E. Non-parametric statistics does not use the values of μμ or σσ . True False F. When data points are widely spaced around the regression line, the coefficient of correlation is close to 1. True False G. If the value of the y intercept of the regression line is positive, then the coefficient of correlation could be negative. True False
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.
E. Non-parametric statistics does not use the values of μμ or σσ .
- True
- False
F. When data points are widely spaced around the regression line, the coefficient of
- True
- False
G. If the value of the y intercept of the regression line is positive, then the coefficient of correlation could be negative.
- True
- False
H. ANOVA can tell which mean is different.
- True
- False
I. If a confidence interval for the difference of 2 proportions is found and the interval contains 0, it suggests the proportions are the same.
- True
- False
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