Complete parts (a) through (c) using the following data Row 1 Row 2 90 69 75 90 (a) Find the equation of the regression line for the given data, letting Row 1 represent the x-values and Row 2 the y-values. Sketch a scatter plot of the data and draw the regression line. Input the values of the slope and intercept for the regression line when Row 1 represents the x-values. y = (Round to three decimal places as needed.) Construct a scatter plot of the data and draw the regression line. Plot Row 1 on the horizontal axis and Row 2 on the vertical axis. Choose the correct graph below. O A. OB. OC. OD. (b) Find the equation of the regression line for the given data, letting Row 2 represent the x-values and Row 1 the y-values. Sketch a scatter plot of the data and draw the regression line. Input the values of the slope and intercept for the regression line when Row 2 represents the x-values. y= _x+ (Round to three decimal places as needed.) Construct a scatter plot of the data and draw the regression line. Plot Row 2 on the horizontal axis and Row 1 on the vertical axis. Choose the correct graph below. OA. OB. Oc. OD. (c) What effect does switching the explanatory and response variables have on the regression line? O A. The value of m is unchanged, but the sign of m and value of b change. OB. The sign and value of m is unchanged, but the value of b changes. OC. The value of b is unchanged, but the sign and value of m change. OD. The sign of m is unchanged, but the values of m and b change. O E. The sign and value of m and the value of b all change. OF Nothing changes.
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.
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