TABLE OF CONTENTS
I.
The Basics
Basic Types of
Research Designs
Goal Definition
Research Questions, Hypotheses, and
Null Hypotheses
Significance
One-Tailed and Two-Tailed
Significance Tests
Procedure Used to Test for
Significance
Bonferroni's Theorem
Sampling
Data Collection
Data Analysis
Reporting the Results
Validity and Reliability
Variability and Error
II. Types Of
Data
Nominal Data
Examples of Nominal Data
Ordinal Data
Examples of Ordinal Data
Interval and Ratio Data
Examples of Interval and Ratio Data
The Statistical Test You Use Depends
on the Type
of Data you Have
III. Designing
and Using Questionnaires
Ways to Get
Information
Questionnaire Research Flow Chart
Time Considerations
Cost Considerations
Advantages of Written Questionnaires
Disadvantages Of Written
Questionnaires
Questionnaire Design - General
Considerations
Qualities of a Good Question
Pre-notification Letters
Cover Letters
Response Rate and Following up on
Nonrespondents
Nonresponse Bias
The Order of the Questions
Anonymity and Confidentiality
The Length of a Questionnaire
Incentives
Notification of a Cutoff Date
Reply Envelopes and Postage
The Outgoing Envelope and Postage
"Don't Know",
"Undecided", and
"Neutral" Response
Question Wording
Sponsorship
IV. Descriptive
and Inferential Statistics
Minimum, Maximum
and Range
Mean, Median and Mode
Skewness and Kurtosis
Variance and Standard Deviation
Standard Error of the Mean and
Confidence Intervals
Finite Population Correction
Confidence Intervals with Small
Sample Sizes
Degrees of Freedom
Summary of Formulas for Descriptive
Statistics
V. Sample Size
Estimation
Determine Sample
Size for Means
Determine Sample Size for Percents
Finite Population Correction for
Situations where the Sample Size
Exceeds 10% of the Populations Size
VI. Chi-Square
Statistic and Contingency Table Analysis
One-Way Chi-Square
Two-Way Chi-Square
VII. Tests for
Percents
Establish
Confidence Intervals Around a Percent
T-Test Between Percents (Proportions)
Examples that Would Use a One-Sample
Test
Examples that Would Use a Two-Sample
Test
Using Percentages in Formulas
Compare Percents Drawn from One
Sample
Compare Percents Drawn from Two
Samples
VIII. Tests for
Means
Compare a Sample
Mean to a Known Population Mean
t-Test to Compare a Sample Mean to a
Population Mean
Matched Pairs t-Test to Compare Means
Independent Groups t-Test to Compare
Means
IX. Analysis of
Variance
Fixed and Random
Factors
The F-Ratio
Between and Within Groups Variability
Examples of One-Factor Designs
Example of a Multi-Factor Design
Interaction Effects in Multi-Factor
Designs
ANOVA Table for a One-Factor Design
ANOVA Table for a Two-Factor Design
Post-hoc Tests
X. Correlation
and Regression
Spearman's
Rank-Difference Correlation
Coefficient
Pearson's Product-Moment Correlation
Coefficient
Simple Linear Regression
Curve Fitting and Robust Regression
Correlation and Simple Regression
Formulas
XI. Multiple
Regression
Coefficient of
Multiple Determination (r-squared)
Overall F-Test
Regression Coefficients
F-Test for the Significance of An
Independent Variable
Partial Correlation Matrix
Residual Analysis
Stepwise Method
Missing Data
Multicollinearity
Dummy variables
Probit & Logistic Regression
XII.
Forecasting Overview
Genius Forecasting
Trend Extrapolation
Consensus Methods
Simulation Methods
Cross-Impact Matrix Method
Scenario
Decision Trees
Combining Forecasts
Difficulties in Forecasting
Technology
Defining a Useful Forecast
Do Forecasts Create the Future?
The Ethics of Forecasting
How to Order Survival Statistics
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