The table shows the percents x and numbers y (in millions) of women in the work force for selected years. T1970 1975 1980 1985 1990 1995 2000 2005Percent, x 43.3 46.3 51.5 54.5 57.5 58.9 59.9 59.3Number, y 31.5 37.5 45.5 51.1 56.8 60.9 66.3 69.3Year(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? (Roundyour answer to two decimal places.)million women

Here the dependent variable (y) is number and the independent variable (x) is percent.No. of years

Answered: (a) Use the regression capabilities 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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Report the equation of the regression line and interpret it in the context of the problem
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C) if a country increases its life expectancy, the happiness index will increase or decrease d) if the life expectancy is increased by 4.5 years in a certain country .how much will the happiness index change? Round two decimal places e) use the regression line to predict that happiness index of a country with a life expectancy of 89 years . Round to two decimal places use the space below to type your answers
The table below shows the number, in thousands, of vehicles parked in the central business district of a certain city on a typical Friday as a function of the hour of the day. Hour of the day Vehicles parked(thousands) 9 A.M. 6.2 11 A.M. 7.6 1 P.M. 7.6 3 P.M. 6.7 5 P.M. 4 (a) Use regression to find a quadratic model for the data. (Let V be the number of vehicles and t be the time in hours since midnight. Round the regression parameters to three decimal places.) V= (b) Express using functional notation the number of vehicles parked on a typical Friday at 2 P.M., and then estimate that value. (Round your answer to two decimal places.) V_____= _____ thousand
How much of the variation in average annual energy expenditures is explained by the least-squares regression line? Round the answer to at least one decimal place.
The cost of a flight is related to the distance traveled: Miles Cost ($) 225 38.5 525 76.1 1,100 119 1,375 142 1,950 200 2,250 244 a)Graph the scatter plot on your calculator. Is the data linear, quadratic, or exponential? b) Use the appropriate regression to find the equation of best fit. c) Use your model to predict the cost of a flight that travels 800 miles? Is this interpolation or extrapolation? d) Use your model to predict the cost of a flight that travels 3000 miles. Is this interpolation or extrapolation?
How is the Polynomial Regression model different from the Simple Linear Regression and Multiple Linear Regression models? Select an answer: a. The independent variables are categorical instead of numerical. b. There are multiple dependent variables instead of just one. c. The independent variable is raised to a higher power (squared, cubed, etc.). d. The dependent variable is raised to a higher power (squared, cubed, etc.).
Regression was used to determine if the number of beers a person drinks predicts blood alcohol content (BAC) in a random sample of college students. The results are in the table below. Intercept Beers Coefficients Standard Error 0.013 0.002 -0.013 0.018 t Stat P-value -1.005 0.332 7.480 2.97E-06 Write out the answers to each of the following questions and upload a picture of yo a. Write out the prediction equation. b. Interpret the slope. c. What is the predicted value for BAC for someone who drank 3 beers? Show your work. d. If the number of beers equals 5 and the BAC equals 0.10, what is the residual? Show your work.
Interpreting technology: A biologist computed a least-squares regression line for predicting the brain weight in grams of a bird from its body weight in grams. The results are presented in the following Excel output. Coefficients Intercept 3.68952298 Body Weight 0.07800925 Part: 0 / 2 Part 1 of 2 Write the equation of the least-squares regression line. Use the full accuracy shown in the Excel output (do not round your answers). Regression line equation: y = X
st e this 1:33 38% K A pediatrician wants to determine the relation that exists between a child's height, x, and head circumference, y. She randomly selects 11 children from her practice, measures their heights and head circumferences, and obtains the accompanying data. Complete parts (a) through (g) below. Click the icon to view the children's data. (a) Find the least-squares regression line treating height as the explanatory variable and head circumference as the response variable. Data Table y = X + (Round the slope to three decimal places and round the constant to one decimal place as needed.) View an example Height (inches), X Head Circumference (inches), y D 27.75 17.8 24.75 17.3 25.75 17.4 26.25 17.7 25 17.1 28.25 17.9 26.75 17.5 27 17.7 26 26 27.5 ||| = Print Get more help. (...) 17.5 17.7 17.8 1 LTE2 + ... Done O X Clear all Check answer
Enterprise Industries produces Fresh, a brand of liquid laundry detergent. In order to study the relationship between price and demand for the large bottle of Fresh, the company has gathered data concerning demand for Fresh over the last 30 sales periods (each sales period is four weeks). Here, for each sales period, Run the regression Model in Excel. Copy and paste entire output below. Find the least squares point estimates b0 and b1 on the computer output and report their values. Interpret b0 and b1. Write down the regression equation At x=0.3, what is the residual? Find correlation coefficient. Negative or positive association? Find R2. Interpret the result.

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