Last updated: 2020-06-23

Checks: 2 0

Knit directory: MSTPsummerstatistics/

This reproducible R Markdown analysis was created with workflowr (version 1.5.0). The Checks tab describes the reproducibility checks that were applied when the results were created. The Past versions tab lists the development history.

R Markdown file: up-to-date

Great! Since the R Markdown file has been committed to the Git repository, you know the exact version of the code that produced these results.

Repository version: ac9c26c

Great! You are using Git for version control. Tracking code development and connecting the code version to the results is critical for reproducibility. The version displayed above was the version of the Git repository at the time these results were generated.

Note that you need to be careful to ensure that all relevant files for the analysis have been committed to Git prior to generating the results (you can use wflow_publish or wflow_git_commit). workflowr only checks the R Markdown file, but you know if there are other scripts or data files that it depends on. Below is the status of the Git repository when the results were generated: 


Ignored files:
    Ignored:    .DS_Store
    Ignored:    .RData
    Ignored:    .Rhistory
    Ignored:    .Rproj.user/
    Ignored:    analysis/.DS_Store
    Ignored:    analysis/.RData
    Ignored:    analysis/.Rhistory
    Ignored:    data/.DS_Store

Note that any generated files, e.g. HTML, png, CSS, etc., are not included in this status report because it is ok for generated content to have uncommitted changes.

These are the previous versions of the R Markdown and HTML files. If you’ve configured a remote Git repository (see ?wflow_git_remote), click on the hyperlinks in the table below to view them.

File Version Author Date Message
html 61e3892 Anthony Hung 2020-06-23 add cheatsheet links
html 2a37983 Anthony Hung 2020-06-23 Build site.
html a1a0bd4 Anthony Hung 2020-06-23 Build site.
html cdeb6c5 Anthony Hung 2020-06-22 Build site.
html 14c0094 Anthony Hung 2020-06-12 Build site.
html 1378fca Anthony Hung 2020-06-12 Build site.
html 9bb0ed6 Anthony Hung 2020-05-12 Build site.
html 2114e6c Anthony Hung 2020-05-10 Build site.
html 29c91df Anthony Hung 2020-05-10 Build site.
html a6d0787 Anthony Hung 2020-05-09 Build site.
html e18c369 Anthony Hung 2020-05-02 Build site.
html 0e6b6d0 Anthony Hung 2020-04-30 Build site.
html 5cbe42c Anthony Hung 2020-04-23 Build site.
html 4e08935 Anthony Hung 2020-03-30 Build site.
html f15db48 Anthony Hung 2020-03-30 Build site.
html 310d040 Anthony Hung 2020-02-20 Build site.
html e02f5ce Anthony Hung 2020-02-20 add dataviz
html 5a37a3e Anthony Hung 2020-02-14 Build site.
html 96722bd Anthony Hung 2019-08-07 Build site.
html 15ca1f1 Anthony Hung 2019-07-18 Build site.
html a3aa9e0 Anthony Hung 2019-07-18 Build site.
html ceb577e Anthony Hung 2019-07-12 Build site.
html 397882b Anthony Hung 2019-05-30 Build site.
html 6d3e1c8 Anthony Hung 2019-05-28 Build site.
html c117ef1 Anthony Hung 2019-05-28 Build site.
Rmd c3c7b6e Anthony Hung 2019-05-28 Bayesian
html c3c7b6e Anthony Hung 2019-05-28 Bayesian
html b291d24 Anthony Hung 2019-05-24 Build site.
html 4e210d6 Anthony Hung 2019-05-24 Build site.
html c4bdfdc Anthony Hung 2019-05-22 Build site.
html 096760a Anthony Hung 2019-05-19 Build site.
html da98ae8 Anthony Hung 2019-05-18 Build site.
html 2ec7944 Anthony Hung 2019-05-06 Build site.
html 536085f Anthony Hung 2019-05-06 Build site.
html ee75486 Anthony Hung 2019-05-05 Build site.
html 5ea5f30 Anthony Hung 2019-04-30 Build site.
html e0e8156 Anthony Hung 2019-04-30 Build site.
html e746cf5 Anthony Hung 2019-04-29 Build site.
Rmd 133df4a Anthony Hung 2019-04-29 introR
html 133df4a Anthony Hung 2019-04-29 introR
Rmd 3c0adcd Anthony Hung 2019-04-26 add intro to course file

Welcome!

I hope you are all excited for the course! Throughout this quarter we will covering topics in the theory and practical aspects of statistical tests and probabilistic inference. We will also have the time to engage in excercises to apply our knowledge to toy datasets. The course will close off with individual projects in which you work with data generated during your summer rotations using your newfound skills.

Goals

Probability vs Statistics

While the title of this course only mentions statistics, in reality knowledge of probability and statitics go hand-in-hand. Both probability and statistics deal with analyzing the relative frequency of events that are the result of random processes.

From Steven Skiena’s “Calculated Bets” book:

Probability deals with predicting the likelihood of future events, while statistics involves the analysis of the frequency of past events.

Probability theory enables us to find the consequences of a given ideal world, while statistical theory enables us to to measure the extent to which our world is ideal.

We will explore more of both of these fields throughout the course.

Note

Note that we will be able to explore many different topic areas in this course. However, given the limited amount of time we have to spend together, we will not be able to delve very deeply into most topics to the level where you would be able to base your entire thesis work off of what you learn here. We hope to familiarize you with common statistical tools and methods and encourage you to take courses that are dedicated to exploring these topics in more depth should you require them for your thesis project.

Bibliography