Draw on information from each of the first 6 chapters of our textbook.
The dataset(s) can be from your laboratory, from a public repository, or you can make it up.
The dataset needs to satisfy the Binomial Distribution.
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?
Binomial test
Project Two - Continuous Random Variables
Draw on information from each of the first 6 chapters of our textbook.
The dataset(s) can be from your laboratory, from a public repository, or you can make it up.
The dataset needs to satisfy the Normal Distribution.
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.
Suggestions for Each Project
Restrict each project to one or two groups. Do not plan on doing an ANOVA. For the continuous random variable project you can do a one-group (test an outlier) or two-group t-test with independent or dependent data.
Do not use a large sample size unless you are working with something meaningful. Do not spend excessive time at the keyboard with data entry. In fact, import existing data; or manually type it in; either way.
Discuss these projects with anyone including each other and/or your PI; or work alone.
Although two group designs are rare in laboratory research; a t-test can be used as a post hoc test. Thus, 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.
Scheduled Lectures and Laboratories
Lecture 1. Sampling and Data, Pages 1-66. March 12
Course Description. The Biomedical Statistics ANAT 597 provides the student with a foundational knowledge of basic statistics. This foundation of knowledge enables to the student to adapt to the statistical requirements of their specific research. In addition, this course provides instruction for using R/RStudio to perform statistical analysis and data graphics display. A coordinated combination of lecture topics and laboratory exercises address descriptive, population, and non-parametric statistics.
Examinations. The are two examinations; a mid-term and a final. Each examination is worth 100 points; 50% of 200 total points available for the course. Essay style questions are crafted from lecture topics and laboratory exercises. Each examination is two hours long.
Attendance. Recommended. Pending the individual's assessment for the merit of attendance in their particular case. It may become awkward if the two examinations are not attended.
Statistics software: R and RStudio. Please install R/RStudio on the personal computer that you routinely bring to class. We will be using R/RStudio at the most basic level. R/Rstudio Desktop is free and is compatible with Windows, MAC, and Linux. R must be installed before installing RStudio. RStudio is a computer desktop application that facilitates access to the functions of R.
Install R Base System for your operating system from the following link (There is no need to install source code). https://cran.rstudio.com/