there, if the values are less than 30 samples. If it is more than 30 samples, then you can just feed this n, instead of n minus 1. So, the formula will be over x minus x bar. So, whenever you push this x bar, x bar is nothing but your view. So, mean is other x plus x bar. So, in standard deviation, we have to have a serial number. If suppose we have 5 values means, we have to put up serial numbers like this. Then the particular value, suppose we have 7, 8, like that means, then we have to calculate the values. That is mean, then we have to calculate x minus x bar. Then x minus x bar of the whole square. Then we have to sum up it. This will give sigma x minus x bar of the whole square. When you divide it by, take the measures of central and this portion. Now, from this we can calculate some more. That is standard error. Standard error is given by the formula, standard deviation divided by root of n. Where as test is called a standard deviation and root of n is the sample size. So, from this is the standard error, standard error of mean. This is standard error of mean. When you are calculating confidence interval, confidence interval which is nothing but plus or minus 2 standard error. So, you will calculate standard deviation. From here you will calculate standard error. From here, you will derive this confidence interval that is nothing but mean plus or minus 2 standard error. Then you can calculate coefficient of variation. Coefficient of variation by mean into 100. So, in this problem we are going to explain the more measures of central difference that is mean, mean and more. Mean is the average, mean is the central value, mode is the most retreated number. Dispersion is range is maximum minus minimum value. Standard deviation is given by the formula. Root of x minus, sigma x minus x minus equals to n minus only in the sample is 30. If it is more than 30, it is just the n. So, for standard deviation of table like this, the values can be mean, x minus x bar, So, sigma x minus x bar is elements called as mean deviation. It is elements from the range and standard deviation. What you can derive or calculate is mean deviation standard error of mean which is given by the power of standard deviation divided by root of n. How long do you have seen about mean median mode? That is, measures of central tendency measures of dispersion. So, sigma x minus x bar, mean deviation, then standard error of mean that is standard deviation root of n, confidence interval which is mean plus or minus 2 standard error, coefficient of variation is given by the power of standard deviation mean equal to 100. So, these 4 things mean standard error confidence interval, coefficient of variation. These 4 things are as which you can derive from this commonly as measures of central tendency dispersion. We will move on to the next problem. So, the second problem is about the tests of significance. So, tests of significance, so that we will improve at the end. If the p value is less than 0.05, then we call it as significant. So, for that we need to say the high hypothesis which 2 variables you are associating. Usually you have to define the alternative hypothesis that is association. The hypothesis says there is no association, nothing means nothing. So, there is no association. So, smoking, lung cancer smoking you have like this, you randomly get these 4 groups randomly. So, you want to say if there is association that is your alternative hypothesis. If there is no association, then there is a if that is what is none like hypothesis. So, you have to mention what is your hypothesis that is the first statement by a specter. Then you have to calculate the chi-square value. So, like how we put a table for, we have to put a table here. So, what is the So, what is the expected value of the expected value of the expected value of the expected value? What is the expected value of the expected value of the expected value of the expected value of the expected value of the expected value of the expected value of the expected value of the expected value of the expected value of the expected value of the expected value of the expected value of the expected value of the expected value of the expected value of the expected value of the expected value of the expected value of the expected value of the expected value of the expected value of the expected value of the expected value of the expected value of the expected value of the expected value of the expected value of the expected value of the expected value of the expected value of the expected value of the expected value of the expected value of the expected value of the expected value of the expected value of the expected value of the expected value of the expected value of the expected value of the expected value of the expected value of the expected value of the expected value of the expected value of the expected value of the expected value of the expected value of the expected value of the expected value of the expected value of the expected value of the expected value of the expected value of the So, this is calculated by the power bar rho minus 1 into so, rho in exams most of the two bar rho means that it will be 4 3 bar rho 3 bar rho means 3 minus 1 into 2 minus 1 which will give you 2, 3 divided by 22. So, here most of the in your exams you need to be 1. Then after getting this calculated is taking a freedom and getting this time struggle value we have to look at the power of it in some days this table may be provided and 2 bar is given for you we may not when the kites value is greater than 3.84 for freedom 1 0.05. Remember this number that the p value is going to be less than 0.05 p value less than 0.05 indicates that there is a significant significant association to be. So, in that case if p value is less than 0.05 it is not like what this is. If greater than 0.05 then max of not like like this. First test our significance p use that is the kites value test. Then we are moving on standard address which is the standard error of difference between proportion and p. Example here is till even moving level the quotient here is I know this here is this difference significantly different are not. Same way the proportion means the percentage of this 15 percent value there is a difference of 2 percent value is this 2 percent and significant difference are not. So, this is the our itself portion. So, based on this we have to formulate the hypothesis first as we does here as we did in kites value test. So, now this is our aim of this is from this we are going to calculate the z value which is given by the formula actual difference the standard error of standard error of difference between means are proportion. So, now I am just going to focus only on in this case we can find out that the actual difference is actually that difference between the e and the s standard error of difference between this is given by the formula by proportion this is given as root of p 1 q 1 divided by this is the formula. So, here I am concerned about what is p p is your equivalence 100 minus p which will be 87. Then you calculate then you calculate 3.84 is the magical number here the magical number is 1.96 if the number is more than 1.96 then you say there is a significant difference that is p value will be less than 0.35. Instead of p 1 q 1 you substitute the formula with standard deviation here the standard deviation which is square root of 2. So, then you calculate means then substitute here then you calculate the p is 1.96 2 means. So, that is the number is the number you have to remember. So, that is about the third problem significant standard error of difference between two means are proportion. Three important steps standard which I will introduce we have a different. So, the first step in the most important is you are calculating very carefully in assessing the water level three different types of wells that is cylindrical cylindrical rectangular is the only way to find out. So, here we use that which consists of six. So, in the third cup turns blue which means you need six grams of mixing powder mixing powder to disinfect 4.55 liters of water here you can ask why here is 4.55 liters of water. So, six grams of mixing powder is needed to disinfect 4.55 liters of water. So, this is the basic principle. So, based on this we need to calculate so, we just need to multiply the part part amount of the mixing powder here you need not only amount of the water. So, amount of mixing powder added is needed to disinfect place which come which is with this part you will get this thing. So, in this calculation you have got this which is equal to 1000 liters you get it in your view you have got it. So, when you substitute the meter with the mixing powder this is the second step. Then the third step as I said it is going to be you should make a bucket. So, not 100 grams of mixing powder. You have to put the mixing powder then put water make it into a paste then add water up to two thirds of the mixing powder this is your line. So, mixing powder is nothing but gas so, you have to remove this CAO if you do not remove this CAO when it goes into the weather. So, further this is the steps these are the steps we need to paste and remove this line. Remove this line and what is the super light pollution should be added. You have to tie it to a row insert it to the middle agitate vertically, horizontally as the then only you can tie this under graphs. So, if your total is 600 grams means then you have to do it twice. So, here is three calculations this should be on the top. So, I have mentioned two rules that this should be on the top and the problems we will do there. Exposure here outcome there. So, this is a basic law for two work to be able to take case control study. So, if you can make this table perfectly then half of the calculations are done. So, here we get a particular values case control study, you can calculate arts mentioned arts is nothing but your chance of business. So, arts is you know the arts of arts ratio is these other ways called as cross product ratio very easy. So, with this 99% of the problems over and what is the 20% it is you have to write the interpretation property. The similar measure what you get there is you get you have 8 times more chance of getting a lung cancer, but in arts ratio you say among lung cancer equation being a shocker will be 8 times more. So, it is a retrospective study. So, we have to be very careful in that interpretation. Then second is the cohort setup this is the outcome should be on the top. Exposure should be here see what you can calculate is incidence that is incidence among the exposed these are all the exposed to. Here you can calculate that this is the exposed to. Incidence among the exposed is incidence among exposed. Incidence among un exposed there is C by C plus D this is incidence. Now, related risk is given by the formula incidence of incidence among exposed divided by incidence among un exposed. So, the interpretation I mean here is tends if the ready risk is k then if you have to say being a smoker is a ready risk interpretation. Then we can calculate two more values here that is add interval risk. Always add interval risk yes. If suppose I remove smoothing from this continuity how much amount of lung cancer can hold its amount of lung cancer is directly at smoothing. So, that is that is the it is given by the cohort incidence among exposed divided by incidence among un exposed divided by incidence among exposed. It is given by the cohort by incidence among reported population minus incidence among un exposed divided by incidence among the population. This all these three related risk add interval risk population is at its interpretation we have seen. Then the last one is where screening screening as I said here holds standard then the test what about the test says are not. So, positive positive negative this is the test positive. The test says positive actually this is so positive this is so negative this is for honestly positive this is for honestly negative. Now, you can calculate four values for the predictive value. So, how do you know? Because if you do good for you you will remember the power of the sum. But predict you well if it is positive predictive values all piece will be there. Positive predictive value is here TPLT values all the pieces will be there two will be on the top always remember two will be on the top. So, all these four power plus two will be on the top. So, this is given by the power of the TPLT means this negative predictive value is out of the total predicted positive predictive values of possible and negatives. Then we have specificity and sensitivity. Sensitivity to have a number in this way. Sensitivity among pieces sensitivity is possibility among pieces. Sensitivity among pieces. Specificity is negativity among things. If you remember this phrase properly. Sensitivity is possibility among pieces. Specificity is negativity among pieces. So, two are possible. I said two will be on the top here two negative will be on the top. So, positively these are all put in the pieces. This is two negative plus. This and here it will be exactly the same for positive predictive value all pieces will be there for negative predictive values all pieces will be there. Here if it is positively among pieces you can easily do this. And it will be the exact opposite of this. These two will be the exact opposite. So, this is the sensitivity. A test which is put has put sensitivity is used as a screening test. A test which has put specificity is used as a screening test. So, here the four letter is the key here. You can remember this way. Sensitivity means this is first screening. More letter is the specificity more letter is other screening. So, in your interpretation if you have values of screening sensitivity and specificity then you can mention whether it can be the test can be considered as an automated test or a screening test easily. Now, this is the 6th loop. Indicators. Indicators you can do it into modernity. Modernity. Modernity. Modernity. This is modernity followed by specificity and the abstinence care indicators. Modernity care indicators. Then malaria and malaria indicators. This has just formed us. You have to know the definition of that particular word. Then express it in the person that you are glad that you have to. So, modernity. Modernity became divided into incidence and prevalence. This will be again called as rate. So, whenever you mention rate you have to mention the periods, specific time, what time it is. Under incidence rate the commonly used are incidence, attack rates, second rate rate. Second rate is attack rate. Incidence is given by the form of total number of new cases divided by total population. I don't know population at this time. Incidence total population. And usually it was in person days. Sometime it would be in thousands. If the incidence is very less in this much less than 1, they mentioned it per thousand or per 10% population. But whatever it is you have to mention the incidence rate that year. So, there are three important components. One of them is value. Then you have attack rate. Attack rate is same as your incidence. One thing is in the denominator here is total number of cases. One thing is the total population. Epidemics outbreaks. That is during outbreaks, population risk. This was the important thing in the attack rate. Then second rate attack rate, which means over exposed to that particular business will get the second rate attack rate. These are all incidental prevalence, point prevalence. This January to December, new cases will come and go. This is how many cases are there? This is called as point prevalence. It is 70,000 cases per 100 population. This is like a bad cases and now you can express it. Per thousand population. Most of the cases are crude and dead rate. It is called crude and dead rate. Because like it is company, it is company, it is company, it is company. This is crude because it rate as total number of deaths. If you should always mention about policy birth of some population, if it is with births, then that is called as crude birth rate. It must be dead rate. This second rate attack rate is called as killing power of the business. This is all this expressing 100, which means that this is with 100% vitality. Means all the cases there, out of the total number of deaths of the business. Which means total number of deaths. So this means if you go process, proportional number of deaths in this area, out of 100 deaths, 10 deaths will give you to go process. So that is also expressing 100. Then past this week, again past this week means, here is extra total number of deaths, degree 3, total number of deaths in that age. In that age, in the gender indicators of vitality are announced at the MCH gap. So first and foremost is your CVF, that is the new birth rate. As the name of the number of the population number of lying birth, all the student population will be in middle population. MCH gap, you should understand what is between abortion, what is between this three births, what is between the human and what is between the infant. So in this picture, this is the picture given in mark. This is the point of view. If the child still births more than 30 centimetres, then we conclude this to date. This is called as still birth rate. Infants, they are not the same. Within one month, we have to get a date. This is one week. We will always have a budget except for your still birth and pre-regulated mortality rate, which has more live births and still births also. So now what are the response from the pre-regulated care, which is given after the week of the delivery. And the obstetric care, which is given before the end of this preregulated month is going to complete this work. So here in human activity, still birth, neonatal, and births, plus three births in the top. Then you can calculate, 75. So in out of the top, I don't get the examination right. Incidents. Here in the top, we do. And we say, if you replace this slide path, this path here, so to show all the, then that will become slide path. In the same way, instead of slide postage, you would slide, you would have this filiria. Filiria, this slide path of this. Symptom, I mean filiria. This is related. Combining these two, it will become filiria, et cetera, et cetera. In unit, you get all five. You have to say population and population in year. So whenever you mention this denominator, you have to stop one more important, which is, if I just, then one lap, this thing. So whatever the denominator will be, it is mentioned, you have to say, 150 maternal years. Well, one lap in the year, in year. So what is maternal year? Any, better, any, which are raised, which are raised, due to the complications of pregnancy, delivery, and postpartum period within 42 days. This is 15 years, maternal year. This is called as maternal part of life. It is called as ratio. You replace the total reproductive age group man, maternal one. We are controlling this indicators. In this class, we have seen about six set of problems, which will be commonly encountered. We have missed a few in this problem. That is, we have not covered about T test, which in some problems set. So you can add a T test. Then they will give the water. Then water quality interpretation is prescription of a diet. Then they will give an upgrade in the investigation. So you can read out this, this will be of more theory. There will be any follow-up on this. So you can read out this thing. Thank you.