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 through scientific research.
von
Doing Clinical Research: Biostatistics with the Wolfram Language
University of Cape Town
Über diesen Kurs
5,295 kürzliche Aufrufe
Kompetenzen, die Sie erwerben
Learn to use the Wolfram Language to summarize data and create plotsLearn to use the Wolfram Language to do common statistical tests
Zertifikat zur Vorlage
Erhalten Sie nach Abschluss ein Zertifikat
100 % online
Beginnen Sie sofort und lernen Sie in Ihrem eigenen Tempo.
Flexible Fristen
Setzen Sie Fristen gemäß Ihrem Zeitplan zurück.
Stufe „Anfänger“
Ca. 10 Stunden zum Abschließen
Empfohlen: Four weeks of study, at approximately five hours per week.
Englisch
Untertitel: Englisch
Lehrplan - Was Sie in diesem Kurs lernen werden
2 Stunden zum Abschließen
Week 1
This first week establishes the aims of the course and motivation for using the Wolfram Language. We aim to support you in gaining a remarkable new set of skills for doing statistical analysis that you can continue to use long after you complete the course. We will also describe the process of procuring the software that you will use in the course. The first is the absolutely free version, which is software as a service, meaning it runs in any web browser. The second is the desktop version. If you work or study 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.
2 Stunden zum Abschließen
14 Videos (Gesamt 54 min), 8 Lektüren
14 Videos
Welcome6m
The Klopper Research Group1m
Assumptions1m
Learning a computer language1m
Why the Wolfram language?7m
Getting Mathematica5m
The new Wolfram Cloud1m
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 Wolfram Cloud10m
Welcome to Module 310m
Module 3 Notebook10m
Module 3 Exercise10m
3 Stunden zum Abschließen
Week 2
In week 2, we start with some actual coding, now that you know about the Wolfram Language and its different coding environments. We start off with a demonstration of a completed project. It is just a little teaser, showcasing what you will be able to do at the end. Next, we are going to learn to code by doing simple arithmetic. That is simple 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. These are the stepping stone required to bringing in your own data, ready for the analyses in the following weeks.
3 Stunden zum Abschließen
20 Videos (Gesamt 100 min), 8 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
8 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
Coronavirus data analysis10m
1 praktische Übung
Modules 1 to 5
5 Stunden zum Abschließen
Week 3
In week 3, its time to start analyzing data, now that you can write some code and import your data. The two most important steps to understand the message hidden in data, are 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 it really shines when creating plots. There are almost no limits to customizing plots. No matter what your project requirements, you will learn to create plots that work for you. Starting this week is an optional Honors lessons that introduce machine learning using the Wolfram Language.
5 Stunden zum Abschließen
27 Videos (Gesamt 153 min), 10 Lektüren, 2 Quiz
27 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
01: Introduction to neural networks46
02: Introduction to machine learning6m
03: The fundamentals25
04: Basic framework of a neural network10m
05: Layers in a neural network11m
06: Reviewing a neural network4m
07: From inputs to predictions6m
08: Finding a solution10m
10 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
Neural networks in the Wolfram language10m
2 praktische Übungen
Modules 6 to 9
Honors: Deep learning basics1h
5 Stunden zum Abschließen
Week 4
This final week covers all the common statistical tests - going from Student's t-test to analysis of variance to chi-squared tests. We conclude the course with a run-through of the demonstration research project that you saw at the beginning of week two. This brings together all the skills that you have acquired during the course and prepares you for the final exam. You will also have the opportunity to create your own computational essay, if you are not content with just working through the demonstration project. For those following the optional Honors lessons there is an introduction to deep learning using the Wolfram Language.
5 Stunden zum Abschließen
27 Videos (Gesamt 121 min), 13 Lektüren, 3 Quiz
27 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
Congratulations on reaching the end20
09: Introduction to Wolfram Language machine learning25
10: Automated Machine Learning10m
11: Running an automated algorithm4m
12: Testing the automated algorithm3m
13: Setting the method to neural network3m
14: Normalizing the data7m
15: Manually created neural networks8m
16: Regression - part 14m
17: Regression - part 22m
18: Regression - part 37m
13 Lektüren
Welcome to Module 105m
Module 10 Notebook5m
Module 10 Exercise5m
Welcome to Module 115m
Module 11 Notebook5m
Module 11 Exercise5m
Welcome to Module 125m
Module 12 Notebook5m
Module 12 Exercise5m
Welcome to Module 1310m
Module 13 Notebook10m
Final Exam Instructions10m
Continuing your journey with deep neural networks10m
3 praktische Übungen
Modules 10 to 13
Final Exam
Honors: Deep learning functions1h
von
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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