Let's say that I gave 3 different types of pills or 3 different types of food to people taking a test. And I want to figure out if the type of food people take going into the test really affect their scores? Now, one thing I forgot to mention, with any hypothesis test, we're going to need some type of significance level. Our F statistic is going to be the ratio of our Sum of Squares between the samples-- Sum of Squares between divided by, our degrees of freedom between and this is sometimes called the mean squares between, MSB, that, divided by the Sum of Squares within, so that's what I had done up here, the SSW in blue, divided by the SSW divided by the degrees of freedom of the SSwithin, and that was m n-1.
And our SSwithin was 6 and we had how many degrees of freedom?
If this number is really small and our denominator is larger, that means that our variation within each sample, makes up more of the total variation than our variation between the samples. So this is food 1, food 2, and then this over here is food 3. The probability of getting something this extreme, just by chance, assuming the null hypothesis, is very low.
The true population mean of the group that took food 1 will be the same as the group that took food 2, which will be the same as the group that took food 3. Calculating SST total sum of squares.
Let's say that my null hypothesis is that the means are the same. Obviously I'll never be able to give that food to every human being that could ever live and then make them all take an exam.
Food doesn't make a difference. The F -test can be used to answer the following questions: BATCH 1: If you're seeing this message, it means we're having trouble loading external resources on our website.
Also, 6. So our F statistic is going to be 12.
The summary statistics for each batch are shown below. Does a new process, treatment, or test reduce the variability of the current process?
So we're going to define--we're going to assume our null hypothesis, and then we're going to come up with a statistic called the F statistic.