Health Data Analysis, HDA - I: Introduction to Statistics with R

Learning objectives

To provide a hands-on skill to graduates in any discipline, researchers, and academics from local and abroad. After successful completion of this short course, the participant should be able to manage, analyze their research data, present using suitable graphical techniques, and interpret the results. The teaching will be mostly practical exercise and assignment oriented. Moreover, the participant will be capable to conduct necessary data analysis for the research article. This is the first course in a series of courses on health data analysis using R.

Course Facilitators

Time and Venue

October 10-14, 2020; 18:30-21:30 Bangladesh standard time.

Delivery mode: Online (zoom)

Course fee

1. Professionals: 2990 BDT per participant;
2. Student/Fresh graduate: up to 50% scholarship;
3. International: $39;
4. Group participants (3 or more): 20% discount.

Course outline

Day 1: October 10, Saturday; Time – 18:30-21:30

1. Introduction to Statistics, Getting inside of my dataset,
2. Basics of R and RStudio, Installing and loading packages, googling R,
3. Data structures in R,
4. My first code in R,
5. Take-home assignment.

Day 2: October 11, Sunday; Time – 18:30-21:30

1. Assessment and review,
2. Describing data using summary statistics and plots,
3. Measuring association: correlation and regression,
4. Data manipulation in R,
5. Correlation and regression,
6. Take-home assignment.

Day 3: October 12, Monday; Time – 18:30-21:30

1. Assessment and review,
2. Statistical hypothesis testing, the idea and the nuts and bolts,
3. Common statistical tests,
4. Conducting hypothesis testing for mean, correlation and regression in R,
5. Interpreting the R-output,
6. Take-home assignment.

Day 4: October 13, Tuesday; Time – 18:30-21:30

1. Assessment and review,
2. Odds ratio and Logistic regression,
3. Odds ratio from the 2-by-2 table in R,
4. Conducting logistic regression in R and interpreting the output,
5. Writing your own function in R,
6. Take-home assignment.

Day 5: October 14, Wednesday; Time – 18:30-21:30

1. Assessment and review,
2. Advance graphics in R, ggplot2,
3. Practicing ggplot2,
4. Creating collaborative projects with binary data lab.