Biostatistics (SBE304) - Fall 2019
Teaching Staff
Instructor: Prof. Ayman M. Eldeib
Demonstrator: Eng. Asem Alaa
Lecture Hours
Monday, 2nd slot (+3rd slot each two weeks).
Section Hours
| Section | Day | Time Slot |
|---|---|---|
| 1 | Tuesday | 4th |
| 2 | Wednesday | 4th |
Office Hours
| Day | Time |
|---|---|
| Tuesday | from 4pm to 8pm |
| Wednesday | from 4pm to 8pm |
Feel free to request for additional office hours by sending me an email (asem.a.abdelaziz@eng1.cu.edu.eg)
Course Outline
| Week | Biostatistics & R | Lecture notes | Tutorial notes |
|---|---|---|---|
| 1 | Introduction to R and Probabilities | Lecture 1 | Tutorial 1 |
| 2 | Discrete RVs and Probability Distributions, R (distributions, data manipulation and basic visualization) | Lecture 2 | Tutorial 2 |
| 3 | Continuous RVs and their Probability Distributions, R (continous distributions, high quality visualizations) | Lecture 3 | Tutorial 3 |
| 4 | Revision | Quiz | |
| 5 | Sampling Distributions and Point Estimates | Lecture 4 | Tutorial 4 |
| 6 | Estimation of Statistical Intervals | Lecture 5 | Tutorial 5 |
| 7 | Revision and Project Prototype Submission | Revision Quiz | Project milestone submission |
| 8 | Hypothesis testing & SPSS | Lecture 6 | Tutorial 6 |
- Each week you have to submit homework which consists of:
- A selected problem set (indicated in the tutorial notes)
- A selected R problems (indicated in the tutorial notes)
- In-class demos will be uploaded to this repository: sbme-tutorials/biostatistics-sbe304
Course Project
The main aim of this project is to apply our understanding from this course to solve real world problems. Since statistical techniques are typically data-driven, the project must first consists of data then an idea, for example to make inference about the population from a sample, learning from data to make future predictions, or just statistical modeling of data to give interpretations on how data are generated. Another aim of this project is to encourage the students to improve their profiles quantitatively by adding new programming skills (e.g R) and possibly new research interests to their profiles and qualitatively by considering a personal website with a blog about the project in the grading process.
The details of the class project can be viewed in PDF in this project statement.
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