Consider the following regression estimates (FN4) Linear regression Number of obs 29,471 318.65 F(1, 29469) Prob > F 0.0000 R-squared 0.0108 Root MSE = 801.34 Robust income Coef. Std. Err. t P>|t| [95% Conf. Interval] female -167.6086 -186.0124 -149.2047 9.389494 -17.85 0.000 60.38 0.000 _cons 946.3256 15.67369 915.6045 977.0468 where income is weekly income in NZ$, female is equal to 1 if the person if female and 0 if the person is male. What is the average income of all males in this regression? Please only state the number. Do not use the $ sign in your answer. || || || || || = =

Consider the following regression estimates (FN4) Linear regression Number of obs 29,471 318.65 F(1, 29469) Prob > F 0.0000 R-squared 0.0108 Root MSE = 801.34 Robust income Coef. Std. Err. t P>|t| [95% Conf. Interval] female -167.6086 -186.0124 -149.2047 9.389494 -17.85 0.000 60.38 0.000 _cons 946.3256 15.67369 915.6045 977.0468 where income is weekly income in NZ$, female is equal to 1 if the person if female and 0 if the person is male. What is the average income of all males in this regression? Please only state the number. Do not use the $ sign in your answer. || || || || || = =

Functions and Change: A Modeling Approach to College Algebra (MindTap Course List)

6th Edition

ISBN:9781337111348

Author:Bruce Crauder, Benny Evans, Alan Noell

Publisher:Bruce Crauder, Benny Evans, Alan Noell

Chapter3: Straight Lines And Linear Functions

Section3.CR: Chapter Review Exercises

Problem 16CR: XYZ Corporation Stock Prices The following table shows the average stock price, in dollars, of XYZ...

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Respiratory Rate Researchers have found that the 95 th percentile the value at which 95% of the data are at or below for respiratory rates in breath per minute during the first 3 years of infancy are given by y=101.82411-0.0125995x+0.00013401x2 for awake infants and y=101.72858-0.0139928x+0.00017646x2 for sleeping infants, where x is the age in months. Source: Pediatrics. a. What is the domain for each function? b. For each respiratory rate, is the rate decreasing or increasing over the first 3 years of life? Hint: Is the graph of the quadratic in the exponent opening upward or downward? Where is the vertex? c. Verify your answer to part b using a graphing calculator. d. For a 1- year-old infant in the 95 th percentile, how much higher is the walking respiratory rate then the sleeping respiratory rate? e. f.
XYZ Corporation Stock Prices The following table shows the average stock price, in dollars, of XYZ Corporation in the given month. Month Stock price January 2011 43.71 February 2011 44.22 March 2011 44.44 April 2011 45.17 May 2011 45.97 a. Find the equation of the regression line. Round the regression coefficients to three decimal places. 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 the stock price to be in January 2012? January 2013?
For the following exercises, use Table 4 which shows the percent of unemployed persons 25 years or older who are college graduates in a particular city, by year. Based on the set of data given in Table 5, calculate the regression line using a calculator or other technology tool, and determine the correlation coefficient. Round to three decimal places of accuracy
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A regression was run to determine if there is a relationship between the happiness inde expectancy in years of a given country (x). The results of the regression were: ŷ=a+bx a=-1.042 b=0.186
A statistics student wanted to determine if the distance to a destination was related to the price an airline would charge to fly to that destination. The student did a regression of airfare, y, on distance, x, and obtained the printout shown below from a statistical software package. Predictor Coef Constant 83.02 Distance 0.117 Oŷ= 0.117+83.02x Oy=83.02 +0.117x Oy= 49.29 + 83.02x Oŷ= 0.028 + 0.117x Oy=83.02 + 25.25x 1 SE Coef 49.29 0.028 S = 25.25 R-Sq = 63.2 % Which of the following is the correct equation of the least-squares line? Mark this and return t-ratio 1.689 4.179 R-Sq (Adj) = 64.7% Save and Exit р 0.046 0.000 di I tv Next AM Submit Aa
mean of x = 2.882, standard deviation = 1.634 Mean of y = 2.588, standard deviation = 0.246 The correlation coefficient is 0.159 slope coefficient for regression line = .0239 y intercept = 2.52 write the regression model
Having the variation data regression line r=0.931 and the coefficient of determination is 0.867.. And the variation of 91.6% is explained by the regression line.. About the unexplained variation? [ ]% of the variation is unexplained and is due to other factors or to sampling error. (Round to one decimal place as needed.)
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The regression equation for predicting a woman's muscle mass (a quantitative metric, Y) from age (in years, X) is given as ý = 156.35 - 1.19. The ANOVA table for the linear regression of Y vs X is given below. Source Df SS MS p-value Age 11627.5 11627,5 174.06 <,0001 Error 58 3874.4 66.8 Total 59 15501.9 Fill in the blanks below that demonstrate how to construct an interval estimate for the muscle mass of an individual 60-year-old woman. Use a confidence level of 95%; note that the multiplier is t = 2.002 and the standard error of the mean response is s(i,) = 1.055. 95% Interval: ( Select) + ( Select ) [ Select]
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