Pestle ANOVA is the process of testing the mean of two or more groups or two or more variables. So ANOVA So, try to empower factors by comparing the means are different samples. So, for ANOVA hypotheses, now hypotheses mean data sample means are equal or do not have a significant difference the auto hypothesis is when the sample means are not equal. So, for ANOVA now hypotheses mean that ah the mean So, this one this Microsoft is always a mean that means, our first data is equal to mean our second data is equal to the mean of the data is equal to the mean or some other data until the Minerva l data. So, for not hypotheses You mean that are the means are equal, you can just look into it These are parameters here and interpret them for alternate party system minis are not equal. So, for one way ANOVA the one way ANOVA is used to me only about one independent variable.

So, we can do something IDC vital stats dot r f one way, df First Data can df second data k stats da ah should be f test saw one way, one way Okay, the D f all the first data set the land and the second data Said Toby, okay, so we can just print the result. Okay, so we get a status is 1000 tree tree file, so 1335 and the p value is 3.9. So how do we interpret this result? Okay, so to get a p value we use the summary function, okay. So we can interpret a value as the p value is more than 0.05. Hence, we fail to reject that null hypothesis or the main or variable one is the same as the main variable so they're not happy This is true to 95% confidence interval okay so the data now hypothesis that a mean our first variable is equal to mean our second variable okay so and I and it 5% confidence means we are 95% complete and they are the result is our call