# Bio 5075 Fall 2020 Syllabus

### Live Zoom sessions are **Mondays from 2:30 to 4:00 pm. Zoom link is available from the course site in Canvas or from the instructors upon request.**

### Office hours are by appointment. To schedule a time to meet, email the TAs and instructors at: **bio5075-admin@lists.genetics.wustl.edu**

### Instructors: Zach Pincus and Mike White

### Teaching Assistants: Aidan Schneider, Yawei Wu

**IMPORTANT:** Before the first class, ensure that you have a working installation of Jupyter notebook. Follow these instructions.

### If you have trouble completing the installation instructions, contact one of the instructors at **bio5075-admin@lists.genetics.wustl.edu **and we will help you.

### For any questions, email the course admins at: **bio5075-admin@lists.genetics.wustl.edu**

**HOMEWORK:**

### Weekly homework is due by the end of the day on **Wednesdays**. Late homework will penalized 5% and any homework not submitted within two weeks of the due date will be given no credit.

**SCHEDULE:**

**2020-09-14**

Lecture 0 (Computation): Introduction to Jupyter and Python

- Course format
- Introduction to Jupyter Notebook

**2020-09-21**

Lecture 1 (Computation): Python Loops and Variables

- Variables
- Lists
- Flow control: FOR loops

**2020-09-28**

Lecture 2 (Computation): Dictionaries and Conditionals

- Dictionaries
- Flow control: conditional statements
- Coding strategies

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**2020-10-05**

Lecture 3 (Computation): More lists, Reading Files, Functions

- Functions
- File input/output
- List comprehensions and manipulations

**2020-10-12**

**Lecture 4 (Statistics): Summarizing Numbers**

- Single number summaries: mean, median, mode
- Two numbers: variance and standard deviation
- Dot plots and histograms
- Distributions

**2020-10-19 Lecture 5 (Statistics): Basic Probability**

- Intuitive probability estimation from histograms
- Basic theory and notation
- How probabilities combine: “and” and “or”
- Independence and conditional probability
- Counting successes and failures

**2020-10-26**

**Lecture 6 (Statistics): Simulation and Hypothesis Testing (I)**

- Why simulate?
- Hypothesis testing and the null distribution
- What p-values are and are not
- Recent controversies in the use of p-values

**2020-11-02**

Lecture 7 (Computation): Compound data structures, Plots

- Lists of lists, dictionaries of lists, etc.
- Matplotlib

**2020-11-09**

**Lecture 8 (Computation): Numpy arrays**

- Numpy arrays vs lists

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**2020-11-16**

**Lecture 9 (Computation): Pandas, Bioinformatics**

- Pandas dataframes
- IO

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**2020-11-23**

**Lecture 10 (Statistics): Simulation and Hypothesis Testing (II)**

- Permutation testing
- Sampling from a population
- Bootstrap confidence intervals
- Bootstrap hypothesis testing

**2020-11-30**

Lecture 11 (Statistics): Power Analysis, Experimental Design, and Parametric Statistics I

- Statistical Power
- Paired tests
- The standard error and the t-test
- ANOVA

**2020-12-07**

Lecture 12 (Statistics): Power Analysis, Experimental Design, and Parametric Statistics II

- Chi squared tests

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**FINAL HOMEWORK DUE Tuesday, December 15.**