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Teaching & Academics Science Python

Biostatistics Fundamentals using Python

Learn how easy it is to use Python to do your biostatistical analysis
Bestseller
Rating: 4.4 out of 54.4 (100 ratings)
529 students
Created by Juan Klopper
Last updated 5/2020
English
English [Auto]
30-Day Money-Back Guarantee

What you'll learn

  • After completing this course, students will be able to use Python to do their own biostatistical analysis
Curated for the Udemy for Business collection

Requirements

  • Students should have access to a computer with an internet connection. A basic understanding of statistics is assumed.

Description

This course empowers you to do your own biostatistical analysis.  Whether you are a healthcare professional, scientist, or just someone interested in supercharging their research career, the time to learn how to use a modern computer language to do you own analysis, has arrived.

Python is becoming the de facto standard in data analysis.  It is a free to use, powerful programming language.  With the minimum of effort, you will soon be able to do all you own analysis, create beautiful plots, and deliver your reports or publish your research with confidence and pride.

Who this course is for:

  • Any scientist, healthcare worker, or person interested in doing their own biostatistics.

Course content

13 sections • 59 lectures • 5h 51m total length

  • Preview00:44
  • Motivation
    00:47
  • Why choose python?
    00:37

  • Preview00:37
  • Installing python
    03:41
  • Jupyter notebook
    05:53
  • Shutting down Jupyter
    02:00
  • Introducing Google Colaboratory
    07:33
  • Preview04:31

  • Doing simple arithmetic
    14:14

  • Preview00:12
  • Collections 01 - Python lists
    13:36
  • Collections 02 - Ranges
    05:55
  • Collections 03 - Dictionaries
    08:18

  • Preview00:31
  • Working with data 01 - Importing external data
    10:26
  • Working with data 02 - Accessing the imported data
    10:59
  • Preview00:23
  • Working with data 03 - Creating random data
    09:17
  • Working with data 04 - Creating a DataFrame with simulated random data
    09:38
  • Working with data 05 - Cleaning up data
    12:23
  • Working with data 06 - More cleaning up
    07:07

  • Preview00:39
  • Descriptive statistics 01 - Measure of central tendency
    10:21
  • Descriptive statistics 02 - Measures of dispersion
    08:26

  • Preview00:30
  • Preview21:04
  • Data visualization 02 - Scatter plots continued
    07:31
  • Data visualization 03 - Box plots
    05:25
  • Data visualization 04 - Histograms
    09:00
  • Data visualization 05 - Dot plots
    06:24
  • Data visualization 06 - Bar charts
    04:48
  • Preview00:41
  • Data visualization - Plotly Express Part 1
    13:46
  • Data visualization - Plotly Express Part 2
    09:06

  • Preview00:30
  • Preview13:52
  • Assumptions for the use of parametric tests 02
    05:35
  • Assumptions for the use of parametric tests 03 - Homogeneity of variance
    02:22
  • Assumptions for the use of parametric tests 04 - Outliers
    05:03

  • Preview00:23
  • Correlations 01 - Univariate correlation
    11:01
  • Correlations 02 - Multivariate correlation
    03:48
  • Preview00:17
  • Linear regression 02
    06:07
  • Linear regression 03
    11:02

  • Preview00:19
  • Comparing means
    08:02

Instructor

Juan Klopper
Head of Postgraduate Research at the University of Cape Town
Juan Klopper
  • 4.4 Instructor Rating
  • 355 Reviews
  • 1,598 Students
  • 4 Courses

I am a Senior Lecturer in Surgery and the Head of both Postgraduate Surgical Research and Surgical Education at the University of Cape Town, South Africa.   My academic interests extend to online education and I am the recipient of the Open Education Consortium Educator of the Year Award in 2014.  My course on Healthcare Statistics is also the first course from a University in Africa on the Coursera massive open online course platform.

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