A college bookstore must order books two months before each semester starts. They believe that the number of books that will ultimately be sold for any particular course is related to the number of students registered for the course when the books are ordered. They would like to develop a best fitting line to predict how many books to order. From past records, the bookstore obtains the number of students registered, X, and the number of books actually sold for a course, Y , for 12 different semesters. A scatterplot of the data along with the best fitting line is presented below. a. The correlation between the two variables is r = .89. Calculate and interpret the value of r2. b. The equation for the best fitting line is Y = 9.30 + 0.673X. Explain and interpret the value of 9.30. c. How many books should the store order for a class of 50 students? Would you trust this prediction?
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.
A college bookstore must order books two months before each semester starts. They believe that the number of books that will ultimately be sold for any particular course is related to the number of students registered for the course when the books are ordered. They would like to develop a best
fitting line to predict how many books to order. From past records, the bookstore obtains the number of students registered, X, and the number of books actually sold for a course, Y , for 12 different semesters.
A scatterplot of the data along with the best fitting line is presented below.
a. The
b. The equation for the best fitting line is Y = 9.30 + 0.673X. Explain and interpret the value of 9.30.
c. How many books should the store order for a class of 50 students? Would you trust this prediction?
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