Linear Regression

Linear Regression 1

Linear Regression

Batting Averages Compared To Home Run Averages

Linear Regression 2

Linear Regression

Team A is continuing with our choice of major league baseball for the data set for this week’s assignment. Team A will discuss our hypothesis statement, perform a regression hypothesis test on the data and interpret the results of our hypothesis test. The research question is formulated using a data series from the University of Phoenix library. The data set used is the Major League Baseball data set. Within this data series National and American League statistics are shown. The research question created by Team A is: Does the batting average of the baseball teams compare to the home run averages of the teams? To research this question linear regression analysis will be used. Linear regression analysis is used to describe possible relationships between different variables. This type of testing is useful in areas such as biological, behavioral and social sciences. This will assist in comparing the batting averages versus the home run averages. One of the applications used to plot the data set in a linear regression analysis is scatter plot with a trend line. Team A will use a scatter plot and trend line to determine if the null hypothesis can be rejected. The null hypothesis (H0) is that regression line will be equal to zero. The alternate hypothesis (H1) will be that the regression line will not be equal to zero. A level of significance will be used at .05.

There are two primary reasons for fitting a regression equation to a set of data--first, to describe the data; second, to predict the response from the carrier. The rationale behind the way the regression line is calculated is best seen from the point-of-view of prediction. A line gives a good fit to a set of data if the points are close to it. Where the points are not tightly grouped about any line, a line gives a good fit if...