Mathematica for healthcare and life science statistics
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Mathematica for healthcare and life science statistics

Learn an easy, yet powerful computer language and how to use it to do your own statistical analysis.
4.6 (8 ratings)
Instead of using a simple lifetime average, Udemy calculates a course's star rating by considering a number of different factors such as the number of ratings, the age of ratings, and the likelihood of fraudulent ratings.
51 students enrolled
Created by Dr Juan Klopper
Last updated 8/2017
English
Current price: $10 Original price: $45 Discount: 78% off
5 hours left at this price!
30-Day Money-Back Guarantee
Includes:
  • 4.5 hours on-demand video
  • 28 Supplemental Resources
  • Full lifetime access
  • Access on mobile and TV
  • Certificate of Completion
What Will I Learn?
  • Understand the Wolfram computer language
  • Import your own data into Mathematica
  • Do statistical analysis of the data
  • Create plots and graphs from your data
View Curriculum
Requirements
  • A basic understanding of statistical terms.
Description

This course is for anyone in the healthcare and life sciences interested in doing their own statistical analysis.  You will learn an easy to use, powerful computer language and how to use it to do statistical analysis.  The introduction shows you how to get a copy of Mathematica or how to use the free version in the cloud.  The Wolfram company also provides complimentary access to Wolfram|One for all students who take this course.  More information is available in the BONUS MATERIAL video lecture.

Although the course assumes some knowledge of statistical concepts, it does supply enough information on the basics of statistics, so that most learners will find it a useful resource enough resource to learn these concepts, over and above learning how to write code to do the actual analysis.

The course is made up of clearly defined sections, each with its own set of video lectures.  The first video in each section is accompanied by notebook files and, where required, a spreadsheet data file.  The notebook in each section marked Recording... is a copy of the notebook that I use in the video lectures.  The other notebook file contains much more description of both the code and the statitics.  You can use this as an additional study resource as you learn how to use Mathematica.

The course starts with a gentle introduction to using Mathematica by showing you how to perform simple calculations. From here it progresses through descriptive statistics, plotting and charting, the creation of simulated data and the importation of existing data.  

Before too long you will be able to do advanced statistical tests such as parametric and nonparametric tests and even survival analysis.  All with a few short lines of code.

Get ready to understand and do your own statistics.

Who is the target audience?
  • Healthcare and life science students and professionals interested in the statistical analysis of their own data.
Compare to Other Statistics Courses
Curriculum For This Course
66 Lectures
04:39:14
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Course orientation
4 Lectures 17:58

In this video I tell you about how to get hold of a copy of Mathematica and how to use it free of charge, in the cloud.

Getting Mathematica
02:53

In this video I show you around the user interface of the desktop version of Mathematica.  The coding environment is the notebook.  It allows for the entry of titles, subtitles, text, paragraphs, and computer code.

Desktop Mathematica
08:35

The cloud version of Mathematica is free to use.  It offers the same notebook environment as the desktop version.

Mathematica in the cloud
04:22
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Mathematica, the fancy calculator
3 Lectures 11:38

In this first proper look at Mathematica we complete a few simple arithmetical calculations.

Preview 06:08

Now that we know how to do simple arithmetic, we take a look at calculating powers.  We also consider the order of arithmetical operations and how to manually change the usual order.  Finally, we calculate the mean or average of a set of numerical values.

02 Powers, order, and the simple mean
04:11
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Collections
7 Lectures 26:52

Introduction to this section.

Preview 00:47

In this video we take a look at creating a list of elements.

Preview 05:42

Lists can contain other lists as elements.  This video will show you how these are used to build up matrices.

02 Nested lists and matrices
02:52

Instead of typing in each element of a list, you can use a formula to create the elements of a list for you.

03 List comprehension
06:41

Once you have a list or lists, you might want to access only certain of the elements.  Each element in a list has an address, which is what allows us to make this selection.

04 Accessing elements of a list
05:40

Lists come in various shapes and sizes.  This video will show you how to calculate the number of elements in a list.

05 The length of a list
02:37

It is straight forward top add elements to a list that has already been created.  This video also shows you how to extract all the elements of nested lists into one single list.

06 Appending to or flattening a list
02:33
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Descriptive statistics
4 Lectures 14:00

Measures of central tendency calculate a single value to represent a list of values.  These include the mean or average, the median, and the mode.

01 Measures of central tendency
04:30

Measures of dispersion give us an idea of the spread of the data.  These include the standard deviation, the range, the interquartile range and various quartiles and percentiles.

02 Measures of dispersion
03:42

It can be tedious to calculate each individual measure of central tendency and dispersion.  This video will show you how to create a short Mathematica function.  You can use it to calculate all of the descriptive statistics for a list of values in one go.

03 Functions
05:25
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Random variables
5 Lectures 18:32

This video shows you how to create random integers and random real numbers.

Preview 05:49

Introduction to this section.

Preview 00:44

Mathematica can also choose random categorical variables from a list.

02 Random categorical variables
05:09

In this video we take a closer look at the normal distribution.

03 The normal distribution
02:54

Now that you know how to create random values, this video shows you how to select values at random that follow a specified distribution, i.e. the normal distribution, given a mean and a standard deviation.

04 Random values following a distribution
03:56
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Confidence intervals
3 Lectures 09:38

Introduction to this section.

Preview 00:25

In this video we import the HypothesisTesting package into Mathematica and use it to calculate the confidence interval around the mean of a list of values.

01 Confidence intervals around the mean
06:01

02 Confidence intervals around the difference in means and variances
03:12
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Parametric tests
8 Lectures 40:45

Introduction to this section.

Preview 00:16

In this first video we create lists of values to use in our parametric tests.

01 Creating lists
02:54

In this vodeo we calculate a p-value for the comparison of a mean for the list of values to a given mean.

02 One sample t-test
03:45

In this video we use the famous Student's t-test to calculate the p-value for the difference in means between two lists of values.

03 The t-test
10:25

If the two lists of values are not independent, i.e. they come from the same individual such as before and after an intervention, we need a different version of the t-test.

04 Paired-sample t-test
01:14

One-way analysis of variance allows us to compare the means of three or more lists of values.

05 Analysis of variance
08:58

Instead of calculating the p-value for ANOVA manually, we can import and use the ANOVA package.

06 More on ANOVA
08:12

In this video we compare pairs of numerical values for two variables using simple linear regression or the strength of the correlation between two variables.

07 Linear regression
05:01
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Working with data
8 Lectures 38:23

Introduction to this section.

Preview 00:31

Until now we have created our own lists of values.  More commonly, data is already stored in spreadsheets.  In this video I show you the structure of a dataset in Mathematica by manually creating one.

01 Introduction
05:16

In this video we take a look at specifying the directory or folder on your computer where the spreadsheet file resides so as to make it easier for Mathematica to import the file.

If you are using the cloud version, simply upload the spreadsheet file into the Home directory (where your notebook file should also be kept).

02 Specifying the directory and importing a file.
04:41

Just as we references elements of a list (collections), we can also access data point values in a data file.

03 Referencing dataset values
05:46

At times we only want to select a subgroup of patients or subjects to use in our analysis.  We can do this by creating a rule (or recipe) that will only select these cases.

04 Selecting rows based on rules
05:32

We can calculate simple descriptive statistics on data in our dataset, similar to the way in which we calculated it for lists of values.

05 Simple descriptive statistics
05:14

Instead of simply selecting a subset of subjects based on a rule, we can also group our dataset into subgroups for easier calculations.

06 Using GroupBy to select data
06:01

For really complex calculations we can create standalone sub-datasets and even extract lists from a dataset.  This is a very useful way of working with the data.

07 Creating sub datasets and lists
05:22
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Plotting
8 Lectures 33:04

Introduction to this section.

Preview 00:21

Plotting or charting is one of the most powerful ways of getting to know and understand your data.  In this first video, we create some data that we will plot.

01 Creating simulated data
08:00

A list plot is used to plot pairs of values, i.e. one on the x-axis and one on the y-axis.  A point is created where they meet.  This first video looks at plotting the values in a list one-by-one.

02 The list plot
03:43

The bubble chart adds a third dimension (another value to the pairs) that is plotted as the size of each point.

03 The bubble chart
01:56

A histogram plot the frequency of occurrence of numerical values in interval ranges.

04 The histogram
06:59

A smooth histogram creates a smooth curve from a kernel density estimate of the frequency distribution of a list of values.  A 3D histogram plots the frequency of the combination of two numerical variables.

05 The smooth and 3D histograms
02:51

The box-and-whisker plot is one of the most common plots in healthcare analysis.  It charts the middle two quartiles and median of a list of values, together with any outliers.

06 The box-and-whisker cahrt
03:32

A bar chart shows the counts of categorical variables.  A pie chart does the same, but represents the whole as a full circle, with proportional slices that make of the frequency of the categorical variable.

07 The bar and pie charts
05:42
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More about parametric tests
6 Lectures 28:49

More than one independent variable can be used to compare three or more numerical variables.  In this video we look at two-factor ANOVA.

01 Two-way ANOVA
06:22

In this video we look at three independent factor ANOVA.

02 Three way ANOVA
03:00

We take a closer look at linear regression in this video.

03 Fitting a curve
09:45

We take a closer look at linear regression in this video.

04 Simple linear regression
04:10

The values that we compare need not only come in pairs, but also in triplets and even more.

05 Multiple linear regression
05:05
3 More Sections
About the Instructor
Dr Juan Klopper
4.2 Average rating
15 Reviews
76 Students
3 Courses
Specialist Surgeon

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 massive open online Coursera platform.