A study was recently performed by an agency in which it attempted to develop a regression model to explain variation in highway mileage ratings of new cars. At one stage of the analysis, the estimate of the model took the form below, 1, if standard transmission the vehicle weight and x2 = Complete parts a through e. 0, if automatic transmission y = 34.33 -0.003x, +4.46x2 a. Interpret the regression coefficient for variable x,. Choose the correct answer below. A. Holding constant the effects of x2, as the vehicle weight increases by 1 pound, the average highway mileage rating decreases by 0.003. O B. The regression coefficient associated with variable x, is the y-intercept. OC. Holding constant the effects of x,, as the vehicle weight decreases by 1 pound, the average highway mileage rating increases by 4.46. O D. Holding constant the effects of x2, as the vehicle weight increases by 1 pound, the average highway mileage rating decreases by 4.46. b. Interpret the regression coefficient for variable x2. Choose the correct answer below. A. Holding constant the effects of x,, a car with a standard transmission has an average highway mileage rating that is 4.46 higher than a car with an automatic transmission. O B. Holding constant the effects of x,, a car with a standard transmission has an average highway mileage rating that is 4.46 lower than a car with an automatic transmission. OC. The regression coefficient associated with variable x, is the y-intercept. O D. Holding constant the effect of x2 a car with an automatic transmission has an average highway mileage rating that is 0.003 lower than a car with a standard transmission. c. Present an estimate of a model that would predict the average highway mileage rating for an automobile with a standard transmission as a function of the vehicle's weight. (Simplify your answers. Type integers or decimals.)
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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