a) Calculate the least squares estimates of the slope and intercept. What is the estimate of 2? Graph the regression model. (b) Find an estimate of the mean number of games won if the opponents can be limited to 1800 yards rushing. (c) What change in the expected number of games won is associated with a decrease of 100 yards rushing by an opponent?
Correlation
Correlation defines a relationship between two independent variables. It tells the degree to which variables move in relation to each other. When two sets of data are related to each other, there is a correlation between them.
Linear Correlation
A correlation is used to determine the relationships between numerical and categorical variables. In other words, it is an indicator of how things are connected to one another. The correlation analysis is the study of how variables are related.
Regression Analysis
Regression analysis is a statistical method in which it estimates the relationship between a dependent variable and one or more independent variable. In simple terms dependent variable is called as outcome variable and independent variable is called as predictors. Regression analysis is one of the methods to find the trends in data. The independent variable used in Regression analysis is named Predictor variable. It offers data of an associated dependent variable regarding a particular outcome.
2. Montgomery, Peck, and Vining (2001) present data concerning the performance of the 28 National Football League teams in 1976. It is suspected that the number of games won (y) is related to the number of yards gained rushing by an opponent (x). The data are shown in the following table.
(a) Calculate the least squares estimates of the slope and intercept. What is the estimate of 2? Graph the regression model.
(b) Find an estimate of the mean number of games won if the opponents can be limited to 1800 yards rushing.
(c) What change in the expected number of games won is associated with a decrease of 100 yards rushing by an opponent?
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