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

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.
Topic revision: r3 - 04 Mar 2021, LorenEvey
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