Quantitative and Statistical Research Methods From Hypothesis to Results.

Quantitative and Statistical Research Methods From Hypothesis to Results.

Of Our Screening Results for the Underlying Assumption of Normality

Saved in:
Bibliographic Details
Online Access: Full text (MCPHS users only)
Main Author: Martin, William E.
Format: Electronic eBook
Language:English
Published: Newark : John Wiley & Sons, Incorporated, 2012
Series:New York Academy of Sciences Ser.
Subjects:
Electronic books.
Local Note:ProQuest Ebook Central
Table of Contents:
  • Intro
  • Quantitative and Statistical Research Methods: From Hypothesis to Results
  • Contents
  • Tables and Figures
  • Preface
  • Acknowledgments
  • The Authors
  • Chapter 1: Introduction and Overview
  • Review of Foundational Research Concepts
  • Independent, Dependent, and Extraneous Variables
  • Scales of Measurement of Variables
  • Review of Foundational Statistical Information
  • Measures of Central Tendency
  • Measures of Variability (Dispersion) of Scores
  • Variance of the Sample (s2)
  • Standard Deviation of the Sample (s)
  • Coefficient of Variation (C)
  • Visual Representations of a Data Set
  • The Normal Distribution
  • Characteristics of the Normal Distribution
  • Descriptive Statistical Applications of the Normal Distribution
  • Inferential Statistical Applications of the Normal Distribution
  • Summary
  • Problem Assignment
  • Key Terms
  • Chapter 2: Logical Steps of Conducting Quantitative Research: Hypothesis-Testing Process
  • Hypothesis-Testing Process
  • Summary
  • Problem Assignment
  • Key Terms
  • Chapter 3: Maximizing Hypothesis Decisions Using Power Analysis
  • Balance Between Avoiding Type I and Type II Errors
  • Illustration of Avoiding Making a Type I (Alpha) Error
  • Illustration of Avoiding Making a Type II (Alpha) Error
  • A Priori Power Analysis
  • Summary
  • Problem Assignment
  • Key Terms
  • Chapter 4: Research and Statistical Designs
  • Formulating Experimental Conditions
  • Reducing the Imprecision in Measurement
  • Sampling Error
  • Error of Measurement
  • Controlling Extraneous Experimental Influences
  • Methods of Controlling Extraneous Variables
  • Internal Validity and Experimental Designs
  • Internal Validity
  • Experimental Designs
  • Randomized Multiple Treatments and Control with Posttest-Only Design
  • Randomized Multiple Treatments and Control with Pretest and Posttest Design
  • Quasi-Experimental Designs
  • Repeated-Treatment Design with One Group
  • Nonequivalent No-Treatment Control Group Time-Series Design
  • Correlational Research Methods
  • Choosing a Statistic to Use for an Analysis
  • Summary
  • Problem Assignment
  • Key Terms
  • Chapter 5: Introduction to IBM SPSS 20
  • The IBM SPSS 20 Data View Screen
  • Naming and Defining Variables in Variable View
  • Entering Variables
  • Entering Data
  • Examples of Basic Analyses
  • Examples of Modifying Data Procedures
  • Summary
  • Problem Assignment
  • Key Terms
  • Chapter 6: Diagnosing Study Data for Inaccuracies and Assumptions
  • Research Example
  • Detecting Erroneous Data Entries
  • Identifying and Dealing with Missing Data
  • Identifying and Assessing Univariate Outliers
  • Identifying and Assessing Univariate Outliers
  • Screening and Making Decisions about Univariate Assumptions
  • Skewness and Kurtosis
  • Histograms
  • Skewness Screening
  • Kurtosis Screening
  • Shapiro-Wilk Statistic
  • Assessing Normal Q-Q Plots for Normality

Similar Items