Mark Gershon, owner of a musical instrument distributorship, thinks that demand for guitars may be related to the number of television appearances by the popular group Maroon 5 during the previous month. Gershon has collected the data shown in the following table: Maroon 5 TV Appearances 3 4 7 8 Demand for Guitars 3 6 7 10 7 This exercise contains only parts b, c, and d. b) Using the least-squares regression method, the equation for forecasting is (round your responses to four decimal places): Y = .6757 + 1.0286 x c) The estimate for guitar sales if Maroon 5 performed on TV 9 times = 9.93 (round your response to two decimal places d) The correlation coefficient (r) for this model = 0.8230 (round your response to four decimal places). The coefficient of determination (F) for this model = .677329 (round your response to four decimal places). The percentage of variation in sales that can be explained by TV appearances = % (round your response to two decimal places).
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.
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