 Hello all, in this video I am going to demonstrate about how to calculate p-value using chi-square test. Before going to the presentation, I want to ensure two things. That is, you should be clear about what is p-value. If you are not clear about p-value, I would request you to see the video of mine which is displayed in the cards above. The second thing I want to ensure is the situation where chi-square test is used. That is when the chi-square test is used. It is used for testing the significance of difference between two proportions or categories. Here in this example, we are looking for association between two variables such as gender and the result outcome. In gender we have two subgroups that is male and female. In results we have two groups that is pass and fail. Here the difference in results between male and female is significant or not. To answer this, we are going to apply chi-square test. There are three methods to apply chi-square test and calculate p-value. One is the manual calculation, second one is online calculators, third one is using software's example SPSS. Here now first I am going to demonstrate how to calculate manually. There are four steps in chi-square test that is number one is stating the hypothesis. We need to state the alternative hypothesis or the research hypothesis and the null hypothesis. Null hypothesis says that there is no significant difference between two categories whereas the alternate or the research hypothesis says there is a significant difference between two categories. The second step is calculating the chi-square test value. So we need to calculate the expected values of the each cell. So how we are going to calculate this expected value of each cell is by applying the formula row total into column total divided by grand total for each cell value. Here is this example. In the same example of comparing association between gender and results, what appears in the cell is the observed value that is actually the observed value. We need to calculate the expected values for this particular cell. We need to calculate using the column total into row total divided by grand total. So by applying this, the expected value of this particular cell will become 87.5. Likewise, we need to calculate the expected value of all the cells. Then we need to calculate sigma observed minus expected whole square divided by expected. That will give the chi-square value. So we need to calculate sigma observed minus expected whole square divided by expected values that will yield the chi-square value. So in the second step, we will arrive at the chi-square test value. In the third step, we move on to the calculation of degree of freedom, which is calculated by the simple formula column minus 1 into row minus 1. So for any 2 bar 2 table, the degree of freedom is going to be 1. The fourth step in calculating the chi-square value is looking for p-value in the probability table. So this is the probability table where degree of freedom is in the y-axis and p-value is in the x-axis. So the chi-square test values are substituted here. We need to look into the 0.05 level, significance level for p-value with the degree of freedom. You can witness as the p-value decreases, the chi-square value increases. When the chi-square test value is greater than 3.84, then we can say p-value is less than 0.05, that is significant. We need to remember this particular value 3.84 for calculation of chi-square in 2 bar 2 table. For the critical value of p-value less than 0.05, the test value will be greater than 3.84. Now we have completed the manual application of chi-square and calculation of p-value through probability table. Now we are moving into the second step of using the online calculators. So what you need to do is just you have to type online chi-square calculator in the Google page, then you will get many results. I am going to demonstrate the first result appeared here. So I am just going to open this tab. So the calculator online chi-square calculator will appear like this. We need to enter the details. Here I am entering the group names. Many of the chi-square calculators will not ask for this group and category names. So I am entering the cell values 85, 15. So it will ask for the significance level. Usually we will keep at 0.05 level. So we need to calculate chi-square for this. Test result is given here. The chi-square statistic is value, statistical value is 1.149. We all know the critical value is 3.84. Anything less than 3.84 will yield p-value greater than 0.05. So here the p-value is greater than 0.05 that is 0.28. So the result is not significant at p-value less than 0.05. So with this we are moving from online calculators to softwares or SPSS. Now I am going to demonstrate how to calculate chi-square value using SPSS. Here I have already imported a data. So this is a study about smartphone addiction. So I am going to demonstrate for association between the presence of smartphone addiction and living with grandparents. So I am going to analyze here. So we all know in SPSS there will be different tabs available here. In that I am going to click analyze. In that I am going to click descriptive statistics. I repeat in analyze descriptive statistics. Then under which I am going to click cross tabs. So I am going to click this living with grandparents in row. In this case the exposure variables will be in the row and the outcome variable will be in the column. Since they are living with grandparents can be an exposure to become addicted to smartphone. In statistics we need to click this chi-square continue. In cells we need to click the row percentages and continue. I am clicking ok cross tabs will appear here. So from this 2 bar to table we need to infer the following. So here present and absent are altered. So out of the 100 children living with their grandparents 19.7 percentage are having smartphone addiction compared to only 14.7 percentage who are not living with their grandparents. By looking at this percentages it seems that there is an increase in smartphone addiction among children who are living with their grandparents. But when we look into the p value here this is the p value which we should consider. This is 0.114 which is not significant that is greater than 0.05 so it is not significant. Even though there was an increase in smartphone addiction among children who are living with their grandparents it is not statistically significant. So that is the inference. Most important thing in SPSS is what we get here as asymptomatic two sided along the PSN chi-square value is the p value. Hopefully this presentation was useful. Thank you for watching this video. 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