In this course you will learn to critically evaluate and put into daily use and practice those techniques (e.g., regression analysis, principles of experimental design, analysis of variance, analysis of covariance and others) that researchers need on a routine basis. You will be able to use statistical software that is available and to draw valid interpretations from your analyses. You will learn when to use one method versus another, the limitations to each method's use, how to diagnose situations where a particular assumption has not been met, and how to remedy those situations. And you will learn to accurately and effectively communicate about the quantitative analyses you choose to perform on your data.
Students will be able to critically evaluate their literature with respect to study design, data analysis strategies and the subsequent data analysis.
Students will be able to:
- Identify the intended and actual scope of inference.
- Identify the use and purpose of randomization, replication, sampling, control of variation and representation in scientific research.
Students will be able to design their own data analysis strategy and carry it out in SAS. They will:
- Understand and develop statistical models for data analysis problems.
- Develop strategies for data analysis based on the study design from which the data were obtained.
- Carry out accurate statistical data analysis.
- Write data analysis programs in SAS.
- Know how to use the on-line help within SASto investigate how to program specific tasks in SAS.
- Acquire knowledge of basic statistical analyses as demonstrated by their ability to carry out a variety of statistical analyses as:
1) Random effects in statistical models
2) Power and sample size calculations
3) Model selection
4) Linear models with different sized experimental units in one analysis
5) Comparison of regression lines
6)Determination of influence and effect of unusual data points
Students will demonstrate effective verbal and written communication of statistical concepts and scientific data analysis as demonstrated through a weekly laboratory report and a final project.
We emphasize clarity and accuracy in oral and written communication in this class. Since scientists will learn about your results from your writing, accurate statements are necessary. But writing about statistics and study design can be confusing because of the jargon and because words have more than one meaning. We give you opportunities to practice writing about what you did.