Which of the following is FALSE? 1. If the linear relationship is significant, we expect larger total sum of squares (SST) than sum of squares regression (SSR). If two variables are very strongly associated, the coefficient of determination II. will near to +1 or -1. III. Changing the units of measurement for x or y changes the correlation coefficient. O 1, Il and III O II O I and II only O Il and III only
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.
![Which of the following is FALSE?
If the linear relationship is significant, we expect larger total sum of squares (SST)
than sum of squares regression (SSR).
If two variables are very strongly associated, the coefficient of determination
will near to +1 or -1.
I.
I.
III.
Changing the units of measurement for x or y changes the correlation coefficient.
O 1, Il and III
II
O I and II only
O Il and III only](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2Fda89dda1-46c8-4606-a079-e1d7f739d419%2F61f0311c-8ed0-4466-92fc-951a340dd572%2Fvp9w8p_processed.png&w=3840&q=75)
![In regression, the sum of squares regression (SSR) measures the variability in the
dependent variable about the regression line.
TRUE
FALSE](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2Fda89dda1-46c8-4606-a079-e1d7f739d419%2F61f0311c-8ed0-4466-92fc-951a340dd572%2F8qwg0ce_processed.png&w=3840&q=75)
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