iven are five observations for two variables, x and y. xi 5 9 13 17 20 yi 50 54 46 23 11 The estimated regression equation for these data is ŷ=0.6+2.6x a. Compute SSE, SST, and SST (to 2 decimals) and show work. SSE=________ SST=_________ SSR=_________ b.Compute the coefficient of determination r^2. Comment on the goodness of fit. The least squares line provided a good fit; ________% of the variability in y has been explained by the estimated regression equation (to 3 decimal). Show work. c. Compute the sample correlation coefficient. Enter negative value as negative number. Show work. ___________________
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.
Given are five observations for two variables, x and y.
xi | 5 | 9 | 13 | 17 | 20 |
yi | 50 | 54 | 46 | 23 | 11 |
The estimated regression equation for these data is ŷ=0.6+2.6x
a. Compute SSE, SST, and SST (to 2 decimals) and show work.
SSE=________
SST=_________
SSR=_________
b.Compute the coefficient of determination r^2. Comment on the goodness of fit. The least squares line provided a good fit; ________% of the variability in y has been explained by the estimated regression equation (to 3 decimal). Show work.
c. Compute the sample
___________________
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