Let the Explanatory Variable represent the age of a sample of seven randomly selected men. Let the Response Variable represent the corresponding cholesterol measurements of these men. Explanatory Variable: 39, 52, 47, 43, 63, 58, 69 Response Variable: 189, 238, 220, 215, 244, 236, 248 (a) What is the equation of the regression line for this sample data? The y-intercept of your equation must be to three decimal places and the slope of your equation must be to four decimal places. A. y = 2.1664x + 142.336 B. y = 1.8653x + 105.698 C. y = 1.7283x + 135.543 (b) Using the equation of your regression line from (a) above what is the predicted cholesterol measurement when a man is 60 years old? Your answer must be to four places. A. 239.2410 B. 272.3200 C. 217.6160
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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