Research & Evaluation Ii

Regression Paper: MLB

Introduction

Within this paper, we will be conducting a hypothesis test to answer the research question of whether the number of wins of a team can be explained linearly by the size of stadium, ERA, and stolen bases. To perform this test we will be using a given data set called Major League Baseball Data along with the Hypothesis test for independent groups. To get the calculations we need, we will input the data received into Mega Stat; the attach Appendixes show the results.

The 5 steps in Hypothesis Testing

Step 1: State the Hypothesis

As stated above this paper will be determining whether or not the number of wins can be determined linearly by the ERA, stolen bases, and size of the stadium. In order to show this we need to set up a null and alternative hypothesis showing what we are trying to test. For all further purposes in this paper we will be testing to conclude if we can accept or reject the following null hypothesis. H0: All of the coefficients are zero. If we do reject the null hypothesis we will be able to safely say we can go with the alternative which is, H1: At least one coefficient is non-zero.

Step 2: State the Significance level

The significance level is used to set up a decision rule within the next step of the test. Normally if we will be using the p-value as a decision rule we stat the significance level as .01, .05, or .10. For this paper we will set the level at .05 to test the p-value against.

We can also use the critical value for F in this test and set up another decision rule that shows when we should reject null depending on the value of F for our data set. In order to find the F value we should use to reject or accept the null we have to know the significance level of .05 and also the degrees of freedom set up for the data set. If we look at the Mega stat results for this regression analysis we see that the degrees of freedom set up are 3 and 26. We take this information and look at the Appendix...