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Title: Indiana - Comparison of Means

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Title Indiana - Comparison of Means
Contributor/Contact Susan M. Perkins, PhD
Institution Indiana
Acknowledgment Please cite the appropriate contributors/authors/contacts when using or adapting these materials.
Format PDF slides
Attachment Comparison of Means
URL_Web_Link

Type of Course Single Presentation
Level of Course Mid-level
Audience Clinical Researcher
Topics Description Biostatistics Course for Health Care Providers: A Short Course

The objectives of this course are:
* Understand common tests for comparing means
* t-tests for Paired vs Independent groups data
* One-way ANOVA
* Non-parametric methods
* Know when each test is most appropriate
* Understand sample size calculations for two-group problems
Software Program

Datasets

Data

Keywords Choice of Test: Study Design, Distribution, Number of Groups
Student's T-Test: Paired Design
Student's T-Test for Independent Groups
Assumptions: T-Tests
Two-Groups - Non-Normal Data: Paired or Independent
Sample size calculations
Negative results
Choice of sample size depends on: Question, variability, and analysis
Analysis of Variance (ANOVA)
Assumptions for ANOVA: Normality, equal variances, independent observations
Example of ANOVA - CD4 Counts and PTSD in HIV Patients
Multiple Comparison Techniques
See Also

Type of Activity Course Slides
Disclaimer The views expressed within CTSpedia are those of the author and must not be taken to represent policy or guidance on the behalf of any organization or institution with which the author is affiliated.
Topic revision: r3 - 08 Oct 2012 - 14:40:47 - MaryBanach
 

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