Parameter estimates: Parameter e Estimate e std. Err. + Alternative. DF • T-Stat. P-value *O 131 2.7735131 =0 131 7.507004 <0.0001 =0 131 3.5386467 Intercept 17.966577 6.4779134 0.0064 Father 0.50354896 O.067077219 Mother 0.27714316 0.078318967 0.0006 Analysis of variance table for multiple regression model: Source DF MS F-stat P-value 2 320.94662 160.47331 37.637221 <0.0001 Model Error 131 558.54293 4.2636865 Total 133 879.48955 Summary of fit: Root MSE: 2.0648696 R-squared: 0.3649 R-squared (adjusted): 0.3552
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.
Interpreting a Computer Display. In Exercises 5–8, we want to consider the
Height of Son Identify the following:
a. The P-value corresponding to the overall significance of the multiple regression equation
b. The value of the multiple coefficient of determination R2
c. The adjusted value of R2
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