This course has a singular and clear aim, to empower you to do statistical tests, ready for incorporation into your dissertations, research papers, and presentations. The ability to summarize data, create plots and charts, and to do the tests that you commonly see in the literature is a powerful skill indeed. Not only will it further your career, but it will put you in the position to contribute to the advancement of humanity though scientific research.
We live in a wonderful age with great tools at our disposal, ready to achieve this goal. None are quite as easy to learn, yet as powerful to use, as the Wolfram Language. Knowledge is literally built into the language. With its well-structured and consistent approach to creating code, you will become an expert in no time.
This course follows the modern trend of learning statistical analysis through the use of a computer language. It requires no prior knowledge of coding. An exciting journey awaits.
Doing Clinical Research: Biostatistics with the Wolfram Language
von
University of Cape Town
30 Angemeldet
Lehrplan - Was Sie in diesem Kurs lernen werden
Woche
12 Stunden zum Abschließen
Week 1
This is the first week, welcoming you to the course. It establishes the aims of the course, states the basic assumptions, motivates for the use of the Wolfram Language, gives an overview, and describes the process of procuring the software that you will use in the course. All in all, it will provide you with all the information for successfully completing this course and gaining a remarkable new skill, the ability to do statistical analysis using the Wolfram Language.Through watching the video material, you will learn that there are two software products from which you can choose to complete the course and continue to use long after you are done. The first is the absolutely free version, which is software as a service, meaning it runs in any web browser. The second is desktop desktop version. If you work at, or are students at, an institution with a site licence, you will be able to get the software for free. There is also the option to purchase your own licence.
13 Videos (Gesamt 53 min), 8 Lektüren
13 Videos
Welcome6m
The Klopper Research Group1m
Assumptions1m
Learning a computer language1m
Why the Wolfram language?7m
Getting Mathematica5m
The Wolfram Cloud1m
The Wolfram Programming Lab8m
Free-form input and Wolfram Alpha in the Cloud3m
Mathematica27
Free-form input and Wolfram Alpha in the desktop7m
Help and documentation3m
Assignment notebooks4m
8 Lektüren
How this Course Works10m
Welcome to Module 110m
Meet the Course Instructor10m
Module 1 Notebook10m
Welcome to Module 210m
Welcome to Module 310m
Module 3 Notebook10m
Module 3 Exercise10m
Woche
23 Stunden zum Abschließen
Week 2
Welcome to week two, which consists of modules/chapters four to six. Now that you know a little bit about the Wolfram Language and its different coding environments, it is time to do some actual coding. The week will start off with module/chapter four, a demonstration of a completed project, though. It is just a little teaser to motivate you to push through and finish the course, by showcasing what you will be able to do at the end. Since statistical tests are all about math (don't worry, this course is not about the math), in module/chapter five we are going to learn to code by doing simple arithmetic. That is addition, subtraction, multiplication, and so on. Once you have realized just how simple these tasks are, you will be introduced to the way in which data is stored in a computer language in module/chapter six. This is the stepping stone required to bringing in your own data, ready for the analyses in weeks three and four.
20 Videos (Gesamt 100 min), 7 Lektüren, 1 Quiz
20 Videos
Simulated data demonstration - part 11m
Simulated data demonstration - part 27m
Simple arithmetic30
Addition and subtraction5m
Multiplication and division9m
Powers5m
Arithmetical order2m
Calculating a mean5m
Working with data40
Lists part 17m
Lists part 23m
Tables7m
Index10m
Datasets9m
Selecting6m
Dataset functions3m
Creating lists from datasets2m
Spreadsheets6m
Spreadsheets in the cloud4m
7 Lektüren
Welcome to Module 410m
Module 4 Notebook10m
Welcome to Module 510m
Module 5 Exercise10m
Welcome to Module 610m
Module 6 Notebook10m
Module 6 Exercise10m
1 praktische Übung
Modules 1 to 5
Woche
33 Stunden zum Abschließen
Week 3
Now that you can write some code and import your data, the time has come to start analyzing it, which we will do this week in modules seven to nine. The two most important steps to understand the message hidden in data, is to summarize and visualize it. Descriptive statistics turn rows and columns of data into something that we as humans can understand. By summarizing values and replacing them with single values, we start to get an idea of what our analyses might show.Visualizing the data is an even better way of getting to grips with data. Box-and-whisker plots, scatter plots, bar charts, and the like are wonderful ways to augment your understanding of the data.The Wolfram Language makes summary statistics easy, but is really shines when creating plots. There is almost no limits to customizing plots. No matter what your project requirements, you will learn to create plots that work for you.
19 Videos (Gesamt 102 min), 9 Lektüren, 1 Quiz
19 Videos
Descriptive statistics49
Data import for descriptive statistics5m
Creating lists for descriptive statistics8m
Point estimates10m
Measures of dispersion6m
Data Visualization39
Data import for visualization2m
Scatter plots10m
Box plots3m
Histograms5m
Bar and pie charts6m
Distributions1m
Probability8m
PDF and CDF3m
Discrete distributions7m
Continuous distributions6m
Sampling distributions6m
Simulated data6m
9 Lektüren
Welcome to Module 710m
Module 7 Notebook10m
Module 7 Exercise10m
Welcome to Module 810m
Module 8 Notebook10m
Module 8 Exercise10m
Welcome to Module 910m
Module 9 Notebook10m
Module 9 Exercise10m
1 praktische Übung
Modules 6 to 9
Woche
43 Stunden zum Abschließen
Week 4
This is the week that you have been waiting for, the final week which covers modules ten to thirteen. From Student's t test to analysis of variance to chi-squared tests. All the common tests are here.The week culminates in running through the demonstration research project that you saw at the beginning of week two. It brings together all the skills that you have acquired during the course.Not content with just working through the demonstration project, you will also have the opportunity to create your own computational essay, given a dataset that you can download.
17 Videos (Gesamt 68 min), 12 Lektüren, 2 Quiz
17 Videos
Linear regression36
Importing data4m
Descriptive statistics and visualization3m
Linear model5m
Comparing means17
Data import3m
Comparing two means8m
Comparing more than two means7m
Comparing categorical variables21
Contingency tables7m
Chi-squared test3m
Creating a Computational Essay47
Data import7m
Main research question6m
Secondary research questions7m
The end20
12 Lektüren
Welcome to Module 1010m
Module 10 Notebook10m
Module 10 Exercise10m
Welcome to Module 1110m
Module 11 Notebook10m
Module 11 Exercise10m
Welcome to Module 1210m
Module 12 Notebook10m
Module 12 Exercise10m
Welcome to Module 1310m
Module 13 Notebook10m
Final Exam Instructions10m
2 praktische Übungen
Modules 10 to 13
Final
Dozent
Juan H Klopper
DrDepartment of Surgery
Über University of Cape Town
The University of Cape Town is the oldest university in South Africa and is one of the leading research universities on the African continent. UCT has over 25 000 students, of whom 30% are postgraduate students. We offer degrees in six faculties: Commerce, Engineering & the Built Environment, Health Sciences, Humanities, Law, and Science. We pride ourself on our diverse student body, which reflects the many cultures and backgrounds of the region. We welcome international students and are currently home to thousands of international students from over 100 countries. UCT has a tradition of academic excellence that is respected world-wide and is privileged to have more than 30 A-rated researchers on our staff, all of whom are recognised as world leaders in their field. Our aim is to ensure that our research contributes to the public good through sharing knowledge for the benefit of society. Past students include five Nobel Laureates – Max Theiler, Alan Cormack, Sir Aaron Klug, Ralph Bunche and, most recently, J M Coetzee.
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