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.
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Doing Clinical Research: Biostatistics with the Wolfram Language
开普敦大学課程信息
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初級
完成時間大約為15 小時
英語（English）
字幕：英語（English）
您將獲得的技能
Learn to use the Wolfram Language to summarize data and create plotsLearn to use the Wolfram Language to do common statistical tests
可分享的證書
完成後獲得證書
100% 在線
立即開始，按照自己的計劃學習。
可靈活調整截止日期
根據您的日程表重置截止日期。
初級
完成時間大約為15 小時
英語（English）
字幕：英語（English）
提供方
开普敦大学
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.
教學大綱 - 您將從這門課程中學到什麼
完成時間為 3 小時
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.
完成時間為 3 小時
14 個視頻 （總計 54 分鐘）, 8 個閱讀材料
14 個視頻
Welcome6分鐘
The Klopper Research Group1分鐘
Assumptions1分鐘
Learning a computer language1分鐘
Why the Wolfram language?7分鐘
Getting Mathematica5分鐘
The new Wolfram Cloud1分鐘
The Wolfram Cloud1分鐘
The Wolfram Programming Lab8分鐘
Free-form input and Wolfram Alpha in the Cloud3分鐘
Mathematica27
Free-form input and Wolfram Alpha in the desktop7分鐘
Help and documentation3分鐘
Assignment notebooks4分鐘
8 個閱讀材料
How this Course Works10分鐘
Welcome to Module 110分鐘
Meet the Course Instructor10分鐘
Module 1 Notebook10分鐘
Welcome to Wolfram Cloud10分鐘
Welcome to Module 310分鐘
Module 3 Notebook10分鐘
Module 3 Exercise10分鐘
完成時間為 3 小時
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.
完成時間為 3 小時
20 個視頻 （總計 100 分鐘）, 8 個閱讀材料, 1 個測驗
20 個視頻
Simulated data demonstration - part 11分鐘
Simulated data demonstration - part 27分鐘
Simple arithmetic30
Addition and subtraction5分鐘
Multiplication and division9分鐘
Powers5分鐘
Arithmetical order2分鐘
Calculating a mean5分鐘
Working with data40
Lists part 17分鐘
Lists part 23分鐘
Tables7分鐘
Index10分鐘
Datasets9分鐘
Selecting6分鐘
Dataset functions3分鐘
Creating lists from datasets2分鐘
Spreadsheets6分鐘
Spreadsheets in the cloud4分鐘
8 個閱讀材料
Welcome to Module 410分鐘
Module 4 Notebook10分鐘
Welcome to Module 510分鐘
Module 5 Exercise10分鐘
Welcome to Module 610分鐘
Module 6 Notebook10分鐘
Module 6 Exercise10分鐘
Coronavirus data analysis10分鐘
1 個練習
Modules 1 to 5
完成時間為 5 小時
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.
完成時間為 5 小時
27 個視頻 （總計 153 分鐘）, 10 個閱讀材料, 2 個測驗
27 個視頻
Descriptive statistics49
Data import for descriptive statistics5分鐘
Creating lists for descriptive statistics8分鐘
Point estimates10分鐘
Measures of dispersion6分鐘
Data Visualization39
Data import for visualization2分鐘
Scatter plots10分鐘
Box plots3分鐘
Histograms5分鐘
Bar and pie charts6分鐘
Distributions1分鐘
Probability8分鐘
PDF and CDF3分鐘
Discrete distributions7分鐘
Continuous distributions6分鐘
Sampling distributions6分鐘
Simulated data6分鐘
01: Introduction to neural networks46
02: Introduction to machine learning6分鐘
03: The fundamentals25
04: Basic framework of a neural network10分鐘
05: Layers in a neural network11分鐘
06: Reviewing a neural network4分鐘
07: From inputs to predictions6分鐘
08: Finding a solution10分鐘
10 個閱讀材料
Welcome to Module 710分鐘
Module 7 Notebook10分鐘
Module 7 Exercise10分鐘
Welcome to Module 810分鐘
Module 8 Notebook10分鐘
Module 8 Exercise10分鐘
Welcome to Module 910分鐘
Module 9 Notebook10分鐘
Module 9 Exercise10分鐘
Neural networks in the Wolfram language10分鐘
2 個練習
Modules 6 to 9
Honors: Deep learning basics1小時
完成時間為 5 小時
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.
完成時間為 5 小時
27 個視頻 （總計 121 分鐘）, 13 個閱讀材料, 3 個測驗
27 個視頻
Linear regression36
Importing data4分鐘
Descriptive statistics and visualization3分鐘
Linear model5分鐘
Comparing means17
Data import3分鐘
Comparing two means8分鐘
Comparing more than two means7分鐘
Comparing categorical variables21
Contingency tables7分鐘
Chi-squared test3分鐘
Creating a Computational Essay47
Data import7分鐘
Main research question6分鐘
Secondary research questions7分鐘
Congratulations on reaching the end20
09: Introduction to Wolfram Language machine learning25
10: Automated Machine Learning10分鐘
11: Running an automated algorithm4分鐘
12: Testing the automated algorithm3分鐘
13: Setting the method to neural network3分鐘
14: Normalizing the data7分鐘
15: Manually created neural networks8分鐘
16: Regression - part 14分鐘
17: Regression - part 22分鐘
18: Regression - part 37分鐘
13 個閱讀材料
Welcome to Module 105分鐘
Module 10 Notebook5分鐘
Module 10 Exercise5分鐘
Welcome to Module 115分鐘
Module 11 Notebook5分鐘
Module 11 Exercise5分鐘
Welcome to Module 125分鐘
Module 12 Notebook5分鐘
Module 12 Exercise5分鐘
Welcome to Module 1310分鐘
Module 13 Notebook10分鐘
Final Exam Instructions10分鐘
Continuing your journey with deep neural networks10分鐘
3 個練習
Modules 10 to 13
Final Exam
Honors: Deep learning functions1小時
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