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Solutions Manual for Categorical and Nonparametric Data Analysis: Choosing the Best Statistical Technique, 1st Edition (Nussbaum, 2014) | All Chapters 1–15 Covered

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Original solutions manual for Categorical and Nonparametric Data Analysis: Choosing the Best Statistical Technique, 1st Edition by E. Michael Nussbaum (2014), covering the essential principles of categorical data analysis, nonparametric statistics, hypothesis testing, contingency tables, regression models, generalized estimating equations, and statistical decision-making. The solutions manual includes Chapter 1 Levels of Measurement, Probability, and the Binomial Formula; Chapter 2 Estimation and Hypothesis Testing; Chapter 3 Random Variables and Probability Distributions; Chapter 4 Contingency Tables: The Chi-Square Test and Associated Effect Sizes; Chapter 5 Contingency Tables: Special Situations; Chapter 6 Basic Nonparametric Tests for Ordinal Data; Chapter 7 Nonparametric Tests for Multiple or Related Samples; Chapter 8 Advanced Rank Tests (For Interactions and Robust ANOVA); Chapter 9 Linear Regression and Generalized Linear Models; Chapter 10 Binary Logistic Regression; Chapter 11 Multinomial Logistic, Ordinal, and Poisson Regression; Chapter 12 Log-Linear Analysis; Chapter 13 General Estimating Equations; Chapter 14 Estimation Procedures; and Chapter 15 Choosing the Best Statistical Technique, providing comprehensive, step-by-step solutions for statistics, data analysis, research methods, biostatistics, social sciences, psychology, education, and graduate-level quantitative methods courses.

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, TABLE OF CONTENTS
Solutions Manual: Categorical and Nonparametric Data Analysis:
Choosing the Best Statistical Technique, 1st Edition
Author: E. Michael Nussbaum
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Chapter 1. Levels of Measurement, Probability, and the Binomial Formula
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Chapter 2. Estimation and Hypothesis Testing
Chapter 3. Random Variables and Probability Distributions
Chapter 4. Contingency Tables: The Chi-Square Test and Associated Effect Sizes




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Chapter 5. Contingency Tables: Special Situations
Chapter 6. Basic Nonparametric Tests for Ordinal Data
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Chapter 7. Nonparametric Tests for Multiple or Related Samples
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Chapter 8. Advanced Rank Tests (For Interactions and Robust ANOVA)
Chapter 9. Linear Regression and Generalized Linear Models
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Chapter 10. Binary Logistic Regression
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Chapter 11. Multinomial Logistic, Ordinal, and Poisson Regression
Chapter 12. Log-Linear Analysis
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Chapter 13. General Estimating Equations
Chapter 14. Estimation Procedures
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Chapter 15. Choosing the Best Statistical Technique
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, Answers to Even Numbered Problems
Chapter 1 - Levels of Measurement, Probability, and the Binomial Formula

2. (a) ordinal. (b) metric (ratio). (c) nominal. (d) ordinal (ordered categories).
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12. ∗.752∗1−.75  .21 .
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14. =BINOM.DIST(2,4,0.75,1) 26.2%.
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18. z 3.74 , p = .009%.
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©Instructor Web Resource Material Created by E. Michael Nussbaum to accompany Nussbaum:
Categorical and Nonparametric Data Analysis, 2015, Routledge/Taylor & Francis.
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, Answers to Even Numbered Problems

Chapter 2 - Estimation and Hypothesis Testing
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2. Reject null hypothesis of π .80 (z = -4.125, p < .001, SPSS reports the one-sided




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asymptotic value). 9.5
4. X = 9.5 with continuity correction. P .3654 . For one-tailed test, H : = .6525; H :
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 < .6525. SE 
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≤ - 3.04) = .001 So one-tailed p = .001. Because the normal distribution is symmetrical,
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double the one-tailed value, yielding p = .002 (two-tailed).
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6. T = 7, n = 9 (with tie omitted), H0: Prob(+) = .50; Ha: Prob(+) ≠ .50. p = .09 (one-tailed), p =

.18 (two-tailed). (In EXCEL, =1-BINOM.DIST(6, 9, .50, 1)  .09. We fail to reject the null
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hypothesis of no trend.
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8. T = 6, n = 6, H0: Prob(+) = .50; Ha: Prob(+) ≠ .50. p = .016 (one-tailed), p = .03 (two-tailed).

(In EXCEL, =1-BINOM.DIST(5, 6, .50, 1)  .016.) The association is significant.
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©Instructor Web Resource Material Created by E. Michael Nussbaum to accompany Nussbaum:
Categorical and Nonparametric Data Analysis, 2015, Routledge/Taylor & Francis.
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