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 25P
Solve the following problems.
- a. A researcher computes the linear regression equation for a sample of n = 20 pairs of scores, X and Y values. If an analysis of regression is used to lest the significance of the equation, what are the df values for the F-ratio?
- b. A researcher evaluating the significance of a regression equation obtains an F-ratio with df = 1, 23. How many pairs of scores, X and Y values, are in the sample?
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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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- The following fictitious table shows kryptonite price, in dollar per gram, t years after 2006. t= Years since 2006 0 1 2 3 4 5 6 7 8 9 10 K= Price 56 51 50 55 58 52 45 43 44 48 51 Make a quartic model of these data. Round the regression parameters to two decimal places.arrow_forwardbThe average rate of change of the linear function f(x)=3x+5 between any two points is ________.arrow_forwardOlympic 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_forward
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