8. For the following multiple regression which was conducted toattempt to predict the price of yachts based on the independentvariables shown,Regression StatisticsMultiple RR Square0.8905791880.793131289Adjusted R Square 0.7379663Standard Error30.28395534ObservationsANOVAdfSSMSFRegressionResidual?52743.2307415?917.1179509Total1966500Coefficients Standard Errort StatP-valueInterceptAge73.3329162.252761.17799 0.25715-0.138820.05353-2.59326 0.02037LengthNav EqpFlying Bridge3.739840.955683.913280.001380.376440.168762.23061 0.0414017.7075215.578471.13667 0.27351(a). Write down the fitted multiple regression equation(b). Use the p-value approach to test the significance of theindividual regression coefficients at the 5% level ofsignificance(c). Find the percentage variation in the price of yachts that isexplained by the regression model(d). How many yachts were considered in this study?

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8. For the following multiple regression which was conducted to attempt to predict the price of yachts based on the independent variables shown,

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Concept explainers

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.

Question

8. For the following multiple regression which was conducted to
attempt to predict the price of yachts based on the independent
variables shown,
Regression Statistics
Multiple R
R Square
0.890579188
0.793131289
Adjusted R Square 0.7379663
Standard Error
30.28395534
Observations
ANOVA
df
SS
MS
F
Regression
Residual
?
52743.23074
15
?
917.1179509
Total
19
66500
Coefficients Standard Error
t Stat
P-value
Intercept
Age
73.33291
62.25276
1.17799 0.25715
-0.13882
0.05353
-2.59326 0.02037
Length
Nav Eqp
Flying Bridge
3.73984
0.95568
3.91328
0.00138
0.37644
0.16876
2.23061 0.04140
17.70752
15.57847
1.13667 0.27351
(a). Write down the fitted multiple regression equation
(b). Use the p-value approach to test the significance of the
individual regression coefficients at the 5% level of
significance
(c). Find the percentage variation in the price of yachts that is
explained by the regression model
(d). How many yachts were considered in this study?

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