Hello. I apologize for attaching multiple questions but all of them are related to each other. I appreciate your answer:

Question 22 2 pt A large national bank charges local companies for using their services. A bank ofcial reported the results of a regression analysis designed to predict the bank's charges (Y) - measured in dollars per month - for services rendered to local companies. One independent variable used to predict service charges to a company is the company's sales revenue (X)- measured in millions of dollars. Data for 21 companies who use the bank's services were used to t the model: 37:50 +B1Xi 'l'Ei The results of the simple linear regression are provided below: Y = 2, 700 + 20X 35 = 65 two tailed p value : 0.034 (for testing ,81) Interpret the estimate of 50, the Y-intercept of the line. About 95% of the observed service charges fall within $2,700 of the least squares line. For every $1 million increase in sales revenue, we expect a service charge to decrease $2,700. All companies will be charged at least $2,700 by the bank. There is no practical interpretation since the service charges for a sales revenue of $0 does not make sense. Question 23 2 pt: A large national bank charges local companies for using their services. A bank ofcial reported the results of a regression analysis designed to predict the bank's charges (Y) - measured in dollars per month - for services rendered to local companies. One independent variable used to predict service charges to a company is the company's sales revenue (X)- measured in millions of dollars. Data for 21 companies who use the bank's services were used to t the model: 37:50 +l61Xi+5i The results of the simple linear regression are provided below: Y = 2, 700 + 20X 35 = 65 two tailed p value = 0.034 (for testing 31) A 95% condence interval for 31 is (15, 30). Interpret the interval. At the oz = 0.05 level, there is no evidence of a linear relationship between service charge (Y) and sales revenue (X). We are 95% condent that the mean service charge will fall between $15 and $30 per month. You are 95% condent that mean service charge (Y) will increase between $15 and $30 for every $1 million increase in sales revenue (X). You are 95% condent that the sales revenue (X) will increase between $15 and $30 million for every $1 increase in service charge (Y). Question 26 2 pt. A marketing analyst wants to examine the relationship between sales (in $1,000s) and advertising (in $100s) for firms in the food and beverage industry and so collects monthly data for 25 firms. He estimates the model: Sales = Bo + B1 Advertising + & The following table shows a portion of the regression output: Coefficients Standard Error t-stat p-value Intercept 40.10 14.08 2.848 0.0052 Advertising 2.88 1.52 -1.895 0.0608 Which of the following are the competing hypotheses used to test whether the slope coefficient differs from 3? O Ho : B1 = 2.88 H1 : B1 + 2.88 O Ho : B1 = 3 H1 : 1 + 3 O Ho : B1 # 2.88 H1 : B1 = 2.88 O Ho : B1 * 3 H1 : B1 = 3