The following estimated regression equation based on 10 observations was presented. ý = 29.1970 + 0.5509x, + 0.4920x, Here, SST = 6,722.125, SSR = 6,211.375, s. = 0.0819, and s, = 0.0567. (a) Compute MSR and MSE. (Round your answers to three decimal places.) MSR = MSE = (b) Compute Fand perform the appropriate F test. Use a = 0.05. State the null and alternative hypotheses. Hoi ßg> B2 Ho: B, + 0 and B, + 0 H: One or more of the parameters is equal to zero. * 0 and B, = 0 H: B, - 0 and B2 0 %3D Hoi B1 = 82 = 0 : One or more of the parameters is not equal to zero. Find the value of the test statistic. (Round your answer to two decimal places.) F = Find the p-value. (Round your answer to three decimal places.) p-value = | State your conclusion. O Reject H,. There is sufficient evidence to conclude that the overall model is significant. Do not reject Ho. There is sufficient evidence to conclude that the overall model is significant. Reject H,. There is insufficient evidence to conclude that the overall model is significant. Do not reject Hg. There is insufficient evidence to conclude that the overall model is significant.
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.
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