Five observations taken for two variables follow. 4 5 11 4 13 40 40 40 50 20 A. Compute the sample covariance (to 1 decimal and enter negative value as negative figure). B. Compute the sample correlation coefficient (to 3 decimals and enter negative value as negative figure). C. What can you conclude, based on your computation of the sample correlation coefficient? - Select an answer: There is a strong positive linear relationship There is a moderate positive linear relationship There is neither a positive nor a negative linear relationship There is a strong negative linear relationship There is a moderate negative linear relationship
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.
Five observations taken for two variables follow.
| 4 | 5 | 11 | 4 | 13 | |
| 40 | 40 | 40 | 50 | 20 |
|
A. Compute the sample
B. Compute the sample
C. What can you conclude, based on your computation of the sample correlation coefficient? - Select an answer:
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