in the residuals when plotted against x? Year x (year minus 1975) | y (percent assets) 1975 30.2 1976 1 28.4 1977 28.3 1978 26.7 1979 1980 26.8 25.3 1981 6 23.4 1982 7 22.6 1983 22.3 1984 22.2 1985 1986 10 21.4 11 21.5 1987 12 22.5
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- Life Expectancy The following table shows the average life expectancy, in years, of a child born in the given year42 Life expectancy 2005 77.6 2007 78.1 2009 78.5 2011 78.7 2013 78.8 a. Find the equation of the regression line, and explain the meaning of its slope. b. Plot the data points and the regression line. c. Explain in practical terms the meaning of the slope of the regression line. d. Based on the trend of the regression line, what do you predict as the life expectancy of a child born in 2019? e. Based on the trend of the regression line, what do you predict as the life expectancy of a child born in 1580?23003.3 An electronics company is looking to develop a regression model to predict the number of units sold for a special running watch. Data is provided below Sales (units) Price ($) Advertising ($) Holiday 500 100 50 Yes 480 120 40 Yes 485 110 45 No 510 103 55 Yes 490 108 40 No 488 109 30 No 496 106 45 Yes (a) Determine the relationship between price and sales i.e. what is the effect of a unit change in price on sales and is it statistically significant? (b) Determine the relationship between advertising and sales i.e. what is the effect of a unit change in advertising on sales and is it statistically significant? (c) Determine the relationship between Holiday and sales i.e. what is the difference in sales between a holiday and a non-holiday and is it statistically significant? (c) Determine the relationship between Holiday and sales i.e. what is the difference in sales between a holiday and a non-holiday and is it statistically significantAccording to "Reproductive Biology of the Aquatic Salamander Amphiuma tridactylum in Louisiana,"† the size of a female salamander's snout is correlated with the number of eggs in her clutch. The following data are consistent with summary quantities reported in the article. Partial Minitab output is also included. Snout-Vent Length Clutch Size 32 45 53 215 53 160 53 170 54 190 57 200 57 270 58 175 58 245 59 215 63 170 63 240 64 245 67 280 The regression equation is Y = -133 + 5.92x Predictor Coef Stdev T P Constant -133.02 64.30 2.07 0.0608 x 5.919 1.127 5.25 0.0002 s = 33.90 R-sq = 69.7% R-sq(adj) = 67.2% Additional summary statistics are given below. n = 14 x = 56.5 y = 201.4 Σx2 = 45,597 Σy2 = 613,550 Σxy = 164,690 You can use the Distribution Calculators page in SALT to find critical values and/or p-values to answer parts of this question. (a) What is the equation of the regression line…
- Bus and subway ridership in Washington D. C. during the summer months is believed to be heavily tied to thenumber of tourists visiting the city. During the past 12 years, the following data have been obtained: Number of Tourists (in millions) 7 2 6 4 14 15 16 12 14 20 15 7 Ridership ( in 100,000) 15 10 13 15 25 27 24 20 27 44 34 17 a) Develop a linear regression model that would predict bus and subway ridership based on the number of tourists.b) Based on your model, predict the bus and subway ridership if there are eight million tourists in the city.c) Find the coefficient of determination and correlation coefficient between the two variables.Develop an estimated multiple linear regression model that could be used to predict the alumni giving rate using the graduation, % of Classes Under 20, and Student/Faculty Ratio as independent variables. Discuss your findings. School SFR LT20 GT50 GRAD FRR GIVE Arizona State 24 42% 16% 59% 81% 8% Arkansas State—Jonesboro 19 49% 4% 37% 69% 11% Auburn 18 24% 17% 66% 87% 31% Air Force 8 74% 0.10% 81% 88% 11% Military Academy 8 95% 0% 86% 92% 28% Akron 20 39% 6% 35% 69% 15% Arizona 20 35% 17% 60% 79% 5% Arkansas 18 28% 18% 58% 83% 23% Ball State 18 34% 12% 57% 78% 11% Baylor 14 49% 9% 71% 85% 14% Boise State 21 33% 11% 27% 67% 8% Boston College 14 47% 6% 91% 96% 27% Bowling Green State 19 33% 7% 61% 75% 8% BYU 21 46% 12% 78% 84% 17% SUNY 16 36% 21% 67% 88% 9% Alabama 19 46% 16% 67% 85% 34% Central Michigan 22 32% 11% 54% 78% 8% Clemson 16 51% 13% 76% 91% 28% Colorado State 18 34% 19% 64% 83% 7% Berkley 17 62% 15% 91% 97% 12% Cincinnati…Managing Ashland MultiComm Services In its continuing study of the 3-For-All subscription solicitation process, a marketing department team wants to test the effects of two types of structured sales presentations (personal formal and personal informal) and the number of hours spent on telemarketing on the number of new subscriptions. The staff has recorded these data for the past 24 weeks AMS14. Analyze these data and develop a multiple regression model to predict the number of new subscriptions for a week, based on the number of hours spent on telemarketing and the sales presentation type. Write a report, giving detailed findings concerning the regression model used.
- Cafe michigans manager, gary starkm suspects that demand for mocha latte coffees depends on the price being charged. Based on historical observations, Gary has gathered the following data, which show the number of thesse coffees sold over six different price values: Price number sold $2.70 760 $3.50 510 $2.00 980 $4.20 250 $3.10 320 $4.05 480 Using simple linear regression and given that the price per cup is $2.80 the forecasted demand for mocha latte coffees will be [__] cups (enter your response rounded to one decimal place)The Tile Shop owner wants to find out how education of his new hires interacts with sales. He is thinking of hiring less educated employees where he can save money on payroll but still expects high sale levels. Develop a Linear Regression Model and forecast sales for 8, 14, 17 years of education. Sales (1000s) Education Years 24 10 18 9 20 11 22 6 26 13 23 16 21 18Weight (lbs.) 173 184 194 214 168 220 188 188 207 167 217 Systolic Blood Pressure 132 143 153 162 154 168 137 149 159 128 166 1. What is the response variable? 2. What is the explanatory variable? 3. What is the equation of the linear regression line? 4. If person's weight is 150, what can we expect the systolic blood pressure to be?
- What do you think would be your reservations in relaying on the linear regression model for budgetary planning purposes?Cinema HD an online movie streaming service that offers a wide variety of award-winning TV shows, movies, animes, and documentaries, would like to determine the mathematical trend of memberships in order to project future needs. Year 2013 2014 2015 2016 2017 2018 2019 2020 2021 Membership 17 16 16 21 20 20 23 25 24 Use the following time series data, to develop a regression equation relating memberships to time. Forecast 2023 membership Assuming the COVID-19 pandemic comes to an end in 2021, in your opinion, how will this affect membership? Why? How will this affect your prediction? What are the issues associated with qualitative forecasting, and how are these overcome? Provide an example of qualitative forecasting and explain the shortcomings.Movieflix, an online movie streaming service that offers a wide variety of award-winning TV shows, movies, animes, and documentaries, would like to determine the mathematical trend of memberships in order to project future needs.Year 2013 2014 2015 2016 2017 2018 2019 2020 2021Membership (000s)17 16 16 21 20 20 23 25 24 (i) Use the following time series data, to develop a regression equation relating memberships to time.