Class expectations

This will be an inherently difficult class, given the mathematical nature of its content and the disparity in skills among students. However, the course is set such that I assume no basic prior understanding of programs, nor major mathematical skills.

This is an introductory, not advanced, class on stats. In general, I expect that at the end of the class you can design an experiment, collect, handle and analyze your data; oh, and do professional plots. Primarily using R.

Next, I outlined the specific expectations. If you can already meet these expectations, this class then will be too basic for you, and you probably will benefit of a more advanced course. If not, then this class is for you, and I will help you meet this standards.

1. Scientific method

It is expected that when faced with a problem, you can design a robust experiment to solve or identify the given problem.

This includes identifying dependent and independent variables,provide proper treatments and controls, collect data, know about replication, independence, etc.

2. Data manipulation

You will know basic methods to load or create databases in R, plus basic functions to manipulate data, like sorting, filtering, merging, pivoting, etc.

3. Data display

You will know how to do publication quality plots. Basic plots like scatterplot, histogram, boxplot, and maps.

4. Descriptive stats

You will know how to calculate basic metrics of central tendency and variability in your data.

5. Correlation

You will know how to run and interpret the results of a correlation analysis.

6. Regression

You will know how to run and interpret the results of a regression analysis.

7. Hyphothesis testing

You will know how to: State hypotheses,

8. One sample test

Run a one sample test using the Z-Score and the T-score,

9. Two sample test

Run a two sample test using the Z-Score and the T-score,

10. More than two sample test

Run an ANOVA,

Run a post-hoc test,

Test for assumptions (outliers, normality, homogeneity of variances).