TABLE 15-9 Many Factors Determine the Attendance at Major LeagueThe Coefficient of Multiple Determination ( R 2 J

The Answer of TABLE 15-9 Many Factors Determine the Attendance at Major LeagueThe Coefficient of Multiple Determination ( R 2 J

TABLE 15-9 Many Factors Determine the Attendance at Major LeagueThe Coefficient of Multiple Determination ( R 2 J

The Answer of TABLE 15-9 Many Factors Determine the Attendance at Major LeagueThe Coefficient of Multiple Determination ( R 2 J

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TABLE 15-9
Many Factors Determine the Attendance at Major League

question 75

Multiple Choice

TABLE 15-9
Many factors determine the attendance at Major League Baseball games. These factors can include when the game is played, the weather, the opponent, whether or not the team is having a good season, and whether or not a marketing promotion is held. Data from 80 games of the Kansas City Royals for the following variables are collected.
ATTENDANCE = Paid attendance for the game
TEMP = High temperature for the day
WIN% = Team's winning percentage at the time of the game
OPWIN% = Opponent team's winning percentage at the time of the game WEEKEND - 1 if game played on Friday, Saturday or Sunday; 0 otherwise PROMOTION - 1 = if a promotion was held; 0 = if no promotion was held

The regression results using attendance as the dependent variable and the remaining five variables as the independent variables are presented below.
$\begin{array}{l}\text { Regression Statistics }\\\begin{array} { l r } \hline \text { Multiple R } & 0.5487 \\\text { R Square } & 0.3011 \\\text { Adjusted R Square } & 0.2538 \\\text { Standard Error } & 6442.4456 \\\text { Observations } & 80 \\\hline\end{array}\end{array}$

$\begin{array}{l}\text { ANOVA }\\\begin{array} { l c c c c c } \hline & \mathrm { df } & \text { SS } & \text { MS } & \text { F } & \text { Significance } \mathrm { F } \\\hline \text { Regression } & 5 & 1322911703.0671 & 264582340.6134 & 6.3747 & 0.0001 \\\text { Residual } & 74 & 3071377751.1204 & 41505104.7449 & & \\\text { Total } & 79 & 4394289454.1875 & & & \\\hline\end{array}\end{array}$

$\begin{array}{lrrrr}\hline&\text{Coefficients}&\text{ Standard Error}&\text{ t Stat}&\text{p-value}\\\hline\text{Intercept}&-3862.4808&6180.9452&-0.6249&0.5340\\\text { Temp } & 51.7031 & 62.9439 & 0.8214 & 0.4140 \\\text { Win\% } & 21.1085 & 16.2338 & 1.3003 & 0.1975 \\\text { OpWin\% } & 11.3453 & 6.4617 & 1.7558 & 0.0833 \\\text { Weekend } & 367.5377 & 2786.2639 & 0.1319 & 0.8954 \\\text { Promotion } & 6927.8820 & 2784.3442 & 2.4882 & 0.0151 \\\hline\end{array}$

$TABLE 15-9 Many factors determine the attendance at Major League Baseball games. These factors can include when the game is played, the weather, the opponent, whether or not the team is having a good season, and whether or not a marketing promotion is held. Data from 80 games of the Kansas City Royals for the following variables are collected. ATTENDANCE = Paid attendance for the game TEMP = High temperature for the day WIN% = Team's winning percentage at the time of the game OPWIN% = Opponent team's winning percentage at the time of the game WEEKEND - 1 if game played on Friday, Saturday or Sunday; 0 otherwise PROMOTION - 1 = if a promotion was held; 0 = if no promotion was held The regression results using attendance as the dependent variable and the remaining five variables as the independent variables are presented below. \begin{array}{l} \text { Regression Statistics }\\ \begin{array} { l r } \hline \text { Multiple R } & 0.5487 \\ \text { R Square } & 0.3011 \\ \text { Adjusted R Square } & 0.2538 \\ \text { Standard Error } & 6442.4456 \\ \text { Observations } & 80 \\ \hline \end{array} \end{array} \begin{array}{l} \text { ANOVA }\\ \begin{array} { l c c c c c } \hline & \mathrm { df } & \text { SS } & \text { MS } & \text { F } & \text { Significance } \mathrm { F } \\ \hline \text { Regression } & 5 & 1322911703.0671 & 264582340.6134 & 6.3747 & 0.0001 \\ \text { Residual } & 74 & 3071377751.1204 & 41505104.7449 & & \\ \text { Total } & 79 & 4394289454.1875 & & & \\ \hline \end{array} \end{array} \begin{array}{lrrrr} \hline&\text{Coefficients}&\text{ Standard Error}&\text{ t Stat}&\text{p-value}\\ \hline\text{Intercept}&-3862.4808&6180.9452&-0.6249&0.5340\\ \text { Temp } & 51.7031 & 62.9439 & 0.8214 & 0.4140 \\ \text { Win\% } & 21.1085 & 16.2338 & 1.3003 & 0.1975 \\ \text { OpWin\% } & 11.3453 & 6.4617 & 1.7558 & 0.0833 \\ \text { Weekend } & 367.5377 & 2786.2639 & 0.1319 & 0.8954 \\ \text { Promotion } & 6927.8820 & 2784.3442 & 2.4882 & 0.0151 \\ \hline \end{array} The coefficient of multiple determination ( R 2 j) of each of the 5 predictors with all the other remaining predictors are, respectively, 0.2675, 0.3101, 0.1038, 0.7325, and 0.7308. j -Referring to Table 15-9, what is the correct interpretation for the estimated coefficient for PROMOTION? A) The estimated mean paid attendance on promotion day will be 6927.88 higher than when there is no promotion taking into consideration all the other independent variables included in the model. B) The paid attendance on promotion day will be 6927.88 higher than when there is no promotion taking into consideration all the other independent variables included in the model. C) The estimated mean paid attendance on promotion day will be 6927.88 higher than when there is no promotion. D) The paid attendance on promotion day will be 6927.88 higher than when there is no promotion.$

$TABLE 15-9 Many factors determine the attendance at Major League Baseball games. These factors can include when the game is played, the weather, the opponent, whether or not the team is having a good season, and whether or not a marketing promotion is held. Data from 80 games of the Kansas City Royals for the following variables are collected. ATTENDANCE = Paid attendance for the game TEMP = High temperature for the day WIN% = Team's winning percentage at the time of the game OPWIN% = Opponent team's winning percentage at the time of the game WEEKEND - 1 if game played on Friday, Saturday or Sunday; 0 otherwise PROMOTION - 1 = if a promotion was held; 0 = if no promotion was held The regression results using attendance as the dependent variable and the remaining five variables as the independent variables are presented below. \begin{array}{l} \text { Regression Statistics }\\ \begin{array} { l r } \hline \text { Multiple R } & 0.5487 \\ \text { R Square } & 0.3011 \\ \text { Adjusted R Square } & 0.2538 \\ \text { Standard Error } & 6442.4456 \\ \text { Observations } & 80 \\ \hline \end{array} \end{array} \begin{array}{l} \text { ANOVA }\\ \begin{array} { l c c c c c } \hline & \mathrm { df } & \text { SS } & \text { MS } & \text { F } & \text { Significance } \mathrm { F } \\ \hline \text { Regression } & 5 & 1322911703.0671 & 264582340.6134 & 6.3747 & 0.0001 \\ \text { Residual } & 74 & 3071377751.1204 & 41505104.7449 & & \\ \text { Total } & 79 & 4394289454.1875 & & & \\ \hline \end{array} \end{array} \begin{array}{lrrrr} \hline&\text{Coefficients}&\text{ Standard Error}&\text{ t Stat}&\text{p-value}\\ \hline\text{Intercept}&-3862.4808&6180.9452&-0.6249&0.5340\\ \text { Temp } & 51.7031 & 62.9439 & 0.8214 & 0.4140 \\ \text { Win\% } & 21.1085 & 16.2338 & 1.3003 & 0.1975 \\ \text { OpWin\% } & 11.3453 & 6.4617 & 1.7558 & 0.0833 \\ \text { Weekend } & 367.5377 & 2786.2639 & 0.1319 & 0.8954 \\ \text { Promotion } & 6927.8820 & 2784.3442 & 2.4882 & 0.0151 \\ \hline \end{array} The coefficient of multiple determination ( R 2 j) of each of the 5 predictors with all the other remaining predictors are, respectively, 0.2675, 0.3101, 0.1038, 0.7325, and 0.7308. j -Referring to Table 15-9, what is the correct interpretation for the estimated coefficient for PROMOTION? A) The estimated mean paid attendance on promotion day will be 6927.88 higher than when there is no promotion taking into consideration all the other independent variables included in the model. B) The paid attendance on promotion day will be 6927.88 higher than when there is no promotion taking into consideration all the other independent variables included in the model. C) The estimated mean paid attendance on promotion day will be 6927.88 higher than when there is no promotion. D) The paid attendance on promotion day will be 6927.88 higher than when there is no promotion.$ $TABLE 15-9 Many factors determine the attendance at Major League Baseball games. These factors can include when the game is played, the weather, the opponent, whether or not the team is having a good season, and whether or not a marketing promotion is held. Data from 80 games of the Kansas City Royals for the following variables are collected. ATTENDANCE = Paid attendance for the game TEMP = High temperature for the day WIN% = Team's winning percentage at the time of the game OPWIN% = Opponent team's winning percentage at the time of the game WEEKEND - 1 if game played on Friday, Saturday or Sunday; 0 otherwise PROMOTION - 1 = if a promotion was held; 0 = if no promotion was held The regression results using attendance as the dependent variable and the remaining five variables as the independent variables are presented below. \begin{array}{l} \text { Regression Statistics }\\ \begin{array} { l r } \hline \text { Multiple R } & 0.5487 \\ \text { R Square } & 0.3011 \\ \text { Adjusted R Square } & 0.2538 \\ \text { Standard Error } & 6442.4456 \\ \text { Observations } & 80 \\ \hline \end{array} \end{array} \begin{array}{l} \text { ANOVA }\\ \begin{array} { l c c c c c } \hline & \mathrm { df } & \text { SS } & \text { MS } & \text { F } & \text { Significance } \mathrm { F } \\ \hline \text { Regression } & 5 & 1322911703.0671 & 264582340.6134 & 6.3747 & 0.0001 \\ \text { Residual } & 74 & 3071377751.1204 & 41505104.7449 & & \\ \text { Total } & 79 & 4394289454.1875 & & & \\ \hline \end{array} \end{array} \begin{array}{lrrrr} \hline&\text{Coefficients}&\text{ Standard Error}&\text{ t Stat}&\text{p-value}\\ \hline\text{Intercept}&-3862.4808&6180.9452&-0.6249&0.5340\\ \text { Temp } & 51.7031 & 62.9439 & 0.8214 & 0.4140 \\ \text { Win\% } & 21.1085 & 16.2338 & 1.3003 & 0.1975 \\ \text { OpWin\% } & 11.3453 & 6.4617 & 1.7558 & 0.0833 \\ \text { Weekend } & 367.5377 & 2786.2639 & 0.1319 & 0.8954 \\ \text { Promotion } & 6927.8820 & 2784.3442 & 2.4882 & 0.0151 \\ \hline \end{array} The coefficient of multiple determination ( R 2 j) of each of the 5 predictors with all the other remaining predictors are, respectively, 0.2675, 0.3101, 0.1038, 0.7325, and 0.7308. j -Referring to Table 15-9, what is the correct interpretation for the estimated coefficient for PROMOTION? A) The estimated mean paid attendance on promotion day will be 6927.88 higher than when there is no promotion taking into consideration all the other independent variables included in the model. B) The paid attendance on promotion day will be 6927.88 higher than when there is no promotion taking into consideration all the other independent variables included in the model. C) The estimated mean paid attendance on promotion day will be 6927.88 higher than when there is no promotion. D) The paid attendance on promotion day will be 6927.88 higher than when there is no promotion.$

$TABLE 15-9 Many factors determine the attendance at Major League Baseball games. These factors can include when the game is played, the weather, the opponent, whether or not the team is having a good season, and whether or not a marketing promotion is held. Data from 80 games of the Kansas City Royals for the following variables are collected. ATTENDANCE = Paid attendance for the game TEMP = High temperature for the day WIN% = Team's winning percentage at the time of the game OPWIN% = Opponent team's winning percentage at the time of the game WEEKEND - 1 if game played on Friday, Saturday or Sunday; 0 otherwise PROMOTION - 1 = if a promotion was held; 0 = if no promotion was held The regression results using attendance as the dependent variable and the remaining five variables as the independent variables are presented below. \begin{array}{l} \text { Regression Statistics }\\ \begin{array} { l r } \hline \text { Multiple R } & 0.5487 \\ \text { R Square } & 0.3011 \\ \text { Adjusted R Square } & 0.2538 \\ \text { Standard Error } & 6442.4456 \\ \text { Observations } & 80 \\ \hline \end{array} \end{array} \begin{array}{l} \text { ANOVA }\\ \begin{array} { l c c c c c } \hline & \mathrm { df } & \text { SS } & \text { MS } & \text { F } & \text { Significance } \mathrm { F } \\ \hline \text { Regression } & 5 & 1322911703.0671 & 264582340.6134 & 6.3747 & 0.0001 \\ \text { Residual } & 74 & 3071377751.1204 & 41505104.7449 & & \\ \text { Total } & 79 & 4394289454.1875 & & & \\ \hline \end{array} \end{array} \begin{array}{lrrrr} \hline&\text{Coefficients}&\text{ Standard Error}&\text{ t Stat}&\text{p-value}\\ \hline\text{Intercept}&-3862.4808&6180.9452&-0.6249&0.5340\\ \text { Temp } & 51.7031 & 62.9439 & 0.8214 & 0.4140 \\ \text { Win\% } & 21.1085 & 16.2338 & 1.3003 & 0.1975 \\ \text { OpWin\% } & 11.3453 & 6.4617 & 1.7558 & 0.0833 \\ \text { Weekend } & 367.5377 & 2786.2639 & 0.1319 & 0.8954 \\ \text { Promotion } & 6927.8820 & 2784.3442 & 2.4882 & 0.0151 \\ \hline \end{array} The coefficient of multiple determination ( R 2 j) of each of the 5 predictors with all the other remaining predictors are, respectively, 0.2675, 0.3101, 0.1038, 0.7325, and 0.7308. j -Referring to Table 15-9, what is the correct interpretation for the estimated coefficient for PROMOTION? A) The estimated mean paid attendance on promotion day will be 6927.88 higher than when there is no promotion taking into consideration all the other independent variables included in the model. B) The paid attendance on promotion day will be 6927.88 higher than when there is no promotion taking into consideration all the other independent variables included in the model. C) The estimated mean paid attendance on promotion day will be 6927.88 higher than when there is no promotion. D) The paid attendance on promotion day will be 6927.88 higher than when there is no promotion.$

The coefficient of multiple determination ( R ²_j) of each of the 5 predictors with all the other remaining predictors are, respectively, 0.2675, 0.3101, 0.1038, 0.7325, and 0.7308.
$j$
-Referring to Table 15-9, what is the correct interpretation for the estimated coefficient for PROMOTION?

Definitions:

Unconditioned Response

The response normally produced by the conditioned response (e.g., salivation being produced by food).

External Locus

A belief system where individuals perceive their outcomes and experiences as being controlled by external forces or fate rather than their own actions.

Internal Locus

The belief that one's actions and outcomes are a result of personal decisions and efforts rather than external factors.

Self-Actualization

The need to actualize or "make actual" your unique talents and abilities.