A random sample of online music video views and number of guitar sales was measured, and the computer output for regression was obtained: Coefficients Standard Error t Stat P-value Intercept 7.856710924 1.316226455 5.969118 0.001889 Music Video Views 0.094781123 0.027926367 3.393965 0.019378 R-sq. = 69.73%R-sq. (adj) = 63.68% Part A: Use the computer output to determine the LSRL. Identify all the variables used in the equation. Part B: What proportion of the variation of guitar sales is explained by its linear relationship to music video views? Explain. Part C: Determine if increased guitar sales were caused by online music video views. Explain your reasoning.

Explained below.

Step-by-step explanation:

The regression analysis output is as follows:

                       Coefficients          Standard Error         t Stat            P-value

Intercept        7.856710924          1.316226455         5.969118       0.001889

Music Video   0.094781123         0.027926367        3.393965      0.019378

Views

R-sq. = 69.73%

R-sq. (adj) = 63.68%

A

There are two variables used in this study, the independent and the dependent variable.

The independent variable is the number of online music video views and the dependent variable is the number of guitar sales.

B

The coefficient of determination R² specifies the percentage of the variation in the dependent variable (Y) that is forecasted or explained by linear regression and the forecaster variable (X, also recognized as the independent-variable).

Thus, the proportion of the variation of guitar sales that is explained by its linear relationship to music video views is 69.73%.

C

The least square regression line is:

The least square regression line implies that there is a positive relationship between the guitar sales and music video views. That is as the number of music video views increases the guitar sales increases. And vice-versa.

Thus, increased guitar sales were caused by online music video views.

step-by-step explanation:

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