d) Find the regression equation for the data.e) What resale value would you expect for a car aged 5.5 years? Math 1670 - Assignment 6Name:Please write your name on each page of this assignment.1.The table below lists the age of certain used cars (in years) and the associated re-sale value indollars).AgeValueAgeValue$3,448$2,755Ș1,995$1,400$1,268$15,9756.$ 9,28573S 8,0004$ 6,7909.$ 3,15010You may use the following:ΣΧ55 ; ΣΥ-54066; ΣΧΥ- 182668 ; ΣX385.14; ΣΥ488465028a) Draw a scatter diagram. You may use Excel or equivalent.

Given: Age Value 1 15975 2 9285 3 8000 4 6790 5 3150 6 3448 7 2755 8 1995 9…

Answered: d) Find the regression equation for the…

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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The monthly water consumption (thousand liters) and the number of household members in eight private single-family residences is given in the following table: No. of members 12 14 6. 10 8 10 10 Water use (thousand liters) 7 10 5 8 8 10 a. Determine the slope coefficient B1 for the regression of water use given No. of household members. Answer rounded to three decimal places. b. Determine the y-intercept Bo for the regression of water use given No. of household members. Answer rounded to two decimal places. c. Determine the water use for a five-member household. Answer rounded to two decimal places. thousand liters
A regression was run to determine if there is a relationship between hours of TV watched per day (x) and number of situps a person can do (y). The results of the regression were: y=a+bx b=-0.66 a=25.376 r²=0.390625 r=-0.625 Use this to predict the number of situps a person who watches 2.5 hours of TV can do. place. Round to one decimal
Here are two sets of bivariate data with the same response variable. The first contains the variables x & y. The second contains the variables w & y | y w y 25.3 43.9 68.8 36.7 43.8 56.7 57 55 49.2 61.3 27.9 52 57.4 69.3 48 | 50.5 33.7 47.3 58.3 49.2 46.3 56 46.6 34.4 67.1 75.8 35.1 48.3 25.7 43.4 19 76.8 47.2 57.9 7.3 56.8 37.5 57.4 32.9 56.2 44.8 60.4 43.8 49 29.7 38.5 26.4 | 60.9 42.8 53.6 55.6 49.4 60.3 69.7 53.9 55 53.2 67.1 47.8 42.7 57.4 66.3 25 54.8 45.5 57.6 13.9 65 42 51.6 69.5 43.6 38.9 54.8 79.5 29
A regression analysis was performed to determine if there is a relationship between hours of TV watched per day (xx) and number of sit ups a person can do (yy). The results of the regression were: y=ax+b a=-1.172 b=29.62 r2=0.497025 r=-0.705 Use this to predict the number of sit ups a person who watches 4.5 hours of TV can do, and please round your answer to a whole number. ( )
How many independent variables are involved in a multiple regression equation? a. One b. Zero c. Two or more d. At least three
Use the data below for the PHONES questions that follow. Data compiled from the CIA World Factbook, https://www.cia.gov/. The number of cell phones in use in a country can be approximated from the number of main lines in use in that country by using the regression equation yhat=25+3x which had an R² of about 90%. (The numbers here are millions. For example, "1.2" would represent 1.2 million or 1,200,000.) PHONES 1 At the time the data was collected, the USA had about 314 million cell phones in use and about 150 million main lines in use. What was the residual for the USA? Enter a number of millions. For example, if your answer is 2.85 million enter "2.85". Do not enter anything else such as symbols or words.
How does R treat those observations with missing values? In other words, what role do the observations with missing values play in the regression? No command is needed for this question. You must need to provide an answer or take a guess.
C) if a country increases its life expectancy, the happiness index will increase or decrease d) if the life expectancy is increased by 4.5 years in a certain country .how much will the happiness index change? Round two decimal places e) use the regression line to predict that happiness index of a country with a life expectancy of 89 years . Round to two decimal places use the space below to type your answers
Using your dataset, run a regression of Y=GPA and X=# Friends.(do not need your actual data, just the regression results)a) State what this regression is attempting to analyze. “By running this regression, we areattempting to show.....”b) Write out the regression equation and describe what it shows (if Friends increase by 1, then. . . ).c) Find your hypothesized GPA when the # friends equals 17.d) Is the slope of # of Friends significantly different from zero?Include Ho, Ha, decision rule, t statistic from table, tc, decision, and conclusion.e) Is the r-squared of # of Friends significantly different from zero?Include Ho, Ha, decision rule, F statistic from table, Fc, decision, and conclusion.
2. Participants were kept awake for a certain number of hours before given a visuospatial task. Researchers measured how many correct responses each participant had. Results are shown below. Use alpha = .01. Number of Correct Hours Kept Awake (X) Responses (Y) 21 X = 10 SS, = 422 Y = 10 SS, = 690 2 4 19 %3D 6. 13 SPxy =-525 ху 5 20 S, =5.70 S, = 7.29 9. 11 10 9. 14 5 15 5 17 2 18 1 17 1 13 4 18 8 11 A. Graph the data. B. State the hypotheses. C. Make a decision about the null. a. Calculate Pearson's r i. Decision about null hypothesis? b. Calculate effect size i. Interpret effect size. D. State your conclusion. E. Relate your conclusion to the research. F. Calculate the regression formula. G. If someone was kept awake for 9 hours, what is the predicted number of correct responses?
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?
A regression analysis was performed to determine if there is a relationship between hours of TV watched per day (x) and number of sit ups a person can do (y ). The results of the regression were: y=ax+b a=-1.33 b=25.138 r2=0.712336 r=-0.844 Use this to predict the number of sit ups a person who watches 10 hours of TV can do, and please round your answer to a whole number.

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d) Find the regression equation for the data. e) What resale value would you expect for a car aged 5.5 years?