I. The Basics

Basic Types of Research Designs
Goal Definition
Research Questions, Hypotheses, and Null Hypotheses
One-Tailed and Two-Tailed Significance Tests
Procedure Used to Test for Significance
Bonferroni's Theorem
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
Notification of a Cutoff Date
Reply Envelopes and Postage
The Outgoing Envelope and Postage
"Don't Know", "Undecided", and "Neutral" Response
Question Wording

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

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
Dummy variables
Probit & Logistic Regression

XII. Forecasting Overview

Genius Forecasting
Trend Extrapolation
Consensus Methods
Simulation Methods
Cross-Impact Matrix Method
Decision Trees
Combining Forecasts
Difficulties in Forecasting Technology
Defining a Useful Forecast
Do Forecasts Create the Future?
The Ethics of Forecasting

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