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The Analysis of Variance ANOVA |
 Duration : 1.0 day(s) | |
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:: Course SummaryThe focus of this workshop is to present the available tools to compare two groups or more on a continuous or quantitative measurement variable.
Starting with the simplest situation, the Student test or t-test, is covered then increasingly complex cases are discussed: the t-test to compare two related samples, the one-way ANOVA, and ANOVA for several factors and interactions.
Moreover, multiple comparisons techniques are discussed to locate group differences.
Throughout the session, emphasis is put on the conditions of use for each technique, the type of results obtained and their interpretation. A variety of case studies are used to exemplify situations likely to occur in practice, the typical problems and remedial measures.:: Learning ObjectivesUpon completion of this course, participants will be able to:
Determine when the Student test should be used
Determine whether the independent or the paired samples t-test should be used
Know how to assess if the underlying assumptions of the t-test are met
Choose a remedial measure when assumptions are violated
Determine when the ANOVA technique is appropriate to use
Check whether the assumptions underlying ANOVA are met
Understand the notion of interaction and interpret significant ones
Read and interpret an ANOVA table
Use a multiple comparison technique to locate differences detected by ANOVA
Analyze data more quickly and more accurately
Interpret results reliably and with more confidence:: Target AudienceThis session is intended It is also intended for people who work on designed data, survey data, or administrative data. It is also intended for scientists that are comfortable with the design of experiments but need to improve their data analysis of designed experiments skills.:: PrerequisiteThis one-day training session covers the t-test and the analysis of variance (ANOVA) techniques.
Participants should know the essential tools in statistics - descriptive statistics, both numerical (mean, standard deviation, standard error, etc.) and graphical (histogram, box-plot, scatter plot, etc.), and hypothesis testing and confidence intervals.
Potential participants should either have attended the training session Fundamental Tools in Statistics:: Notes and Other InformationThe focus of this course is on data analysis and the interpretation of results rather than on the efficient design of studies and experiments that can be used with the help of techniques covered in this session. If the design is also of interest to you, the two day session entitled Introduction to the Design of Experiments will address these design and analysis issues. | | |
:: Topics Covered
- Statistical Testing for Two Samples
- Completely Randomized Design or Independent Samples
- Principle
- Conditions of Use
- Illustrations
- Paired or Related Samples
- Principle
- Conditions of Use
- Illustrations
- Statistical Analysis of Factorial Designs (More Than Two Samples)
- One-Way Analysis of Variance
- Principle
- Conditions of use
- Illustrations
- Two-Way Unreplicated Analysis of Variance
- Principle
- Conditions of use
- Illustrations
- Two-Way Replicated Analysis of Variance
- The concept of Interaction Between Factors
- Conditions of Use
- Illustrations
- Multi-Way Analysis of Variance
- Multiple Comparisons Techniques to Locate Differences Detected by ANOVA
- Principle of the Techniques
- Overview of the Different Techniques: Fisher's LSD, Tukey, Bonferroni, Dunnett, etc.
- Illustrations
:: Course ContentThis one-day training course discusses the principles underlying the Student test and analysis of variance (ANOVA). The conditions of use and the assumptions of the techniques will be explored and case studies will be used. The main focus of the course is on the interpretation of the results. Participants will learn how to read an analysis of variance table, learn what interactions are, how to detect , interpret and report them. They will learn how to assess if the assumptions underlying the anova technique are met through residual plots and which alternative strategies are available when they are violated. Furthermore, whenever significant differences are detected by anova, participants will learn the principle underlying multiple comparisons techniques used to locate differences. They will get an overwiew of the available techniques, the differences among them, the advantages and drwabacks. Throughout the session emphasis will be put on the interpretation of statistical software output.
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Upcoming Public Sessions |
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| No public session is scheduled yet, contact us if you are interested. |
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Offered Discounts- Register more than 6 weeks before a session date and get a 15% discount (Displayed above if available).
- Register 2 persons or more and get a 10% discount (Applied at checkout).
- Register for 2 sessions or more and get a 10% discount (Applied at checkout).
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Regression on Principal Components and PLS Regression |
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