A regression analysis was conducted to investigate the relationship between the total charge and travel time for a certain car service. Computer output from a linear regression analysis is shown below. The analysis was performed on a sample of 24 observations. Term CoefCoef SE CoefSE Coef Constant −1.55−1.55 0.945 Travel time 0.22 0.023 Assume that the conditions for inference for the slope of the regression equation have been met. Which of the following defines the margin of error of a 90 percent confidence interval for the slope of the least-squares regression line? 1.321(0.945)1.321(0.945) A 1.717(0.945)1.717(0.945) B 1.717(0.22)1.717(0.22) C 1.321(0.023)1.321(0.023) D 1.717(0.023) E
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.
A
| Term | CoefCoef | SE CoefSE Coef |
|---|---|---|
| Constant | −1.55−1.55 | 0.945 |
| Travel time | 0.22 | 0.023 |
Assume that the conditions for inference for the slope of the regression equation have been met. Which of the following defines the margin of error of a 90 percent confidence interval for the slope of the least-squares regression line?
-
1.321(0.945)1.321(0.945)
A -
1.717(0.945)1.717(0.945)
B -
1.717(0.22)1.717(0.22)
C -
1.321(0.023)1.321(0.023)
D -
1.717(0.023)
E
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