Essentials of Statistics for The Behavioral Sciences (MindTap Course List)
9th Edition
ISBN: 9781337098120
Author: Frederick J Gravetter, Larry B. Wallnau, Lori-Ann B. Forzano
Publisher: Cengage Learning
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Textbook Question
Chapter 14, Problem 15P
A set of n =18 pairs of scores (X and Y values) has SSY = 20. SSY, = 80. and SP = 10. If the
- a. Calculate the Pearson
correlation for the scores - b. Find the regression equation for predicting Y from the X values
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Chapter 14 Solutions
Essentials of Statistics for The Behavioral Sciences (MindTap Course List)
Ch. 14.1 - Which of the following is a justified conclusion...Ch. 14.1 - Which of the following correlations indicates the...Ch. 14.2 - What is the value of SP for a set of n 5 pairs of...Ch. 14.2 - A set of n = 5 pairs of X and Y scores has SSx =...Ch. 14.2 - Prob. 3LCCh. 14.3 - A researcher obtains a strong positive correlation...Ch. 14.3 - A set of n = 10 pairs of X and Y values produces a...Ch. 14.4 - Prob. 1LCCh. 14.4 - The Pearson correlation is calculated for a sample...Ch. 14.5 - Prob. 1LC
Ch. 14.5 - Prob. 2LCCh. 14.5 - Prob. 3LCCh. 14.5 - A researcher would like to measure the...Ch. 14.6 - In the general linear equation Y = bX + a, what is...Ch. 14.6 - A set of n = 25 pairs of X and Y values has Mx =...Ch. 14.6 - Prob. 3LCCh. 14.6 - A researcher computes the regression equation for...Ch. 14 - Calculate SP (the sum of products of deviations)...Ch. 14 - Calculate SP (the sum of products of deviations)...Ch. 14 - For the following scores, X Y 2 7 5 4 4 7 7 5 2 6...Ch. 14 - For the following scores, X Y 0 4 2 9 1 6 1 9 a....Ch. 14 - For the following scores, X Y 4 0 1 5 1 0 4 5 a....Ch. 14 - For the following scores, X Y 3 6 5 5 6 0 6 2 5 2...Ch. 14 - With a small sample, a single point can have a...Ch. 14 - For the following set of scores, X Y 4 5 6 5 3 2 9...Ch. 14 - At the beginning of this chapter we discussed a...Ch. 14 - For a two-tailed test with = .05 use Table B.6 to...Ch. 14 - It appears that there is a significant...Ch. 14 - Sketch a graph showing the line for the equation Y...Ch. 14 - A set of n =18 pairs of scores (X and Y values)...Ch. 14 - A set of n = 15 pairs of scores (X and Y values)...Ch. 14 - Briefly explain what is measured by the standard...Ch. 14 - In general, how is the magnitude of the standard...Ch. 14 - For the following set of data, find the linear...Ch. 14 - For the following data: a. Find the regression...Ch. 14 - For the following scores: X Y 3 8 5 8 2 6 2 3 4 6...Ch. 14 - The regression equation is computed for a set of n...Ch. 14 - Solve the following problems. a. One set of 10...Ch. 14 - Does the regression equation from Problem 20...Ch. 14 - Solve the following problems. a. A researcher...
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- Find the equation of the regression line for the following data set. x 1 2 3 y 0 3 4arrow_forwardFor the following exercises, consider the data in Table 5, which shows the percent of unemployed in a city ofpeople25 years or older who are college graduates is given below, by year. 41. Based on the set of data given in Table 7, calculatethe regression line using a calculator or othertechnology tool, and determine the correlationcoefficient to three decimal places.arrow_forwardFor the following exercises, consider the data in Table 5, which shows the percent of unemployed ina city of people 25 years or older who are college graduates is given below, by year. 40. Based on the set of data given in Table 6, calculate the regression line using a calculator or other technology tool, and determine the correlation coefficient to three decimal places.arrow_forward
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- Olympic Pole Vault The graph in Figure 7 indicates that in recent years the winning Olympic men’s pole vault height has fallen below the value predicted by the regression line in Example 2. This might have occurred because when the pole vault was a new event there was much room for improvement in vaulters’ performances, whereas now even the best training can produce only incremental advances. Let’s see whether concentrating on more recent results gives a better predictor of future records. (a) Use the data in Table 2 (page 176) to complete the table of winning pole vault heights shown in the margin. (Note that we are using x=0 to correspond to the year 1972, where this restricted data set begins.) (b) Find the regression line for the data in part ‚(a). (c) Plot the data and the regression line on the same axes. Does the regression line seem to provide a good model for the data? (d) What does the regression line predict as the winning pole vault height for the 2012 Olympics? Compare this predicted value to the actual 2012 winning height of 5.97 m, as described on page 177. Has this new regression line provided a better prediction than the line in Example 2?arrow_forwardFor the following exercises, consider this scenario: The profit of a company decreased steadily overa ten-year spam.The following ordered pairs shows dollars and the number of units sold in hundreds and the profit in thousands ofover the ten-year span, (number of units sold, profit) for specific recorded years: (46,600),(48,550),(50,505),(52,540),(54,495). Use linear regression to determine a function Pwhere the profit in thousands of dollars depends onthe number of units sold in hundreds.arrow_forward
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