The following estimated regression equation based on 10 observations was presented. ŷ = 25.1270 + 0.5309x1 + 0.4920x2 Here, SST = 6,738.125, SSR = 6,221.375, sb1 = 0.0818, and sb2 = 0.0563. Perform a t test for the significance of β1. Use α = 0.05. State the null and alternative hypotheses. a. H0: β1 > 0 Ha: β1 ≤ 0 b. H0: β1 ≠ 0 Ha: β1 = 0 c. H0: β1 < 0 Ha: β1 ≥ 0 d. H0: β1 = 0 Ha: β1 > 0e. H0: β1 = 0 Ha: β1 ≠ 0 5. Find the value of the test statistic. (Round your answer to two decimal places.) 6. Find the p-value. (Round your answer to three decimal places.) p-value = 7. State your conclusion. a. Do not reject H0. There is sufficient evidence to conclude that β1 is significant. b. Reject H0. There is insufficient evidence to conclude that β1 is significant. c. Reject H0. There is sufficient evidence to conclude that β1 is significant. d. Do not reject H0. There is insufficient evidence to conclude that β1 is significant. 8. Perform a t test for the significance of β2. Use α = 0.05. State the null and alternative hypotheses. a. H0: β2 ≠ 0 Ha: β2 = 0 b. H0: β2 = 0 Ha: β2 ≠ 0 c. H0: β2 > 0 Ha: β2 ≤ 0d. H0: β2 < 0 Ha: β2 ≥ 0e. H0: β2 = 0 Ha: β2 > 0 9. Find the value of the test statistic. (Round your answer to two decimal places.) 10. Find the p-value. (Round your answer to three decimal places.)
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.
H0: β1 > 0 |
Ha: β1 ≤ 0 |
H0: β1 ≠ 0 |
Ha: β1 = 0 |
H0: β1 < 0 |
Ha: β1 ≥ 0 |
H0: β1 = 0 |
Ha: β1 > 0 |
H0: β1 = 0 |
Ha: β1 ≠ 0 |
H0: β2 ≠ 0 |
Ha: β2 = 0 |
H0: β2 = 0 |
Ha: β2 ≠ 0 |
H0: β2 > 0 |
Ha: β2 ≤ 0 |
H0: β2 < 0 |
Ha: β2 ≥ 0 |
H0: β2 = 0 |
Ha: β2 > 0 |
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