A linear regression model was fit to a set of data containing 18 observations. The computer output of the regression analysis is shown in the table. Term CoefCoef SE CoefSE Coef TT Constant 12.00 5.43 2.210 xx 0.694 0.241 2.880 Assume the conditions for regression are met. Which of the following defines the margin of error when a 95 percent confidence interval for the slope of the least-squares regression line is calculated? (1.75)(0.241) A (1.75)(0.694) B (1.96)(0.241) C (2.12)(0.241)) D (2.12)(0.694)
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 linear regression model was fit to a set of data containing 18 observations. The computer output of the
| Term | CoefCoef | SE CoefSE Coef | TT |
| Constant | 12.00 | 5.43 | 2.210 |
| xx | 0.694 | 0.241 | 2.880 |
Assume the conditions for regression are met. Which of the following defines the margin of error when a 95 percent confidence interval for the slope of the least-squares regression line is calculated?
-
(1.75)(0.241)
A -
(1.75)(0.694)
B -
(1.96)(0.241)
C -
(2.12)(0.241))
D -
(2.12)(0.694)
E
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