Links
Description
This is a full quarter course that teaches the basics of image processing, statistics, and machine learning using Bioconductor. It consists of an RStudio.cloud workspace and online lectures.
Learning Objectives
- Learn and execute the basic steps of image analysis in R/Bioconductor.
- Assess whether image processing algorithms are working correctly.
- Understand basic spatial statistics and how to assess null models of spatial data.
- Execute and Interpret basic spatial statistics on data that are involved with fluoresence microscopy analysis.
Citation
BibTeX citation:
@online{laderas2020,
author = {Laderas, Ted and Laderas, Ted},
title = {NEUS 643: {Stats} for {Neuroscientists}},
date = {2020-04-01},
url = {https://laderast.github.io/edu/2020-04-01-neus-643-stats-for-neuroscientists/},
langid = {en}
}
For attribution, please cite this work as:
Laderas, Ted, and Ted Laderas. 2020. “NEUS 643: Stats for
Neuroscientists.” April 1, 2020. https://laderast.github.io/edu/2020-04-01-neus-643-stats-for-neuroscientists/.