Intro STATS, Books a la Carte Plus New Mystatlab with Pearson Etext -- Access Card Package
4th Edition
ISBN: 9780321869852
Author: Richard D. De Veaux
Publisher: PEARSON
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Chapter 23.4, Problem 2JC
To determine
Check whether the measuring a person’s height could be used as a substitute for the wetter method of determining how big a person’s mouth and find the numbers in the output helped to reach the conclusion.
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Please do b, c, and d
The average height of people in Faroe island is 180cm. Suppose you run a regression with no independent variables. What would be the estimated form of your regression?
Researchers are interested in predicting the height of a child based on the heights of their mother
and father. Data were collected, which included height of the child (height ), height of the mother (
mothersheight), and height of the father (fathersheight ). The initial analysis used the heights of the
parents to predict the height of the child (all units are inches). The results of the analysis, a multiple
regression, are presented below.
.
regress height mothersheight fathersheight
Source
Model
Residual
Total
height
mothersheight
fathersheight
_cons
SS
df
208.008457
314.295372 37
2 104.004228
8.49446952
MS
522.303829 39 13.3924059
Coef. Std. Err.
.6579529 .1474763
.2003584 .1382237
9.804327 12.39987
t P>|t|
4.46 0.000
C 0.156
0.79 0.434
Number of obs =
F( 2, 37) =
Prob > F
R-squared
Adj R-squared
Root MSE
=
.3591375
-.0797093
-15.32021
=
40
12.24
0.0001
0.3983
0.3657
2.9145
[95% Conf. Interval]
.9567683
.4804261
34.92886
What is the predicted height for a child born to a mother…
Chapter 23 Solutions
Intro STATS, Books a la Carte Plus New Mystatlab with Pearson Etext -- Access Card Package
Ch. 23.4 - Researchers in Food Science studied how big...Ch. 23.4 - Prob. 2JCCh. 23.4 - Prob. 3JCCh. 23 - Prob. 1ECh. 23 - Prob. 2ECh. 23 - Prob. 3ECh. 23 - Prob. 4ECh. 23 - Prob. 5ECh. 23 - Prob. 6ECh. 23 - Prob. 7E
Ch. 23 - Prob. 8ECh. 23 - Prob. 9ECh. 23 - Prob. 10ECh. 23 - Prob. 11ECh. 23 - 12. Shoot to score, double overtime One of the...Ch. 23 - Prob. 13ECh. 23 - Prob. 14ECh. 23 - Prob. 15ECh. 23 - Prob. 16ECh. 23 - Prob. 17ECh. 23 - Prob. 18ECh. 23 - Prob. 19ECh. 23 - Prob. 20ECh. 23 - Prob. 21ECh. 23 - Prob. 22ECh. 23 - Prob. 23ECh. 23 - Prob. 24ECh. 23 - Prob. 25ECh. 23 - Prob. 26ECh. 23 - Prob. 27ECh. 23 - Prob. 28ECh. 23 - Prob. 29ECh. 23 - Prob. 30ECh. 23 - Prob. 31ECh. 23 - Prob. 32ECh. 23 - Prob. 33ECh. 23 - Prob. 34ECh. 23 - Fuel economy A consumer organization has reported...Ch. 23 - 36. SAT scores How strong was the association...Ch. 23 - Prob. 37ECh. 23 - 38. SATs, part II Consider the high school SAT...Ch. 23 - 39. Fuel economy, part III Consider again the data...Ch. 23 - 40. SATs, again Consider the high school SAT...Ch. 23 - Cereals A healthy cereal should be low in both...Ch. 23 - Brain size Does your IQ depend on the size of your...Ch. 23 - Prob. 43ECh. 23 - Prob. 44ECh. 23 - Prob. 45ECh. 23 - Prob. 46ECh. 23 - Ozone and population The Environmental Protection...Ch. 23 - Prob. 48ECh. 23 - Prob. 49ECh. 23 - 50. More sales and profits Consider again the...Ch. 23 - Prob. 51ECh. 23 - Crawling Researchers at the University of Denver...Ch. 23 - 53. Body fat Do the data shown in the table below...Ch. 23 - Prob. 54ECh. 23 - Midterms The data set below shows midterm and...Ch. 23 - Prob. 56ECh. 23 - Prob. 57ECh. 23 - All the efficiency money can buy 2011 A sample of...Ch. 23 - Education and mortality The following software...Ch. 23 - Property assessments The following software output...Ch. 23 - Prob. 61ECh. 23 - Prob. 62E
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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?2300arrow_forwardResearchers are interested in predicting the height of a child based on the heights of their mother and father. Data were collected, which included height of the child (height ), height of the mother ( mothersheight ), and height of the father (fathersheight ). The initial analysis used the heights of the parents to predict the height of the child (all units are inches). The results of the analysis, a multiple regression, are presented below. . regress height mothersheight fathersheight Source Model Residual Total height mothersheight fathersheight _cons SS 208.008457 314.295372 522.303829 df 2 37 Interpret the intercept of this model. 104.004228 8.49446952 Coef. Std. Err. MS 39 13.3924059 .6579529 .1474763 .2003584 .1382237 9.804327 12.39987 t P>|t| 4.46 0.000 C 0.156 0.79 0.434 Number of obs = F( 2, 37) = Prob > F R-squared Adj R-squared = Root MSE 40 12.24 0.0001 0.3983 0.3657 2.9145 [95% Conf. Interval] .3591375 -.0797093 -15.32021 .9567683 .4804261 34.92886arrow_forwardResearchers are interested in predicting the height of a child based on the heights of their mother and father. Data were collected, which included height of the child (height ), height of the mother ( mothersheight), and height of the father (fathersheight ). The initial analysis used the heights of the parents to predict the height of the child (all units are inches). The results of the analysis, a multiple regression, are presented below. . regress height mothersheight fathersheight Source Model Residual Total height mothersheight fathersheight _cons SS 208.008457 314.295372 522.303829 df 104.004228 2 37 8.49446952 MS 39 13.3924059 Coef. Std. Err. .6579529 .1474763 .2003584 .1382237 9.804327 12.39987 Interpret the slope associated with mother's height. t P>|t| 4.46 0.000 с 0.156 0.79 0.434 Number of obs = F( 2, 37) = Prob > F R-squared Adj R-squared = Root MSE = = .3591375 -.0797093 -15.32021 = 40 12.24 0.0001 0.3983 0.3657 2.9145 [95% Conf. Intervall 9567683 .4804261 34.92886arrow_forward
- Researchers are interested in predicting the height of a child based on the heights of their mother and father. Data were collected, which included height of the child (height ), height of the mother ( mothersheight ), and height of the father ( fathersheight ). The initial analysis used the heights of the parents to predict the height of the child (all units are inches). The results of the analysis, a multiple regression, are presented below. . regress height mothersheight fathersheight Source Model Residual Total height mothersheight fathersheight _cons SS df 208.008457 314.295372 37 522.303829 2 104.004228 8.49446952 MS 39 13.3924059 Coef. Std. Err. .6579529 .1474763 .2003584 .1382237 9.804327 12.39987 Calculate the test statistic that is labeled "C" in the output. t P>|t| 4.46 0.000 C 0.156 0.79 0.434 Number of obs = F( 2, Prob > F 37) = R-squared Adj R-squared = Root MSE 40 12.24 0.0001 = 0.3983 0.3657 2.9145 .3591375 -.0797093 -15.32021 = [95% Conf. Intervall .9567683 .4804261…arrow_forwardThe slope of a regression line tells you how much or little a change in your dependent variable impacts your independent variable. O TrueO Falsearrow_forwardSheila's doctor is concerned that she may suffer from gestational diabetes (high blood glucose levels during pregnancy). There is variation both in the actual glucose level and in the blood test that measures the level. A patient is classified as having gestational diabetes if the glucose level is above 140 miligrams per deciliter (mg/dl) one hour after having a sugary drink. Sheila's measured glucose level one hour after the sugary drink varies according to the Normal distribution with μμ = 120 mg/dl and σσ = 10 mg/dl. (a) If a single glucose measurement is made, what is the probability that Sheila is diagnosed as having gestational diabetes?(b) If measurements are made on 5 separate days and the mean result is compared with the criterion 140 mg/dl, what is the probability that Sheila is diagnosed as having gestational diabetes?arrow_forward
- Please answer letters b-e.arrow_forwardA real estate company wants to study the relationship between house sales prices and some important predictors of sales prices. Based on data from recently sold homes in the space, the following variables are used in a multiple regression model. y = sales price (in thousands of dollars) x₁ = total floor area (in square feet) x₂ = number of bedrooms x3 distance to nearest high school (in miles) = The estimated model is as follows. =76+0.098x₁ +16x₂ - 8x3 Answer the questions below for the interpretation of the coefficient of X₂ in this model. (a) Holding the other variables fixed, what is the average change in sales price for each additional bedroom in a house? dollars (b) Is this change an increase or a decrease? O increase O decrease Xarrow_forwardPlease answer parts d, e and f.arrow_forward
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