Okay, two way ANOVA we use these two way ANOVA when we have two independent variables in our we can calculate a two way ANOVA using something that is so I will copy the data. So this is data see payable one Okay. See the robo one okay okay so we get data MBK is a two way ANOVA by using something like this ANOVA data below one tool database to pass data variable tree to a data equal to data. So, we can do something like this to ANOVA data variable one two data variable to process the data they will tree then data equals data. So let me check the formula data variable one two data variable to data availability data equals data okay 123 okay then then to see the p value we will use a summary day you can see the p value we will Use the summary summary fee okay so we have the p value here so degree of freedom sum of square mean of square f and you have we have the p value here Okay, so the result is that developer one does not depend on variable to mean and variable three mean, they are about one minute they're about to mean as a p value of 0.4.
A tree, which is smaller than 0.05. has a fail to reject a null hypothesis or variable i mean is the same as terrible to me. The null hypothesis is true to 95%, complete and interval. Variable one mean and variable three mean has a p value of 0.4 to two which is more than 0.05 has a view to reject a null hypothesis or variable one meaning is the same as they were about three means Then the hypothesis is true to 95% confidence interval. So variable one does not depend on their own word to mean. And variable three mean variable i mean and variable to mean has a p value of 0.53. So variable y mean and their elbow to me has a p value of 0.4 18 mec elbow on me available to me has a p value of 0.5 Okay as a photo Richard and I participate a lot but this is true Okay.
There we go I mean and the robot to me is a p value of 0.42. So I will say, ah, they will bow why mean there'll be one mean and variable to me may have a p value of 0.93 train ah Hello case. So, 0.9 tree tree is more than 0.05 is 0.9 tree tree is more than 0.05 has a feel to each other now hypotheses are variable i mean is the same as zero to me the null hypothesis is true 95% confidence interval variable awami and the robot to me has a p value okay has a feel to reject the null hypothesis. So we can say the variable one mean and variable trimming, the p value is 0.904 is more than 0.05. So we fail to reject a null hypothesis. So if you reject our null hypothesis our variable y mean is the same as our failover tree mean so the now hypothesis is true to 95% confidence interval so this mean is variable one mean is the same as a variable to me.
Variable y mean is SMS available to me