A study was done to look at the relationship between number of movies people watch at the theater each year and the number of books that they read each year. The results of the survey are shown below.   Movies 8 2 7 9 9 2 0 7 4 4 9 Books 0 8 0 0 0 4 9 0 1 0 0   The equation of the linear regression line is:    ˆyy^ =   + xx    (Please show your answers to two decimal places)   Use the model to predict the number of books read per year for someone who watches 6 movies per year. Books per year =  (Please round your answer to the nearest whole number.)   Interpret the slope of the regression line in the context of the question:   For every additional movie that people watch each year, there tends to be an average decrease of 0.88 books read. The slope has no practical meaning since people cannot read a negative number of books. As x goes up, y goes down. Interpret the y-intercept in the context of the question: If someone watches 0 movies per year, then that person will read 7 books this year. The y-intercept has no practical meaning for this study. The best prediction for a person who doesn't watch any movies is that they will read 7 books each year. The average number of books read per year is predicted to be 7 books.

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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.