Exam 14: Regression Analysis
Exam 1: Introduction to Statistics24 Questions
Exam 2: Percentages, Graphs and Measures of Central Tendency69 Questions
Exam 3: Measures of Variability99 Questions
Exam 4: The Normal Curve and Z Score115 Questions
Exam 5: Z Scores, T Scores and Other Normal Curve Transformations110 Questions
Exam 6: Probability76 Questions
Exam 7: Statistics and Parameters92 Questions
Exam 8: Parameter Estimates129 Questions
Exam 9: The Fundamentals of Research Methodology173 Questions
Exam 10: The Hypothesis of Difference130 Questions
Exam 11: The Hypothesis of Association: Correlation131 Questions
Exam 12: Analysis of Variance108 Questions
Exam 13: Nominal Categorical Data and the Chi Square89 Questions
Exam 14: Regression Analysis122 Questions
Exam 15: Repeated-Measures and Matched-Subjects Designs Interval Data113 Questions
Exam 16: Non-Parametrics Revisited: the Ordinal Case113 Questions
Exam 17: Tests and Measurements69 Questions
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The regression of Y on X is used to predict X, given information on a third variable.
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The standard error of multiple estimate may be used when making predictions from
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For the Pearson r, the greater the number of degrees of freedom, the greater the likelihood of
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In the regression equation for Y on X, the "a" term symbolizes
(Multiple Choice)
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Each single data point on a scatter plot represents a pair of scores.
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When all of the internal correlations are significant, then the multiple R must always be significant.
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If the Y intercept equals 50, then a Y value of 50 corresponds with an X value of 0.
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When a correlation value among three or more interval-data variables is required, then the appropriate statistical test is
(Multiple Choice)
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The most accurate predictions are made when the standard error of estimate equals
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In order to calculate the standard error of estimate, the value of the Pearson r must be known.
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For questions below, use the following: A researcher collects the following measures: Y mean = 50, with a standard deviation of 10 X1 mean = 100, with a standard deviation of 15 X2 mean = 200, with a standard deviation of 20 Significant correlations among the variables were found to be as follows: y and 1 = .60 y and 2 = .75 1 and 2 = .20
-Calculate the standard error of multiple estimate.
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A major difference between the Pearson r and the multiple R is that the multiple R requires the use of
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In a two variable linear regression, the intercept indicates the value of when X is at its minimum value.
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Whenever the correlation has a positive value, so too will the
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