The regression equation attached has been fitted to 20 data points. The means of x1 and x2 are equal to 25 and 40 respectively. The sum of squared differences between observed and predicted values of y have been calculated to be SSE = 133.5, and the sum of squared differences between y and the mean of y is SST = 490.8. Determine the following: a. The multiple standard error of estimate. b. The approximate 95 percent confidence interval for the mean of y whenever x1 = 22 and x2 = 29. c. The approximate 95 percent prediction interval for an individual y value whenever x1 = 22 and x2 = 29. d. Calculate and interpret the coefficient of determination for this regression
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.
The regression equation attached has been fitted to 20 data points. The means of x1 and x2 are equal to 25 and 40 respectively. The sum of squared differences between observed and predicted values of y have been calculated to be SSE = 133.5, and the sum of squared differences between y and the mean of y is SST = 490.8. Determine the following:
a. The multiple standard error of estimate.
b. The approximate 95 percent confidence interval for the mean of y whenever x1 = 22 and x2 = 29.
c. The approximate 95 percent prediction interval for an individual y value whenever x1 = 22 and x2 = 29.
d. Calculate and interpret the coefficient of determination for this regression
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