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).

In multiple regression analysis, a problem that is not found in simple linear regressions can be caused by the correlation among the independent variables. This problem is called… …multicollaboration …multicollinearity …multicultural …correlation collateral damage

3. Setup: The data set "Healthy Breakfast" contains, among other variables, the Consumer Reports ratings of 77 cereals and the number of grams of sugar contained in each serving. (Data source: Free publication available in many grocery stores. Data set available through the Statlib Data and Story.) Considering "Sugars" as the explanatory variable and "Rating" as the response variable generated the following regression line: Rating = 59.3-2.40 - Sugars. and the ANOVA table Source Regression Error Total SS df MS 8654.7 1 8654.7 102.35 6342.1 75 84.6 14996.8 76 F Questions: (a) Write down the simple linear regression model and its model assumption. (b) State the null and alternative hypotheses for the model. Based on the ANOVA table, draw conclusion based on the p-value for the test. (c) Obtain Srz and the standard error se (3₁) to construct the 95% confidence interval for $₁.

Section 10.2 Question #11 The data show the number of viewers for television stars with certain salaries. Find the regression​ equation, letting salary be the independent​ (x) variable. Find the best predicted number of viewers for a television star with a salary of ​$11million. Is the result close to the actual number of​ viewers, 3.3 million? Use a significance level of 0.05.   Salary​ (millions of​ $) 108 15 2 15 3 8 4 14   Viewers​ (millions) 9.1 9.3 10.9 1.3 4.8 4.8 3.2 1.8   View the critical values of the Pearson correlation coefficient r. Critical values of the pearson correlation coefficient r n α=0.05 α=0.01 ​NOTE: To test H0​: ρ=0 against H1​: ρ≠​0,reject H0if the absolute value of r is greater than the critical value in the table. 4 0.950 0.990 5 0.878 0.959 6 0.811 0.917 7 0.754 0.875 8 0.707 0.834 9 0.666 0.798 10 0.632 0.765 11 0.602 0.735…

Café Michigan's manager, Gary Stark, suspects that demand for mocha latte coffees depends on the price being charged. Based on historical observations, Gary has gathered the following data, which show the numbers of these coffees sold over six different price values: Price $2.70 $3.40 $1.90 $4.10 $3.00 $4.00 Using simple linear regression, and given that the price per cup is $1.80, the forecasted demand for mocha latte coffees will be cups (enter your response rounded to one decimal place). Number Sold 765 510 980 245 320 480

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 Demand for Guitars 3 4 5 8 6 5 9 6 8 8 6 9 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=0+0x