How well does the line describe the data? What is the mileage that you would expect a 4000-pound car to have?
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.
From the Scatter plot:
Regression equation is
where, intercept and slope
value is 0.751.
Regression line best fits the data if the differences between the observations and the predicted values are small and unbiased (fitted values are not too high or too low).
R-squared is also called Coefficient of Determination. R-squared value represents smaller differences between the observed data values and the fitted values. It explains the variation in the dependent variables with respect to the change in the independent variables.
Since, , we can say that the regression model best fits the data. In other words, 75% of variation in Y is explained by the variation in X.
Larger the R-squared value, better the regression model fits the data.
And since the slope of the line is downwards, there appears to be a negative linear correlation between the two variables. All the data points are closer to the line. So, there are no outliers.
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