Concept explainers
Finding the Equation of a Regression Line In Exercises 17β26, find the equation of the regression line for the data. Then construct a
17. Height and Number of Stories The heights (in feet) and the numbers of stories of the nine tallest buildings in Houston, Texas (Source: Empires Corporation)
(a) x = 950 feet
(b) x = 850 feet
(c) x = 800 feet
(d) x = 700 feet
Trending nowThis is a popular solution!
Chapter 9 Solutions
Elementary Statistics: Picturing the World (7th Edition)
- Regression and Predictions. Exercises 13β28 use the same data sets as Exercises 13β28 in Section 10-1. In each case, find the regression equation, letting the first variable be the predictor (x) variable. Find the indicated predicted value by following the prediction procedure summarized in Figure 10-5 on page 493. Tips Using the bill/tip data, find the best predicted tip amount for a dinner bill of $100. What tipping rule does the regression equation suggest?arrow_forwardApplying the Concepts and SkillsIn Exercises, we repeat the information from Exercises. For each exercise here, discuss what satisfying Assumptions 1β3 for regression inferences by the variables under consideration would mean.ExercisesApplying the Concepts and SkillsIn each of Exercises,a. find the regression equation for the data points.b. graph the regression equation and the data points.c. describe the apparent relationship between the two variables under consideration.d. interpret the slope of the regression line.e. identify the predictor and response variables.f. identify outliers and potential influential observations.g. predict the values of the response variable for the specified values of the predictor variable, and interpret your results.Tax Efficiency.Tax efficiency is a measure, ranging from 0 to 100, of how much tax due to capital gains stock or mutual funds investors pay on their investments each year; the higher the tax efficiency, the lower is the tax. In the articleβ¦arrow_forwardRegression and Predictions. Exercises 13β28 use the same data sets as Exercises 13β28 in Section 10-1. In each case, find the regression equation, letting the first variable be the predictor (x) variable. Find the indicated predicted value by following the prediction procedure summarized in Figure 10-5 on page 493. Oscars Using the listed actress/actor ages, find the best predicted age of the Best Actor given that the age of the Best Actress is 54 years. Is the result reasonably close to the Best Actorβs (Eddie Redmayne) actual age of 33 years, which happened in 2015, when the Best Actress was Julianne Moore, who was 54 years of age?arrow_forward
- Regression and Predictions. Exercises 13β28 use the same data sets as Exercises 13β28 in Section 10-1. In each case, find the regression equation, letting the first variable be the predictor (x) variable. Find the indicated predicted value by following the prediction procedure summarized in Figure 10-5 on page 493. Internet and Nobel Laureates Find the best predicted Nobel Laureate rate for Japan, which has 79.1 Internet users per 100 people. How does it compare to Japanβs Nobel Laureate rate of 1.5 per 10 million people?arrow_forwardManagement proposed the following regression model to predict sales at a fast-food outlet.arrow_forwardRegression and Predictions. Exercises 13β28 use the same data sets as Exercises 13β28 in Section 10-1. In each case, find the regression equation, letting the first variable be the predictor (x) variable. Find the indicated predicted value by following the prediction procedure summarized in Figure 10-5 on page 493. CPI and the Subway Use the CPI/subway fare data from the preceding exercise and find the best predicted subway fare for a time when the CPI reaches 500. What is wrong with this prediction?arrow_forward
- Regression and Predictions. Exercises 13β28 use the same data sets as Exercises 13β28 in Section 10-1. In each case, find the regression equation, letting the first variable be the predictor (x) variable. Find the indicated predicted value by following the prediction procedure summarized in Figure 10-5 on page 493. Crickets and Temperature Find the best predicted temperature at a time when a cricket chirps 3000 times in 1 minute. What is wrong with this predicted temperature?arrow_forwardStatistical technique used to determine the degree to which two variables are related is known as a. Regression b. Correlation c. None of these d. Dispersionarrow_forwardRefer to the data set:(-1, 2), (1, 3), (1, 5), (2, 7), (3, 8), (4, 11)Part a: Make a scatter plot and determine which type of model best fits the data.Part b: Find the regression equation.Part c: Use the equation from Part b to determine y when x = 10arrow_forward
- Appendix B Data Sets. In Exercises 13β16, refer to the indicated data set in Appendix B and use technology to obtain results. Predicting IQ Score Refer to Data Set 8 βIQ and Brain Sizeβ in Appendix B and find the best regression equation with IQ score as the response (y) variable. Use predictor variables of brain volume and/or body weight. Why is this equation best? Based on these results, can we predict someoneβs IQ score if we know their brain volume and body weight? Based on these results, does it appear that people with larger brains have higher IQ scores?arrow_forwardRegression analysis is a statistical tool used to describe a linear or a non linear relationship between one or more predictor variables and one response variable Select one: a.Β True b.Β Falsearrow_forwardCity Fuel Consumption: Finding the Best Multiple Regression Equation. In Exercises 9β12, refer to the accompanying table, which was obtained using the data from 21 cars listed in Data Set 20 βCar Measurementsβ in Appendix B. The response (y) variable is CITY (fuel consumption in mi/gal). The predictor (x) variables are WT (weight in pounds), DISP (engine displacement in liters), and HWY (highway fuel consumption in mi /gal). Which regression equation is best for predicting city fuel consumption? Why?arrow_forward
- Calculus For The Life SciencesCalculusISBN:9780321964038Author:GREENWELL, Raymond N., RITCHEY, Nathan P., Lial, Margaret L.Publisher:Pearson Addison Wesley,