Based on the analyst's data and regression line, complete the following.(a) For these data, values for earnings per share that are greater than the mean of the values for earnings per share tendto be paired with current stock prices that are (Choose one) v the mean of the current stock prices.(b) According to the regression equation, for an increase of one dollar in earnings per share, there is a correspondingincrease of how many dollars in current stock price? A financial analyst is examining the relationship between stock prices and earnings per share. She chooses fifteen publicly traded companies at random andrecords for each the company's current stock price and the company's earnings per share reported for the past 12 months. Her data are given below, with xdenoting the earnings per share from the previous year, and y denoting the current stock price (both in dollars). Based on these data, she computes the least-squares regression line to be y = -0.137 +0.043x. This line, along with a scatter plot of her data, is shown below.Earnings per share, x(in dollars)Current stock price, y(in dollars)59.102.3530.891.3440.951.7629.501.0248.191.6337.291.6821.650.6315.950.631-26.451.020.532.261.5317.720.7842.861.50Earnings per share(in dollars)36.451.1757.562.8440.321.06Current stock price(in dollars)

Here, the slope of the regression is positive which represents there is a direct relationship…

Answered: ed on the analyst's data and regression…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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Using the data, run a regression where you control for “Promotion,” and test the effect of “Wins” on “Attendance”. What should be the attendance if the number of wins is 10? Wins Promotion Attendance 4 29500 36300 6 55700 40100 6 71300 41200 8 87000 53000 6 75000 44000 7 72000 45600 5 55300 39000 7 81600 47500
Using the regression to model annual income, a variable for years of education has a slope = 2000. This means that the model predicts each additional year of education will yield an extra 2,000 for the average person's salary, regardless of how many total years of education a person has. A. True B. False
A researcher that there is a linear association between the level of potassium content (y) in milligrams and the amount of fiber (x) in grams in cereal. The regression line for the data is computed to y=37+28x rate. It was also computed that r=.59 A. What does the value . 59 tell you? B. What does the value 37 tell you? C. What does the value 28 tell you ? 2. For the line in question 1 what percentage of variability in potassium can be explained by variability in fiber?
A statistical program is recommended. The owner of Showtime Movie Theaters, Inc., would like to predict weekly gross revenue as a function of advertising expenditures. Historical data for a sample of eight weeks follow. Weekly Television Gross Newspaper Advertising Advertising ($1,000s) ($1,000s) Revenue ($1,000s) 96 5.0 1.5 90 2.0 2.0 95 4.0 1.5 92 2.5 2.5 95 3.0 3.3 94 3.5 2.3 94 2.5 4.2 94 3.0 2.5 1 (a) Develop an estimated regression equation with the amount of television advertising as the independent variable. (Round your numerical values to two decimal places. Let x₁ represent the amount of television advertising in $1,000s and y represent the weekly gross revenue in $1,000s.) y = 88.64 + 1.60x1 X (b) Develop an estimated regression equation with both television advertising and newspaper advertising as the independent variables. (Round your numerical values to two decimal places. Let x₁ represent the amount of television advertising in $1,000s, x₂ represent the amount of…
Choose the correct answer of each number. 1. An analyst hired by the multinational company to study the sales data of its more than 75 stores worldwide. Used regression analysis to predict $ sales (y) by using $ advertising (x1) and $ salary of sales representatives (x2) across all the branches. You obtained the following regression function: y = 7800 + 8.5x1-1.6x2. If the advertising budgets of one of the branches of the corporation is now $45,000 (which is 10% more than before) and the salary of sales representatives is now $8,500 (which is 20% less than before), then the predicted sales before in that branch is a. $417,750 b. $341,250 c. $376,700 d. $335,6502. An analyst hired by the multinational company to study the sales data of its more than 75 stores worldwide. Used regression analysis to predict $ sales (y) by using $ advertising (x1) and $ salary of sales representatives (x2) across all the branches. You obtained the following regression function: y = 7800 + 8.5x1-1.6x2. If…
Develop a scatterplot and explore the correlation between customer age and net sales by each type of customer (regular/promotion). Use the horizontal axis for the customer age to graph. Find the linear regression line that models the data by each type of customer. Round the rate of changes (slopes) to two decimal places and interpret them in terms of the relation between the change in age and the change in net sales. What can you conclude? Hint: Rate of Change = Vertical Change / Horizontal Change = Change in y / Change in x
A regression analysis between sales ( Y in $1,000 ) and advertising (X in $1,000) resulted in the following equation = 14,200 + 2.6 X The above equation implies that … … an increase of $ 14,200 in advertising is associated with an increase of $ 14,200 in sales … an increase of $ 1,000 in advertising is associated with an increase of $ 14,200 in sales … an increase of $ 2,600 in advertising is associated with an increase of $ 1,000 in sales … an increase of $ 1,000 in advertising is associated with an increase of $ 2,600 in sales
Using the data, run a regression where you control for “Promotion,” and test the effect of “Wins” on “Attendance”. Does “Promotion” have a significant effect on “Attendance”? Wins Promotion Attendance 4 29500 36300 6 55700 40100 6 71300 41200 8 87000 53000 6 75000 44000 7 72000 45600 5 55300 39000 7 81600 47500
A grocery store is interested in how customers' income affects the amount of money they spend each week. A regression analysis is performed to test this analysis. The results of the analysis are that the intercept is $17.80 and the slope is 0.0012. Based on these results, what is the predicted weekly grocery expenditure (to the nearest cent) for a household with an income of $65,000? $95.80 O$78.00 $45.23 $17.80 Ho: mean weekly expenditure = $78.00
For the data in the table, find the regression equation. Here, x gives the number of years of experience for nurses, and y is their annual salary (in $1000's). Round the slope and y-intercept to two decimals, then use your equation to answer the questions below. Years of Salary Experience ($1000's) 40 4 42 43 45 10 46 13 52 15 53 17 56 21 58 22 60 a. What is the expected salary (in $1000's) for a nurse with no work experience? b. By what amount (in $1000's) does an extra year of experience boost the annual salary?
4)
The fitted regression is Sales = 842 − 37.5 Price. (a-1) If Price = 1, what is the prediction for Sales? (Round your answer to 1 decimal place.) (b) If Price = 20, what is the prediction for Sales?

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