Biomedical Statistics Course ANAT 597 Examination Two - Due Monday May 10.

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Examination Two Consists of Four Projects

Project One - Central Limit Theorm and Confidence Intervals

• Draw on information from chapters of our textbook with emphasis on chapter 7.
• What is the difference between standard deviation and standard error?
• The dataset(s) can be from your laboratory, from a public repository, or you can make it up.
• Provide R scripts used to describe the sample(s).
  • Provide a printed table.
  • Provide a printed graphic (bar, line, etc).
• Provide R scripts used to test the null hypothesis.
  • Is the null rejected at the .05 level?

Project Two - Hypothesis Testing

• Draw on information from chapters of our textbook with emphasis on chapters 9-10.
• The dataset(s) can be from your laboratory, from a public repository, or you can make it up.
• Provide R scripts used to describe the sample(s).
  • Provide a printed table.
  • Provide a printed graphic (line, histogram, etc).
• Provide R scripts used to test the null hypothesis.
  • Is the null rejected at the .05 level?
  • T-test - no more than two groups. Can be independent or dependent.

Project Three - Linear Regression

• Draw on information from chapters of our textbook with emphasis on chapters 12.
• The dataset(s) can be from your laboratory, from a public repository, or you can make it up.
• Pearson r.
• Provide R scripts used to describe the sample(s).
  • Provide a printed table.
  • Provide a printed graphic (line, histogram, etc).
• Provide R scripts used to test the null hypothesis.
  • Is the null rejected at the .05 level?
  • Analysis of Variance - F score.

Project Four - ANOVA

• Draw on information from chapters of our textbook with emphasis on chapter 13.
• The dataset(s) can be from your laboratory, from a public repository, or you can make it up.
• Sums of squares - within, between, total
• Provide R scripts used to describe the sample(s).
  • Provide a printed table.
  • Provide a printed graphic (line, histogram, etc).
• Provide R scripts used to test the null hypothesis.
  • Is the null rejected at the .05 level?
  • Fisher F ratio.
  • Analysis of Variance - F score.

Suggestions for Each Project

• Discuss these projects with anyone including each other and/or your PI; or work alone.
  • You could use real data from you laboratory to compare two conditions from a much larger design.
  • Please test the sample for assumptions of variance. This can be easily done in R.
• Treat this is an opportunity to "dry run" a sample of your dissertation data and design (no more than two groups).
• Please do not use the same datasets among you.
• The outline of your projects can essentially follow the outline of the book (below) as relevant.

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