EBK STATISTICS FOR THE BEHAVIORAL SCIEN
3rd Edition
ISBN: 9781506386249
Author: PRIVITERA
Publisher: VST
expand_more
expand_more
format_list_bulleted
Concept explainers
Videos
Question
Chapter 16, Problem 16CAP
1.
To determine
Identify the predictor variable in the description.
2.
To determine
Explain the direction of this relationship in words.
Expert Solution & Answer
Want to see the full answer?
Check out a sample textbook solution
Students have asked these similar questions
Use the model to make the appropriate prediction.
A sociologist wanted to determine whether there was a relation between a state's poverty rate (x) and its teen pregnancy rate (y). Data from all 50 states produced the regression model:
yˆ=4.3+1.4(x)
What does the model suggest for the poverty rate of Florida, which has a poverty rate of 16.6?
a) 9.2%
b) 27.5%
c) 12.9%
d) 17%
e) 22.4%
The relationship between sleep hours and overall happiness level on the next day was estimated as below in a linear format.
(Happiness level is measured through a five-point scale: 1 = Extremely unhappy, 5 = Extremely happy)
Overall happiness level = 0.27 * Sleep hours + 2.34
(The p-value for the coefficient of Sleep hours is 0.02.)
Based on this equation, what is the expected happiness level of a person on a certain day, when he slept 7 hours the day before?
the scatter plot displays the number of pretzels students could grab with their dominant hand and their handspan, measured in centimeters. the equation of the line y=-14.7+1.59x is called the least-squares regression line because it
Chapter 16 Solutions
EBK STATISTICS FOR THE BEHAVIORAL SCIEN
Ch. 16.2 - Prob. 1.1LCCh. 16.2 - Prob. 1.2LCCh. 16.2 - Prob. 1.3LCCh. 16.4 - Prob. 2.1LCCh. 16.4 - Prob. 2.2LCCh. 16.4 - Prob. 2.3LCCh. 16.5 - Prob. 3.1LCCh. 16.5 - Prob. 3.2LCCh. 16.6 - Prob. 4.1LCCh. 16.6 - Prob. 4.2LC
Ch. 16.6 - Prob. 4.3LCCh. 16.8 - Prob. 5.1LCCh. 16.8 - Prob. 5.2LCCh. 16.8 - Prob. 5.3LCCh. 16.9 - Prob. 6.1LCCh. 16.9 - Prob. 6.2LCCh. 16.9 - Prob. 6.3LCCh. 16.13 - Prob. 7.1LCCh. 16.13 - Prob. 7.2LCCh. 16.13 - Prob. 7.3LCCh. 16 - Prob. 1FPCh. 16 - Prob. 2FPCh. 16 - Prob. 3FPCh. 16 - Prob. 4FPCh. 16 - Prob. 5FPCh. 16 - Prob. 6FPCh. 16 - Prob. 7FPCh. 16 - Prob. 8FPCh. 16 - Prob. 9FPCh. 16 - Prob. 10FPCh. 16 - Prob. 11FPCh. 16 - Prob. 12FPCh. 16 - Prob. 13CAPCh. 16 - Prob. 14CAPCh. 16 - Prob. 15CAPCh. 16 - Prob. 16CAPCh. 16 - Prob. 17CAPCh. 16 - Prob. 18CAPCh. 16 - Prob. 19CAPCh. 16 - Prob. 20CAPCh. 16 - Prob. 21CAPCh. 16 - Prob. 22CAPCh. 16 - Prob. 23CAPCh. 16 - Prob. 24CAPCh. 16 - Prob. 25CAPCh. 16 - Prob. 26CAPCh. 16 - Prob. 27CAPCh. 16 - Prob. 28CAPCh. 16 - Prob. 29CAPCh. 16 - Prob. 30PRCh. 16 - Prob. 31PRCh. 16 - Prob. 32PRCh. 16 - Prob. 33PRCh. 16 - Prob. 34PR
Knowledge Booster
Learn more about
Need a deep-dive on the concept behind this application? Look no further. Learn more about this topic, statistics and related others by exploring similar questions and additional content below.Similar questions
- Does Table 2 represent a linear function? If so, finda linear equation that models the data.arrow_forwardFor the revenue model in Exercise 10.206 and Exercise 10.210, explain what the x-intercepts mean to the backpack retailer.arrow_forwardFor the revenue model in Exercise 10.205 and Exercise 10.209, explain what the x-intercepts mean to the computer store owner.arrow_forward
- Do heavier cars use more gasoline? To answer this question, a researcher randomly selected 15 cars. He collected their weight (in hundreds of pounds) and the mileage (MPG) for each car. From a scatterplot made with the data, a linear model seemed appropriate which is included as a photo. What proportion of the variation in mileage is accounted for by the linear relationship with the wight of the car? And if we wanted to test if there is a significant straight-line relationship between the weight and the mileage of a car, we can perform a T test. Give the value of the t statistic for this test.arrow_forwardGPA and Absences 4.8 44 4.0 36 各3.2 2.8 24 20 16 4. 10 12 14 16 Absences (Days)arrow_forwardSherry rents long boards. She records the height in cm and length of the board in cm that the customers rented. She notices a fairly linear relationship so she calculates a least squares regression equation for predicting board length from customer height: y=1/3x+1/3 What is the residual of a customer with a height of 155 cm who rents a 51 cm board?arrow_forward
- A physics student wants to measure the stiffness of a spring (force required per cm stretched). He knows that according to Hooke's law, there is a linear relationship between the distance a spring is stretched and the force needed to stretch the spring. He collects some data by measuring the force applied to the spring when he stretches the spring by some amount. The plot and the least squares fit is given below.From the regression model, the intercept was found to be -2.532 and the slope was found to be 25.321.Part i).The stiffness of the spring was predicted to beA. -9.961B. 25.321C. 50.642D. -2.532E. 125.84Part ii).Refer to the previous question, the physics student used the regression model to predict that a force of 377.28N would be required to stretch the spring by 15cm. Remarkably, his prediction was horribly wrong. Can you explain why? (Check all that apply)A. He made a prediction outside of the range of forces observed.B. He had outliers or influential points in his data.C.…arrow_forwardA physics student wants to measure the stiffness of a spring (force required per cm stretched). He knows that according to Hooke's law, there is a linear relationship between the distance a spring is stretched and the force needed to stretch the spring. He collects some data by measuring the force applied to the spring when he stretches the spring by some amount. The plot and the least squares fit is given below.From the regression model, the intercept was found to be -2.532 and the slope was found to be 25.321.Part i).The stiffness of the spring was predicted to beA. -9.961B. 25.321C. 50.642D. -2.532E. 125.84Part ii).Refer to the previous question, the physics student used the regression model to predict that a force of 377.28N would be required to stretch the spring by 15cm. Remarkably, his prediction was horribly wrong. Can you explain why? (Check all that apply)A. He made a prediction outside of the range of forces observed.B. He had outliers or influential points in his data.C.…arrow_forwardA statistics professor wants to use the number of hours a student studies for a statistic final exam (x) to predict the final exam score (y). A regression model was fit based on data collected for a class during the previous semester, with the following results: y =35.0 + 3x What is the interpretation of the y-intercept? Select the correct response: The y-intercept indicates that when the student study for the final exam, the mean final exam score is high The y-intercept indicates that when the student does not study for the final exam, the mean final exam score is 35.0 The y-intercept indicates that for each increase of one hour in studying time, the mean change in the final exam score is predicted to be 3.0 The y-intercept indicates that for each increase of one hour in studying time, the mean change in the final exam score is predicted to be 38.arrow_forward
- A study investigated how the content of vitamin A in carrots is affected by the time being cooked. In this example: X represents the amount of time, in minutes, that the carrot slices were cooked Y represents the content of vitamin A (in milligrams) in the carrot slices The least-squares regression equation for this relationship is: Y = 23.4 – 0.55X In this study, which variable is the explanatory variable?arrow_forwardHelp please!arrow_forwardA least squares regression line was calculated to relate the length (cm) of newborn boys to their weight in kg. The line is weight = - 5.83 + 0.163 length. Explain in words what this model means. Should new parents (who tend to worry) be concerned if their newborn's length and weight don't fit this equation? What does the given model mean? O A. The weight of a newborn boy can be predicted as - 5.83 kg plus 0.163 kg per cm of length. O B. The minimum length of a newborn baby boy can be no less than 35.7669 cm. O C. The weight of a newborn boy will always equal - 5.83 kg plus 0.163 kg per cm of length. O D. The length of a newborn boy can be predicted as - 5.83 cm plus 0.163 cm per kg of weight. Should new parents (who tend to worry) be concerned if their newborn's length and weight don't fit this equation? O A. No, because this is a model fit to divide the data. All newborn weights above the line are normal and all newborn weights below the line are a matter for concern. O B. Yes,…arrow_forward
arrow_back_ios
SEE MORE QUESTIONS
arrow_forward_ios
Recommended textbooks for you
Glencoe Algebra 1, Student Edition, 9780079039897...AlgebraISBN:9780079039897Author:CarterPublisher:McGraw Hill
College Algebra (MindTap Course List)AlgebraISBN:9781305652231Author:R. David Gustafson, Jeff HughesPublisher:Cengage Learning
Algebra & Trigonometry with Analytic GeometryAlgebraISBN:9781133382119Author:SwokowskiPublisher:Cengage
Elementary AlgebraAlgebraISBN:9780998625713Author:Lynn Marecek, MaryAnne Anthony-SmithPublisher:OpenStax - Rice University
Holt Mcdougal Larson Pre-algebra: Student Edition...AlgebraISBN:9780547587776Author:HOLT MCDOUGALPublisher:HOLT MCDOUGAL
Glencoe Algebra 1, Student Edition, 9780079039897...
Algebra
ISBN:9780079039897
Author:Carter
Publisher:McGraw Hill
College Algebra (MindTap Course List)
Algebra
ISBN:9781305652231
Author:R. David Gustafson, Jeff Hughes
Publisher:Cengage Learning
Algebra & Trigonometry with Analytic Geometry
Algebra
ISBN:9781133382119
Author:Swokowski
Publisher:Cengage
Elementary Algebra
Algebra
ISBN:9780998625713
Author:Lynn Marecek, MaryAnne Anthony-Smith
Publisher:OpenStax - Rice University
Holt Mcdougal Larson Pre-algebra: Student Edition...
Algebra
ISBN:9780547587776
Author:HOLT MCDOUGAL
Publisher:HOLT MCDOUGAL
Correlation Vs Regression: Difference Between them with definition & Comparison Chart; Author: Key Differences;https://www.youtube.com/watch?v=Ou2QGSJVd0U;License: Standard YouTube License, CC-BY
Correlation and Regression: Concepts with Illustrative examples; Author: LEARN & APPLY : Lean and Six Sigma;https://www.youtube.com/watch?v=xTpHD5WLuoA;License: Standard YouTube License, CC-BY