The weight of a car can influence the mileage that the car can obtain. A random sample of 20 cars’ weights and mileage is collected. The table for the weight and mileage of the cars is given below. Use Excel to find the best fit linear regression equation, where weight is the explanatory variable. Round the slope and intercept to three decimal places. Weight Mileage30.0 32.220.0 56.020.0 46.245.0 19.540.0 23.645.0 16.725.0 42.255.0 13.217.5 65.435.0 28.027.5 49.927.5 35.130.0 31.225.0 29.540.0 25.622.5 43.435.0 28.927.5 35.022.5 38.845.0 17.2 Answer: y = ___ x + ___
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.
The weight of a car can influence the mileage that the car can obtain. A random sample of 20 cars’ weights and mileage is collected. The table for the weight and mileage of the cars is given below. Use Excel to find the best fit linear regression equation, where weight is the explanatory variable. Round the slope and intercept to three decimal places.
30.0 32.2
20.0 56.0
20.0 46.2
45.0 19.5
40.0 23.6
45.0 16.7
25.0 42.2
55.0 13.2
17.5 65.4
35.0 28.0
27.5 49.9
27.5 35.1
30.0 31.2
25.0 29.5
40.0 25.6
22.5 43.4
35.0 28.9
27.5 35.0
22.5 38.8
45.0 17.2
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