Shown below is a portion of a computer output for regression analysis relating to Y (dependent variable) and X (independent variable).
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.
Please subparts: Qustions 4 and 5. Thank you.
Shown below is a portion of a computer output for
ANOVA
df SS
Regression 1 24.011
Residual 8 67.989
Coefficients Standard Error
Intercept 11.065 2.043
x -0.511 0.304
- What has been the sample size of the above?
- Perform a t test and determine whether or not X and Y are related. Let level of significance= 0.05
- Perform an F test and determine whether or not X and Y are related. Let level of significance=0.05
- Compute the coefficient of determination.
- Interpret the meaning of the value of the coefficient of determination that you found in (4). Be specific.
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