A social scientist would like to analyze the relationship between educational attainment (inyears of higher education) and annual salary (in $1,000s). He collects data on 20individuals. A portion of the data is as follows:Salary4449Education34Click here for the Excel Data Filea. Find the sample regression equation for the model:Salary = Bo + B1Education + ɛ. (Round answers to 2 decimal places.)Salary =Educationb. Interpret the coefficient for Education.O As Education increases by 1 unit, an individual's annual salary is predicted todecrease by $6,430.O As Education increases by 1 unit, an individual's annual salary is predicted todecrease by $8,590.O As Education increases by 1 unit, an individual's annual salary is predicted toincrease by $6,430.O As Education increases by 1 unit, an individual's annual salary is predicted toincrease by $8,590.c. What is the predictedSalary for an individual who completed 9 years of higher education? (Round coefficientestimates to at least 4 decimal places and final answer to the nearest whole number.)Salary SalaryEducation44349844437256311143374588944676141458.47837313034

Use EXCEL to obtain the regression equation. EXCEL procedure: Go to EXCEL Go to Data>Data…

Answered: A social scientist would like to…

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 table below gives the age and bone density for five randomly selected women. Using this data, consider the equation of the regression line, y = bo + bjx, for predicting a woman's bone density based on her age. Keep in mind, the correlation coefficient may or may not be statistically significant for the data given. Remember in practice, it would not be appropriate to use the regression line to make a prediction if the correlation coefficient is not statistically significant. Age 35 50 54 61 66 Bone Density 354 353 350 334 332 Tab Copy Data Step 6 of 6: Find the value of the coefficient of determination. Round your answer to three decimal places. 田 Tables 國 Key Answer Keyboard Sho How to enter your answer (opens in new window) Previous step ar Submit An © 2022 Hawkes Learning tv APR 24 MacBook Pro
The datasetBody.xlsgives the percent of weight made up of body fat for 100 men as well as other variables such as Age, Weight (lb), Height (in), and circumference (cm) measurements for the Neck, Chest, Abdomen, Ankle, Biceps, and Wrist. We are interested in predicting body fat based on abdomen circumference. Find the equation of the regression line relating to body fat and abdomen circumference. Make a scatter-plot with a regression line. What body fat percent does the line predict for a person with an abdomen circumference of 110 cm? One of the men in the study had an abdomen circumference of 92.4 cm and a body fat of 22.5 percent. Find the residual that corresponds to this observation. Bodyfat Abdomen 32.3 115.6 22.5 92.4 22 86 12.3 85.2 20.5 95.6 22.6 100 28.7 103.1 21.3 89.6 29.9 110.3 21.3 100.5 29.9 100.5 20.4 98.9 16.9 90.3 14.7 83.3 10.8 73.7 26.7 94.9 11.3 86.7 18.1 87.5 8.8 82.8 11.8 83.3 11 83.6 14.9 87 31.9 108.5 17.3…
KidsFeet Regression Line y-Intercept The KidsFeet dataframe contains data collected on 39 fourth grade students in Ann Arbor, MI, in October 1997. Two of the measurements taken on the children were the length in centimeters, (length), and width in centimeters, (width), of their longest foot. This data could be used to answer the following Research Question: How is the width of a fourth-grade student's foot related to the length? Which of the following is the y-intercept of the regression line? ## ## Simple Linear Regression## ## Correlation coefficient r = 0.6411 ## ## Equation of Regression Line:## ## length = 9.817 + 1.658 * width ## ## Residual Standard Error: s = 1.025 ## R^2 (unadjusted): R^2 = 0.411 ( ) 1.0248 ( ) 1.6576 ( ) 22.8153 ( ) 0.411 ( ) 9.8172 ( )0.6411
Body Fat. Where we considered the regression of percentage of body fat on nine body measurements: height, weight, hip, forearm, neck, wrist, triceps, scapula, and sup. Describe and discuss problems that could have arisen in the collection of the data for this regression analysis.
For a two-variable linear regression, if the sample correlation between the depen- dent and independent variables is –0.7, then the independent variable explains 49% of the variation in the dependent variable. Is this statement true? Explain your answer.
State the regression equation and use it to predict taxes for a house with lot size 10K.
Hiroshi Sato, an owner of a sushi restaurant in San Francisco, has been following an aggressive marketing campaign to thwart the effect of rising unemployment rates on business. He used monthly data on sales ($1,000s), advertising costs ($), and the unemployment rate (%) fromJanuary 2008 to May 2009 to estimate the following sample regression equation: Sales(t) = 17.51 +0.05 Advertising Costs(t-1) – 0.70 Unemployment Rate t-1 Requirement: a. Hiroshi had budgeted $620 toward advertising costs in May 2009. Make a forecast in June2009, if the unemployment rate in May 2009 was 9.1%b. What will be the forecast if he raises his advertisement budget to $700?c. Reevaluate the above forecast if the unemployment rate in May 2009 was 9.5%. Please, if possible, can you do the answer in Excel/Spreadsheet
The number of Master’s degrees granted at a particular university is given for selected years in the table below. Year 2005 2010 2015 2020 Number of Master’s Degrees 58 69 76 83 Use the linear regression equation for this data to predict the number of Master’s degrees that this university will grant in the year 2021. Blank 1. Calculate the answer by read surrounding text. Round to the nearest whole number of Master's degrees.
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Mary used a sample of 68 large U.S. cities to estimate the relationship between Crime (annual property crimes per 100,000 persons) and Income (median annual income per capita, in dollars). Her estimated regression equation was Crime = 428 + 0.050 Income. If Income decreases by 500, we would expect that Crime will Group of answer choices remain unchanged. decrease by 25. increase by 500. decrease by 50.
Suppose that you are interested in the relationship between Reading and Writing scores. (c) Compute and interpret the R2 value for the relationship between Reading and Writing scores. (d) Interpret the value of the slope in the regression model predicting Reading scores from Writing scores. RDG WRTG 34 44 47 36 42 59 39 41 36 49 50 46 63 65 44 52 47 41 44 50 50 62 44 41 47 40 42 59 42 41 47 41 60 65 39 49 57 54 73 65 47 46 39 44 35 39 39 41 48 49 31 41 52 63 47 54 36 44 47 44 34 46 52 57 42 40 37 44 44 33 71 58 47 46 42 33 42 36 47 41 52 54 52 54 39 39 31 41 60 54 47 31 39 28 42 36 47 57 42 49 36 41 50 33 34 34 55 55 28 46 42 42 44 44 60 52 39 57 36 37 44 44 39 42 39 34 42 39 42 44 52 54 65 65 42 26 47 62 52 62 44 54 52 54 47 44 65 57 63 65 60 59 47 44 65 57 53 61 68 63 55 56 39 53 52 52 65 67 52 44 57 67 63…
The arm span and foot length were both measured (in centimeters) for each of 20 students in a biology class. The computer output displays the regression analysis. Which of the following is the best interpretation of the coefficient of determination r2? About 37% of the variation in arm span is accounted for by the linear relationship formed with the foot length. About 65% of the variation in foot length is accounted for by the linear relationship formed with the arm span. About 63% of the variation in arm span is accounted for by the linear relationship formed with the foot length. About 63% of the variation in foot length is accounted for by the linear relationship formed with the arm span.

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