The Little Handbook of Statistical Practice
Gerard E. Dallal, Ph.D
Chief, Biostatistics Unit
Jean Mayer USDA Human Nutrition Research Center on Aging
at Tufts University
711 Washington Street
Boston, MA 02111
[email protected]
******IMPORTANT ANNOUNCEMENT !!!******
- *Permissions*
- How to cite these pages
- Introductory remarks and an advisory
- An all-important foundation!
- The basics
- Look At the Data!
- Logarithms
- Summary Statistics
- Probability
- The Normal Distribution
- Outliers
- The Behavior of Sample Means
(orWhy Confidence Intervals Always Seem to be Based On the Normal Distribution)
- Confidence Intervals and Tests of Signficance
- (Confidence Intervals)
- Other Intervals
- Paired Data / Paired Analyzes
- The Ubiquitous Sample Mean!
- What Student Did
- What StudentReallyDid
- Significance Tests
- Prologue
- Significance Tests / Hypothesis Testing
- Significance Tests Simplified
- Student’s t Test for Independent Samples
- P values
- Why P=0. 05?
- A Valuable Lesson
- One-Sided Tests
- Contingency Tables
- (Proportions)
- (Odds)
- (Paired Counts)
- Sample Size Calculations
- Some Underlying Theory & Some Practical Advice
- Controlled Trials
- (Surveys)
- Group Randomized, Multi-level, and Hierarchical Studies
- Nonparametric Statistics
- Simple Linear Regression
- Introduction to Simple Linear Regression
- How to Read the Output From Simple Linear Regression Analyzes
- Correlation and Regression
- Frank Anscombe’s Regression Examples
- Transformations In Linear Regression
- Which fit is better?
- / The Regression Effect The Regression Fallacy
- Comparing Two Measurement Devices: Part I
- Comparing Two Measurement Devices: Part II
- Linear models: Nomenclature
- Multiple Linear Regression
- Introduction to Regression Models
- Student’s t Test for Independent Samples Is A Special Case of Simple Linear Regression
- Introduction to Multiple Linear Regression
- The Most Important Lesson You’ll Ever Learn About Multiple Linear Regression Analyzes
- How to Read the Output From Multiple Linear Regression Analyzes
- The Meaning of Regression Coefficents
- What Does Multiple Regression Look Like?
- What Does Multiple Regression Look Like? (Part 2)
- Why Is a Regression Line Straight?
- Partial Correlation Coefficients
- Which Predictors Are More Important?
- The Extra Sum of Squares Principle
- Simplifying A Multiple Regression Equation
- Which variables go into a multiple regression equation?
- The Mechanics of Categorical Variables With More Than Two Categories
- Interactions In Multiple Regression Models
- Regression Diagnostics
- Analysis of Variance
- Single Factor ANOVA
- How to Read the Output From One-Way Analysis of Variance
- Multiple Comparisons
- Labeling Similar Means After Performing an Analysis of Variance
- Adjusting Results for Other Variables
- Adjusted Means, aka Least Squares Means
- Adjusted Means: Adjusting For Numerical Variables
- Adjusted Means: Adjusting For Categorical Variables
- Which Variables Should We Adjust For?
- Multi-Factor Analysis of Variance
- The Model For Two- Factor Analysis of Variance
- (Pooling Effects)
- Fixed and Random Factors
- Repeated measures analysis of variance
- (Randomized) Complete (Block Designs) *************
- (Crossover Studies)
A good case can be made that the best set of articles about statistical practice written for the practitioner is the series of (Statistics Notes) appearing in the British Medical Journal.
There have been many attempts at online statistics instruction.HyperStatis one of the better ones, not only for the content but also for the additional links.
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August 8, 2007
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