This course provides an introduction to the statistical theory of sampling, parameter estimation and hypothesis testing, covering the following topics:
- Random variables
- Discrete and continuous probability distributions
- Sampling distributions
- Sampling methods
- Confidence intervals
- Hypothesis testing
We will be working with jupyter notebooks. The easiest way to access jupyter is via the Anaconda platform. Please install Anaconda from https://www.anaconda.com in advance of the workshop.
NB no knowledge of programming is required for this workshop.
Download this repository to your computer as a ZIP file and unpack it.
Open JupyterLab (within Anaconda) and navigate to the unpacked directory to work with the .ipynb examples.
Alternatively, you can run the notebooks online using Binder:
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This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.