Question

The management of a professional baseball team is in the process of determining the budget for next year. A major component of future revenue is attendance at the home games. In order to predict attendance at home games, the team statistician has used a multiple regression model with dummy variables. The model is of the form y = β0 + β1x1 + β2x2 + β3x3 + ε, where: y = attendance at a home game. x1 = current power rating of the team on a scale from 0 to 100 before the game. x2 and x3 are dummy variables, and they are defined below. x2 = 1, if weekend, x2 = 0, otherwise. x3 = 1, if whether is favorable, x3 = 0, otherwise. After collecting the data, based on 30 games from last year, and implementing the above stated multiple regression model, the team statistician obtained the following least squares multiple regression equation and output as follows: y= - 1050 + x1 + 2200x 2 + 5400x 3 Sb1 = 800, Sb2=1000,Sb3 = 1850 Assume that the overall model is useful in predicting game attendance. The team statistician wants to know if the mean attendance is higher on the weekends as compared to the weekdays.

Please show work!!!!

a. discuss the importance of linear regression use beyond sports.

b.State the appropriate null and alternative hypotheses.

c.At α = .05, test to determine if the attendance is higher at weekend home games.

Answer 1

A) Linear Regression : This is defined as a basic and commonly used type of predictive analysis

Mainly there are three major uses for regression analysis , They are as follows

(1) determining the strength of predictors

, (2) forecasting an effect,

(3) trend forecasting.

Here they are several types of linear regressions , they are :

a) Simple linear regression

b) Multiple linear regression

c) Ordinal regression

d) Logistic regression

e) Multinominal regression

B) Null Hypothesis : This hypothesis defines that a population parameter is equal to hypothesized value and this is also a mutually exclusive statements

Alternative Hypothesis : The hypothesis that defines that population parameter is may be smaller or greater, or different than the hypothesized values and also this can be one - sided or two - sided , this is also called a mutually exclusive statements.