Exam 16: Predicting Wholl Win the Super Bowl: Using Linear Regression
Exam 1: Statistics or Sadistics Its up to You50 Questions
Exam 2: Means to an End: Computing and Understanding Averages79 Questions
Exam 3: Vive La Différence: Understanding Variability80 Questions
Exam 4: A Picture Really Is Worth a Thousand Words41 Questions
Exam 5: Ice Cream and Crime: Computing Correlation Coefficients77 Questions
Exam 6: Just the Truth: An Introduction to Understanding Reliability and Validity77 Questions
Exam 7: Hypotheticals and You: Testing Your Questions73 Questions
Exam 8: Are Your Curves Normal Probability and Why It Counts76 Questions
Exam 9: Significantly Significant: What It Means for You and Me78 Questions
Exam 10: Only the Lonely: The One Sample Z-Test79 Questions
Exam 11: Tea for Two: Tests Between the Means of Different Groups69 Questions
Exam 12: Tea for Two Again: Tests Between the Means of Related Groups81 Questions
Exam 13: Two Groups Too Many Try Analysis of Variance77 Questions
Exam 14: Two Too Many Factors: Factorial Analysis of Variancea Brief Introduction77 Questions
Exam 15: Cousins or Just Good Friends Testing Relationships Using Correlation Coefficient75 Questions
Exam 16: Predicting Wholl Win the Super Bowl: Using Linear Regression79 Questions
Exam 17: What to Do When Youre Not Normal: CHI-Square and Some Other Nonparametric Tests75 Questions
Exam 18: Some Other Important Statistical Procedures You Should Know About47 Questions
Exam 19: Data Mining: An Introduction to Getting the Most Out of Your Big Data50 Questions
Exam 20: A Statistical Software Sampler9 Questions
Exam 21: The Ten or More Best and Most Fun Internet Sites for Statistics Stuff9 Questions
Exam 22: The Ten Commandments of Data Collection10 Questions
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Standard error of estimate is computed as the variance of all values for error in prediction.
(True/False)
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Error in prediction (error of estimate) is calculated as the distance between each individual data point and the regression line.
(True/False)
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What important guideline should you keep in mind when choosing independent variables for multiple regression?
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Based on the formula for a regression line, what does a represent?
(Multiple Choice)
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The higher the absolute value of the correlation coefficient, the less accurate the prediction is of one variable based on the other variable.
(True/False)
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The regression line reflects the best estimate of predicted scores for the independent variable based on levels of the dependent variable.
(True/False)
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Which of the following is the point at which the regression line crosses the y-axis?
(Multiple Choice)
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In regression, the criterion variable is also known as the _______.
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Which of the following symbols is associated with the y-intercept in the regression equation?
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When using two predictor variables, these variables should be _______.
(Multiple Choice)
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What statistical technique is used to make predictions of future outcomes based on present data?
(Multiple Choice)
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When determining the number of predictor variables to use to predict a criterion variable, you need to keep all of the following guidelines in mind, except ______.
(Multiple Choice)
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Which of the following is used to illustrate the "best guess" as to the predicted Y variable score based on X?
(Multiple Choice)
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When computing a predicted value, your second step is to ______.
(Multiple Choice)
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Which of the following is the correct formula for linear regression?
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Which of the following symbols is associated with the predicted score in the regression equation?
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