CHALLENGEACTIVITY315: Using regression to make predictionsRound answers to two decimal places when appropriate.Jump to level 1A financial advisor wants to determine how the amount of time spent on financial education affects the amount ofdebt.(Amount of t50000400003000020000100001020304050Financial education time (in hours)The equation of the regression line isY = 50000+(–500).A financial education time of 38hours is found to result in an amountof debt of 31000 dollars What isthe predicted amount of debt?dollars€1.23Where is the observed value inrelation to the regression line?PickA financial education time of 32 hours is found to result in aamount of debt of 36887 dollars. What is the predicted amount of debt? Ex 1.23Where is the observed value in relation to the regression line?dollarsPickA financial education time of 27 hours is found to result in aamount of debt of 32562 dollars. What is the predicted amount of debt? Ex: 1.23Where is the observed value in relation to the regression line?dollarsPick2CheckNext>D-0-0-Feedback?

Given the information:Regression line equation:Ŷ = 50,000 + (−500)Xwhere:Ŷ = predictor variable or…

Answered: CHALLENGE ACTIVITY 315: Using…

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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1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 Price/Book Value Ratio Return on Equity 13.032 1.405 8.305 2.113 6.654 1.239 3.262 2.449 5.291 2.398 7.719 0.353 2.569 7.593 5.104 2.012 4.797 2.182 4.129 1.918 1.549 1.951 5.046 2.417 2.159 3.011 1.725 5.582 4.698 Growth% 6.385 11.846 135.669 12.459 0.073 25.092 14.188 8.804 22.766 38.082 18.985 25.696 24.519 19.666 11.624 22.849 49.965 69.649 36.696 3.819 41.139 9.218 29.108 17.772 25.114 29.295 23.764 31.405 9.497 14.759 18.541 12.026 39.016 14.228 39.439 14.097 27.022 14.841 13.237 20.669 17.311 14.887 15.849 5.601 16.775 11.172 8.401 16.161 18.404 23.973 16.673 14.725 46.605 28.839 52.021
The estimated regression model is given : Consumption = 49.13 + 0.85 Income + error Consumption is dependent variable ; Income ( weekly) - family Income Let's say a family income earns $ 100 more per week . How to affect the consumption level? Choose one right answer A. For every 100 $ a family earns more per week in this case the consumption will grow on average and expected of 85 $ worth. B. For every 100 $ a family earns more per week in this case the consumption will fall on average and expected of 49.14 $ worth.
(d) If the life expectancy is increased by 3.5 years in a certain country, how much will the happiness index change? Round to two decimal places. (e) Use the regression line to predict the happiness index of a country with a life expectancy of 84 years. Round to two decimal places.
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
The local coffee shop keeps track of how much coffee they sell versus the temperature on that day, here are their figures: Sales in Php 1651 1757 1437 1525 1349 1231 Temp in Celsius 21.6 22.6 25 27.3 29.8 30.1 Suppose you want to create a regression equation that will predict the total sales in Php using the temperature of the day in Celcius, what is the total sales for the day in Php if the temperature is 31.5? Round your answers to the nearest hundredths.
Table 3 gives the market value of a luxury sedan (in dollars) xyears after its purchase. Find an exponential regression model of the form y= ab* for this data set. Estimate the purchase price of the sedan. Estimate the value of the sedan 10 years after its purchase. Round answers to the nearest dollar. TABLE 3 Value ($) 1 23,125 19,050 3 15,625 11,875 5 9,450 6 7,125 2.
Many small companies buy advertising without considering its effect. The marketing manager is trying to make the case that "you have to spend money to make money." Spending on billboard advertise ments, in the manager's opinion, has a direct effect on sales. These are records for 7 months in 1000s: Monthly expenditure on 21 25 billboards 16 42 34 10 19 Monthly sales Develop a regression estimating equation. If the monthly expenditure on billboards is 20,000/- what is the monthly sale generated 34 14 48 32 26 29 20
Suppose that a simple linear regression model is appropriate for describing the relationship between y = house price (in dollars) and x = house size (in square feet) for houses in a large city. The population regression line is y = 22,500 + 43x and ?e = 4,000. b) Approximately what proportion of 2,000 sq ft homes would be priced over $110,000? (You may need to use a table. Round your answer to four decimal places.) Approximately what proportion of 2,000 sq ft homes would be priced under $100,000? (You may need to use a table. Round your answer to four decimal places.)
The table below shows the average weekly wages (in dollars) for state government employees and federal government employees for 10 years. Construct and interpret a 90% prediction interval for the average weekly wages of federal government employees when the average weekly wages of state government employees is $825. The equation of the regression line is y = 1.597x- 169.203. Wages (state), x Wages (federal), y 742 775 783 802 842 890 912 939 949 954 1,002 1,039 1,097 1,145 1,199 1,242 1,271 1,299 1,335 1,398 Construct and interpret a 90% prediction interval for the average weekly wages of federal government employees when the average weekly wages of state government employees is $825. Select the correct choice below and fill in the answer boxes to complete your choice. (Round to the nearest cent as needed.) O A. There is a 90% chance that the predicted average weekly wages of federal government employees is between S and S given a state average weekly wage of $825. O B. We can be 90%…
The table below shows the average weekly wages (in dollars) for state government employees and federal government employees for 10 years. Construct and interpret a 95% prediction interval for the average weekly wages of federal government employees when the average weekly wages of state government employees is $895. The equation of the regression line is y = 1.454x- 36.984. Wages (state), x Wages (federal), y 712 778 789 801 843 878 927 937 939 958 1,014 1,054 1,116 1,146 1,191 1,248 1,270 1,302 1,335 1,401 Construct and interpret a 95% prediction interval for the average weekly wages of federal government employees when the average weekly wages of state government employees is $895. Select the correct choice below and fill in the answer boxes to complete your choice. (Round to the nearest cent as needed.) O A. We can be 95% confident that when the average weekly wages of state government employees is $895, the average weekly wages of federal government employees will be between $ and…
A teacher wants to form a linear regression equation to predict a student's Score on the final based on the number of hours they spent studying for it. Final scores are in percents. y=2x + 60 R-Squared = 0.65 %3D What does the slope mean in terms of the situation? O For each additional hour a student studies, their grade on the final increases by 2%. O For each additional 2 hours a student student studies, their score on the final increases by 1%. O Every hour a student studies, increases their score on the final. O Always choose C. O The more a student studies, the better they will do on the final.
The managing director of a consulting group has the accompanying monthly data on total overhead costs and professional labor hours to bill to clients. Complete parts a through o. Click the icon to view the monthly data. a. Develop a simple linear regression model between billable hours and overhead costs. Overhead Costs OxBillable Hours (Round the constant to one decimal place as needed. Round the coefficient to four decimal places as needed. Do not include the $ symbol in your answers.) Monthly Overhead Costs and Billable Hours Data Overhead Costs $385,000 Billable Hours 3,000 $425,000 4,000 $445.000 5,000 $497,000 6,000 $570,000 7,000 $590,000 8,000

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