Calculate the coefficient of correlation betweenage 'of cars and annual maintenance cost and comment :Age of cars(years) (X)Annual maintenancecost ('00) (Y):24781012:16151819172120

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Answered: Calculate the coefficient of…

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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Data Management - Statistical Anaylsis Per the following graph, explain the reason for every statistic that is calculated. For example, You have a scatter plot of an hourly wages vs level of education, the trend is represented by a cubic curve with R^2=0.999. It can mean that the relationship of the level of education vs the hourly wages has a cubic trend as the cubic model suits well the set of data (R^2 is very close to 1).
The variable income (yearly) is examined in a regression setting where the predictor variable is the lag (1) of income and the following output is produced. a) Write down the regression equation. b) Interpret the meaning of the slope. c) A dummy variable for gender (male=0, female=1) was added to the model. Interpret its coefficient of -0.2. Us_change %>% model(TSLM(log(Income) ~ log(LagIncome))) %>% report() #> Series: Consumption #> Model: TSLM #> #> Residuals: #> Min 1Q Median 3Q Max #> -2.5824 -0.2778 0.0186 0.3233 1.4223 #> #> Coefficients: #> Estimate Std. Error t value Pr(>|t|) #> (Intercept) 0.5445 0.0540 10.08 < 2e-16 *** #> Log(LagIncome) 1.1000 0.0467 5.82 2.4e-08 *** #> --- #> Signif.codes: 0 '***'0.001'**'0.01'*' 0.05'.' 0.1 ' ' 1 #> #> Residual standard error: 0.591 on 196 degrees of freedom #>…
Data Management - Statistical Anaylsis Per the following graph, explain the reason for every statistic that is calculated. For example, You have a scatter plot of an hourly wages vs level of education, the trend is represented by a cubic curve with R^2=0.999. It can mean that the relationship of the level of education vs the hourly wages has a cubic trend as the cubic model suits well the set of data (R^2 is very close to 1).
9. Microprocessing, a computer firm specializing in software engineering, has compiled the following revenue records for the years 1989 to 1995. 89 | 90 92 93 94 95 Years 91 Revenue($100,000) The second degree equation that best describes the secular trend for these data is Y^ = 2.119+0.375x + 0.020 x², where 1992 = 0 and x units = 1 year a. Calculate the percent of trend for these data b. Calculate the relative cyclical residual for these data c. Plot the percent of trend from part a d. In which year does the largest fluctuation from trend occur, and is it the same for both the methods?
4. What do you know about explained and unexplained variation? What is regression line and regression equation?
Data Management - Statistical Anaylsis Per the following graph, explain the reason for every statistic that is calculated. For example, You have a scatter plot of an hourly wages vs level of education, the trend is represented by a cubic curve with R^2=0.999. It can mean that the relationship of the level of education vs the hourly wages has a cubic trend as the cubic model suits well the set of data (R^2 is very close to 1).
For Equation 1, what score on self-reported health would you predict for a non-white, unmarried male who is 24 years old and has 12 years of education?
A regression was run to determine if there is a relationship between the happiness index (y) and life expectancy in years of a given country (x).The results of the regression were: ˆyy^=a+bxa=-1.778b=0.143 (d) If the life expectancy is increased by 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 94 years. Round to two decimal places.

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Calculate the coefficient of correlation between age 'of cars and annual maintenance cost and comment : Age of cars (years) (X) Annual maintenance cost ('00) (Y) 4 7 8 10 12 : 16 15 18 19 17 21 20