Find the equation for the line of best fit, by clicking on “calculate least squares regression line.” Include this equation as well as a screenshot of the scatter plot containing the line of best fit.
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- Might we be able to predict life expectancies from birthrates? Below are bivariate data giving birthrate and life expectancy information for each of twelve countries. For each of the countries, both x, the number of births per one thousand people in the population, and y, the female life expectancy (in years), are given. Also shown are the scatter plot for the data and the least-squares regression line. The equation for this line is y = 82.17 -0.47x. Birthrate, x (number of births per 1000 people) 14.3 27.4 51.1 46.8 24.9 29.9 18.2 41.6 49.4 14.1 33.9 49.3 Send data to calculator Female life expectancy, y (in years) 75.6 70.5 58.2 59.0 73.3 62.7 73.6 65.2 62.4 74.3 67.0 53.9 Send data to Excel Female life expectancy (In years) Based on the sample data and the regression line, answer the following. 85+ 80+ 75+ 70+ 65 60 55+ 50 (a) From the regression equation, what is the predicted female life expectancy (in years) when the birthrate is 29.9 births per 1000 people? Round your answer to…Heights (in centimeters) and weights (in kilograms) of 7 supermodels are given below. Find the regression equation, letting the first variable be the independent (x) variable, and predict the weight of a supermodel who is 171 cm tall. \begin{array}{c|ccccccc} \mbox{Height} & 174 & 166 & 176 & 176 & 178 & 172 & 172 \cr \hline \mbox{Weight} & 55 & 47 & 55 & 56 & 58 & 52 & 53 \cr \end{array} The regression equation is \hat{y} = + x . The best predicted weight of a supermodel who is 171 cm tall isFor major league baseball teams, do higher player payrolls mean more gate money? Here are data for each of the American League teams in the year 2002. The variable x denotes the player payroll (in millions of dollars) for the year 2002, and the variable y denotes the mean attendance (in thousands of fans) for the 81 home games that year. The data are plotted in the scatter plot below, as is the least-squares regression line. The equation for this line is y = 11.43 + 0.23x. Player payroll, x (in Mean attendance, y (in $1,000,000s) thousands) Anaheim 62.8 28.52 Baltimore 56.5 33.09 40- Boston 110.2 32.72 35 Chicago White Sox 54.5 20.74 30- Cleveland 74.9 32.35 25- Detroit 54.4 18.52 Kansas City 49.4 16.30 15- Minnesota 41.3 23.70 10+ New York Yankees 133.4 42.84 Oakland 41.9 26.79 20 40 60 80 100 120 140 Seattle 86.1 43.70 Player payroll, Тarmpa Bay 34.7 13.21 X (in $1,000,000s) Техas 106.9 29.01 Toronto 66.8 20.25 Send data to calculator Send data to Excel Based on the sample data and…
- Might we be able to predict life expectancies from birthrates? Below are bivariate data giving birthrate and life expectancy information for each of twelve countries. For each of the countries, both x, the number of births per one thousand people in the population, and y, the female life expectancy (in years), are given. Also shown are the scatter plot for the data and the least-squares regression line. The equation for this line is y= 82.15 – 0.47x. 00 Birthrate, x Female life expectancy, y (in years) (number of births per 1000 people) 40.4 65.2 85- 50.4 59.0 80+ 18.4 71.6 75- 26.5 69.9 70 32.0 64.5 65- 51.7 52.9 60- 34.4 67.2 14.6 75.9 50.1 45.8 59.2 49.9 62.1 Birthrate 73.7 26.2 (number of births per 1000 people) 73.7 14.4 Save For Later Submit Assignment Check 2 Accessibility O 2022 McGraw Hill LLC AN Rights Reserved. Terms of Use / Privacy Center DO 80 DIl 110 17 Da SO FA F4 esc F2 & delete %24 % 8 %23 6 7 3 4 7. U T K LA G S D Female life expectancy (in years)RequiredPage 92 The company uses the number of professional hours as the cost driver for office support costs. Use an algebraic equation to describe how total office support costs can be estimated. Use a spreadsheet program to perform a regression analysis. Use office support costs as the dependent variable (Y) and the professional hours as the independent variable (X). Determine the total fixed cost per office and variable cost per professional hour. Identify the R2 statistic provided by the Excel program and explain what it means. Mr. Dean plans to open a new branch office in a Dallas suburb. He expects that the monthly professional hours will be 3,000. Estimate the total office support cost for Mr. Dean. What portion of the total cost is fixed and what portion is variable? Explain how multiple regression analysis could be used to improve the accuracy of the cost estimates. *You will use excel to setup a worksheet with your data and run regression analysis.*Please help me better understand how to solve this word problem. In a study of 2000 model cars, a researcher computed the least-squares regression line of price (in collars) on horsepower. He obtained the following equation of: Price = -7000 + 170 X horsepower. Based on the least-squares regression line, what would we predict the cost of a 2000 model car with horsepower equal to 230 to be (assuming no extrapolation error)?
- Biologist Theodore Garland, Jr. studied the relationship between running speeds and morphology of 49 species of cursorial mammals (mammals adapted to or specialized for running). One of the relationships he investigated was maximal sprint speed in kilometers per hour and the ratio of metatarsal-to-femur length. A least-squares regression on the data he collected produces the equation ŷ = 37.67 + 33.18x %3D where x is metatarsal-to-femur ratio and ŷ is predicted maximal sprint speed in kilometers per hour. The standard error of the intercept is 5.69 and the standard error of the slope is 7.94. Construct an 80% confidence interval for the slope of the population regression line. Give your answers precise to at least two decimal places. Lower limit: Upper limit:If you have 2 datasets on which you have conducted a regression analysis, how would you determine whether you can combine them into one dataset?Using the guide of the textbook and your RQ, determine the equation of the least-square line for the following data: 1 6 3. Select the correct answer in the slope-intercept form. O y=-x+10.5 O y=-2x+11 O y=x O y=x+10 O x+y=11
- Students who are going to college have a cost per credit. The chart below is a cost of tuition cost increase over the years. A table of the yearly cost is listed below. A) Use technology (graphing calculator or excel) to determine the least squares regression line for the best fit line for the data given above. List the equation and R^2 Regression factor. B) Use your equation from technology to estimate how much college credits will cost in 2021The following regression equation is based on the analysis of four variables: SM_DOLLARS is the dollar amount of a watershed conservation agency's weekly spending on social media ads. RADIO_ADS is the number of radio advertisements aired weekly by the agency. WS_DOLLARS is the dollar amount of the agency’s weekly spending on web search ads. The variable WEB_VISITS is the number of weekly visitors to their educational website. These data have been recorded every week for the past three years. WEB_VISITS (expected) = 208 + 1.25*SM_DOLLARS + 1.5*RADIO_ADS + 1.2*WS_DOLLARS The data meet the assumptions for regression analysis, and the regression results, including the coefficients, were found to be statistically significant. Initially, $320 was spent on social media ads, 10 radio ads were aired, and $120 spent on web search ads. How many additional weekly web visits would you predict when the agency increases its weekly spending on social media ads by $440 without changing the…