The file NFCEast.csv has information on NFL games hosted by NFC East teams in 2019 and 2020. The variable team1 gives the name of the hosting team, the variable ELO classifies the home teams according to their probability of winning (determined from the elo_prob1 columns - E1 represents a probability of winning that is less than 0.25, E2 less than 0.5, E3 less than 0.75, and E4 greater than 0.75). The response variable Diff gives the amount that the home team won (positive value) or lost (negative value) by.

A. Use R studio and first perform a single factor ANOVA for Elo.

1. What are the null and alternative hypotheses?

2. Is the null hypothesis rejected or not? Why? What conclusion can be drawn?

3. What percentage of the variability in y is explained for by Elo?

4. Use Tukey's test to determine with Elo pairs have a statistically significant difference.

B. Now perform a single factor ANOVA for team1

1. What are the null and alternative hypotheses?

2. Is the null hypothesis rejected or not? Why? What conclusion can be drawn?

3. What percentage of the variability in y is explained by team1?

4. Use Tukey's test to determine with team1 pairs have a statistically significant difference.

C. Next, perform a two factor ANOVA with replication

1. What is the null and alternative hypotheses for the interaction effect.

2. Is the null hypothesis rejected? Why or why not? What conclusion can be drawn?

NFCEast.csv: https://docs.google.com/spreadsheets/d/1wjKKcfR7Pm6Vjm5YiU5vrWGu2phDD82wVtRF2RaoUQU/edit?usp=sharing