Select the correct scatter diagram from the options above. 4 Does a simple linear regression model appear to be appropriate? A simple linear regression model does not appear to be appropriate. V Round your answers to four decimal places. b. Develop an estimated multiple regression equation with z = Weight and z? = WeightSq as the two independent variables. 11376 8 WeightSq 728 Weight + 12 c. Use the following dummy variables to develop an estimated regression equation that can be used to predict the price given the type of bike: Type_Fitness =1 if the bike is a fitness bike, 0 otherwise; and Type_Comfort = 1 if the bike is a comfort bike; otherwise. Compare the results obtained to the results obtained in part (b). 1284 O 572 O Type_Fitness - 907 8 Type_Comfort Type of bike appears to be a(n) significant factor in predicting price. But, the estimated regression equation developed in part (b) appears to provide a slightly better fit. d. To account for possible interaction between the type of bike and the weight of the bike, develop a new estimated regression equation that can be used to predict the price of the bike given the type, the weight of the bike, and any interaction between weight and each of the dummy variables defined in part (c). What estimated regression equation appears to be the best predictor of price? Please round to four decimal places. 215 O Weight - Type_Fitness - Type_Comfort + & WxF + WxC 5924 6343 7232 261 266

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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.