KThe following table below lists the percentage P of the female population who had college degrees in selected years.198019902000201012.618.8 23.633.0P(%)(a) Use linear regression to find a linear function P that models the data.(b) Estimate when this percentage was between 16.1% and 27.3%.(c) Did your estimate involve interpolation or extrapolation?(a) P(x)=(Simplify your answer. Use integers or decimals for any numbers in the expression. Round to the nearest thousandth as needed.)

Answered: Image /qna-images/answer/9cd3ce16-552c-4de9-a134-bfe947b35df7.jpg

Answered: The following table below lists the…

Advanced Engineering Mathematics

10th Edition

ISBN:9780470458365

Author:Erwin Kreyszig

Publisher:Erwin Kreyszig

Chapter2: Second-order Linear Odes

Section: Chapter Questions

Problem 1RQ

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Use the pizza cost and the subway fare in the table below to find the regression equation, letting pizza cost be the predictor (x) variable. (Pizza cost is in dollars per slice, subway fare and CPI are in dollars.) What is the best predicted subway fare when pizza costs $3.98 per slice? Year Pizza Cost Subway Fare CPI 1960 1973 1986 1995 2002 2003 2009 2013 2015 2019 0.152 0.353 1.000 1.251 1.753 2.003 2.254 2.300 2.747 2.997 0.151 0.346 1.000 1.347 1.497 2.004 2.253 2.551 2.747 2.750 29.6 44.4 109.6 152.4 180.0 184.0 214.5 233.0 237.0 252.2 The regression equation is y=+x. (Round the y-intercept to four decimal places as needed. Round the slope to three decimal places as needed.) The best predicted subway fare when pizza costs $3.98 per slice is $ (Round to the nearest cent as needed.)
Would you please assist in answering this question with working out?Thank you. Q. Using a sample of recent university graduates, you estimate a simple linear regression using initial annual salary as the dependent variable and the graduate's weighted average mark (WAM) as the explanatory variable. If the regression model has an estimated intercept of 2200 and an estimated slope coefficient of 550, what is the predicted starting salary of a student with a WAM of 82?
Refer to the data below which contains the percentage change (X) in a stock market index over the first five trading days of the year and percentage change (Y) in the index over the whole year. Complete parts a and b. (X) (Y) 1.4 0.2 14.7 - 9.4 -0.3 2.9 19.6 20.2 a. Estimate the linear regression of Y on X. A y₁ = taxi (Round to four decimal places as needed.) 2.2 - 3.8 - 1.9 27.7 - 1.3 5.7 22.6 2.4 -1.5 1.3 11.8 26 1.5 - 4.4 - 4.4 20.5 0.7 - 1.0
The table shows the percents x and numbers y (in millions) of women in the work force for selected years. T 1970 1975 1980 1985 1990 1995 2000 2005 Percent, x 43.3 46.3 51.5 54.5 57.5 58.9 59.9 59.3 Number, y 31.5 37.5 45.5 51.1 56.8 60.9 66.3 69.3 Year (a) Use the regression capabilities of a graphing utility to find the least squares regression line for the data. (Round your coefficients to two decimal places) YM (b) According to this model, approximately how many women enter the labor force for each one-point increase in the percent of women in the labor force? (Round your answer to two decimal places.) million women
Perform a linear regression analysis on the following data and determine the "a" coefficient (i.e., slope): Y 4.99 22.19 1.96 9.89 2.98 11 9 40.46 4.04 18.93 6.06 25 0.88 0.19 8.02 34.02 6.97 28.03
3. A study of beer consumption using the annual data from 1980 -2001 produced the following regression: Y = 0.41 +0.052.X₁; −0.047X2; +0.032X3; −0.018X4i (0.027) (0.011) (0.009) (0.008) (0.009) R² = 0.94 F = 66.58 DW statistic=1.32, figures in the brackets are standard errors Where: Y₁ = Annual aggregate beer consumption in year t (billion pints) X₁₁ = Real disposable income income in year t ($ billions at 2001 prices) X2i = Price of beer in year t (index number with 2001 = 100) X31 Price of wine and sprits in year t (index number with 2001 = 100) = X4₁ = Price of cigarettes in year t (index number 2001 = 100) (a) What is the effect of a change in the price of beer on beer consumption? Does it have the correct sign? Explain. (b) Comment on the signs of the other three coefficients. Are they as expected? (c) Tests the significance of the coefficients on each of the variables Xit i = 1, 2, 3, 4. What assumptions have you made in carrying out these tests? (d) What conclusion do you draw…
Use the pizza cost and the subway fare in the table below to find the regression equation, letting pizza cost be the predictor (x) variable. (Pizza cost is in dollars per slice, subway fare and CPI are in dollars.) What is the best predicted subway fare when pizza costs $3.91 per slice? Year 1960 1973 1986 1995 2002 2003 2009 2013 2015 2019 Pizza Cost 0.153 0.347 0.998 1.247 1.751 1.996 2.246 2.298 2.751 2.997 Subway Fare 0.149 0.347 1.001 1.347 1.500 1.996 2.252 2.548 2.753 2.748 CPI 29.6 44.4 109.6 152.4 180.0 184.0 214.5 233.0 237.0 252.2 Question content area bottom Part 1 The regression equation is y=enter your response here+enter your response herex. (Round the y-intercept to four decimal places as needed. Round the slope to three decimal places as needed.) Part 2 The best predicted subway fare when pizza costs $3.91per slice is $enter…
In bivariate regression, the value of Y when X equals 0 is: Group of answer choices Intercept (b0) Residual Slope (b1)

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