We ended Chapter 9 with a discussion of hypothesis testing for equality of two variances. If the null hypothesis cannot be rejected, then the assumptions we made about the equality of variances in Chapter 9 are justified. The test statistic used was F-statistic which will be helpful in solving some problems in Chapters 10, 11 and 12.
We started the new Chapter 10 by first looking at a farming problem where the farmer is trying to determine whether she should use low, medium or high level of fertilizer to maximize the yield. To obtain samples we use experimental design with one factor.
The hypothesis that all levels of fertilizer are equally effective is tested using Analysis of Variance (ANOVA). We compare the between and within group variabilities which leads to a one-sided F-test. We found in the example that we can reject the equality hypothesis with a very low p value. We then looked at the confidence intervals for the differences between the means to see if one particular level of fertilization is better than the others. Chapter 10 ended by solving the same problem using MegaStat and examining the Summary Table which includes all the numbers we found manually.
In Week 11 we will do the course evaluations.
