UNL PSYC 451 - Preparation for the Story Problem Portion of Quiz #1 (14 pages)

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Preparation for the Story Problem Portion of Quiz #1



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Preparation for the Story Problem Portion of Quiz #1

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Pages:
14
School:
University of Nebraska-Lincoln
Course:
Psyc 451 - Multivariate Research Design and Data Analysis

Unformatted text preview:

Preparation for the Story Problem Portion of Quiz 1 Correlations Bivariate Regression b weights Multiple Regression b weights 1 Tell how to interpret each of the following correlations r for a quantitative continuous predictor variable nsig r for a quantitative continuous predictor variable r for a quantitative continuous predictor variable r for a binary predictor variable nsig r for a binary predictor variable r for a binary predictor variable 2 Tell how to interpret each of the following simple regression weights b for a quantitative continuous predictor variable nsig b for a quantitative continuous predictor variable b for a quantitative continuous predictor variable b for a binary predictor variable nsig b for a binary predictor variable b for a binary predictor variable 3 Tell how to interpret each of the following multiple regression weights b for a quantitative continuous predictor variable nsig b for a quantitative continuous predictor variable b for a quantitative continuous predictor variable b for a binary predictor variable nsig b for a binary predictor variable b for a binary predictor variable 4 When one considers the correlation of a specific predictor with the criterion and that predictor s contribution to a multiple regression there are nine possibilities Specify each of them there might be a special name or maybe just a description Correlation Multiple Regression Weight significant non significant significant significant non significant significant Answers 1a interpreting correlations quant predictors r direct relationship those with higher scores on the predictor tend to have higher scores on the criterion and vice versa nsig r no reliable relationship between pred and crit knowing value of one tells you nothing about value of the other r indirect relationship those with higher scores on the predictor tend to have lower scores on the criterion and vice versa binary predictors r group with higher coded value has higher mean score on the criterion



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