Module #8 Assignment

 For this assignment, we are expected to run an ANOVA hypothesis test. 

1. Firstly, it is necessary to combine the individual response data into three separate vectors to identify the ratings of the high, moderate, and low stress groups.

 Once this is done, binding these vectors into a data frame using the as.data.frame and cbind function is the next step to structure these data into a single command. The stack function allows the data to be illustrated in a more readable and accessible manner before running the ANOVA function. 

Using the Oneway.test function provides information on the F value, the numerator df, denominator df, and the p-value of the data under the assumption that the variances are equal.  

2. The second question asks us to use the ISwR :: zelazo package. The data matrix is as follows:

I wasn't sure how to approach this question, so I opted to use the t-test to glean some information so I could determine some useful characteristics about the set. Since I am writing this after the due-date, and for my own benefit, I employ the answer key to help guide me to the correct next-step. Using the same process as in Question 1, I created a data frame from the zelazo package.

Next, I stacked the data, as before. 

Then, I conducted a one-way T-test.

Although my numbers are different from those posted, I chalk this up to a misinput of the data or a mistake on my end. Again, this is being done for the purpose of practicing this process and becoming familiar with conducting these tests. 

When the ANOVA test is run, the results show that the null hypothesis, that there is not evidence of significant differences between babies that are trained and those that are not, cannot be rejected, as the p-value is greater than the significance level (0.05 < 0.2239).