Drag each graph given below to its corresponding regression equation to the right.13. y = - 1.361x+21.952Ay140-30-120-25100-20-80-60-15-40-10-20-5-102030 40 501014. y = 2.115x + 21.958AyAy30-70-25-60-50-20-4015-3010-20-5-10-15. y = 2.125x +9.588s 10 15 20 2s 30 35 405 10 15 20 25 3016. y = -0.705x +27.214

Given that All the lines re of the form y=mx+c, where m is the slope of the regression line and c…

Answered: Drag each graph given below to its…

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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There is a linear relationship between the number of chirps made by the stiped ground cricket and the air temperature. It was determined that the linear regression model is: y = 25.2 + 3.3x where x is the number of chirps per minute and y is the estimated temperature in degrees Fahrenheit. What is the predicted number of chirps made when the temperature is 60 degrees Fahrenheit? Round to the nearest integer. Do not include units.
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
Bankers at a large financial institution created the linear regression model d = 0.37 – 0.0004s to predict the proportion of customers who would default on their loans, d, based on the customer's credit score, s. For a customer with a credit score of 700, which of the following is true? A The default proportion is predicted to be 0.09. В The default proportion will be 0.09. The default proportion is predicted to be approximately 1.75 million. The default proportion will be approximately 1.75 million. E The default proportion is predicted to be 0.28.
Suppose you wanted to test whether or not the payoff to an additional year of education was the same for men and women in the STEM majors. How would you set up your regression analysis in this case
Explain how to find se
M3
9 students were surveyed to see what their age is and what their income level is. Find the equation of the line using linear regression. We want to predict their age using their income. age 18 24 38 22 19 35 28 19 27 income 456 786 835 855 645 244 587 1400 975 Just a side note, the 19 year old is making 1400, would be considered an outlier since they are making way more than everyone else. (y=-.0061x+34.9874 4 decimals) y=30.3709-.0064
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…
Match the regression equation with the appropriate graph. Drag each graph given below to its corresponding regression equation to the right. 13. y = - 1.361x+ 21.952 Ny Ay 140- 30- 120- 25- 100- 20- 80- 15- 60- 40- 10- 20- 5- 14. y = 2.115x+21.958 10 20 30 40 50 2 4 8. 10 Ay Ay 30- 70- 60- 25- 50- 20- 40- 15- 30- 10- 20- 5- 10- 15. y = 2.125x + 9.588 5 10 15 20 25 30 35 40 5 10 15 20 25 30 16. y = - 0.705x + 27.214
A linear regression analysis reveals a strong, negative linear relationship between x and y. Which of the following could possibly be the results from this analysis? (A) ŷ 13.1 27.4x, r = 0.85 (B) == 27.4+ 13.1x, r = -0.95 (D) == (C) ŷ 13.1+ 27.4x, r = 0.95 542 385x, r = -0.15 (E) 0.85 0.25x, r = -0.85

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