Об этом курсе: If you’ve ever skipped over`the results section of a medical paper because terms like “confidence interval” or “p-value” go over your head, then you’re in the right place. You may be a clinical practitioner reading research articles to keep up-to-date with developments in your field or a medical student wondering how to approach your own research. Greater confidence in understanding statistical analysis and the results can benefit both working professionals and those undertaking research themselves. If you are simply interested in properly understanding the published literature or if you are embarking on conducting your own research, this course is your first step. It offers an easy entry into interpreting common statistical concepts without getting into nitty-gritty mathematical formulae. To be able to interpret and understand these concepts is the best way to start your journey into the world of clinical literature. That’s where this course comes in - so let’s get started! The course is free to enroll and take. You will be offered the option of purchasing a certificate of completion which you become eligible for, if you successfully complete the course requirements. This can be an excellent way of staying motivated! Financial Aid is also available.
Автор: University of Cape Town
Преподаватели: Juan H Klopper, Dr
Department of Surgery
| Выполнение | 6 weeks of study, 2-3 hours/week |
| Язык | English |
| Как пройти курс | Чтобы пройти курс, выполните все оцениваемые задания. |
| Оценки пользователей |
Программа курса
НЕДЕЛЯ 1
Getting things started by defining study types
Welcome to the first week of this course. We’ll be tackling five broad topics to provide you with an intuitive understanding of clinical research results. This isn’t a comprehensive statistics course, but it offers a practical orientation to the field of medical research and commonly used statistical analysis. The first topics will look at research methods and the collection of data - with a specific focus on study types. By the end of the lectures you should be able to identify which study types are being used and why the researchers selected them when you are reading a paper.
11 видео, 11 материала для самостоятельного изучения, 1 тренировочный тест
- Видео: About the course
- 閱讀: How this course works
- 閱讀: Pre-course survey
- 討論提示: Introduce yourself to your peers
- 閱讀: Study types
- Видео: Observing and intervening: Observational & experimental studies
- 閱讀: Key notes: Observational and experimental studies
- Видео: Observing and describing: Case series studies
- 閱讀: Key notes: Case series studies
- Видео: Comparing groups: Case-control studies
- 閱讀: Key notes: Case-control studies
- Видео: Collecting data at one point in time: Cross-sectional studies
- 閱讀: Key notes: Cross-sectional studies
- Видео: Studying a group with common traits: Cohort studies
- 閱讀: Key notes: Cohort studies
- Видео: Let's intervene: Experimental studies
- 閱讀: Key notes: Experimental studies
- Видео: Working with existing research: Meta-analysis and Systematic Review
- 閱讀: Key notes: Meta-analysis and systematic review
- 練習測驗: Test your knowledge: Study types
- 閱讀: Peer review introduction
- Видео: Doing a literature search: Part 1
- Видео: Doing a literature search: Part 2
Оцениваемый: Week 1: Navigating Clinical Research
НЕДЕЛЯ 2
Describing your data
With the next topics, we finally get started with the statistics. Have you ever looked at the methods and results section of any healthcare research publication and noted the variety of statistical tests used? You would have come across terms like t-test, Mann-Whitney-U test, Wilcoxon test, Fisher’s exact test and the ubiquitous chi-squared test. Why so many tests you might wonder? It’s all about types of data. In this week, I am going to tackle the differences in data which determine what type of statistical test we can use in making sense of our data.
15 видео, 12 материала для самостоятельного изучения, 3 тренировочных теста
- Видео: Some key concepts: Definitions
- 閱讀: Key notes: Definitions
- Видео: Data types
- 閱讀: Key notes: Data types
- Видео: Arbitary classification: Nominal categorical data
- 閱讀: Key notes: Nominal categorical data
- Видео: Natural ordering of attributes: Ordinal categorical data
- 閱讀: Key notes: Ordinal categorical data
- Видео: Measurements and numbers: Numerical data types
- 閱讀: Key notes: Numerical data types
- Видео: How to tell the difference: Discrete and continuous variables
- 閱讀: Key notes: Discrete and continuous variables
- 練習測驗: Test your knowledge: Data types
- Видео: Introduction
- 閱讀: Key notes: Describing the data
- Видео: Measures of central tendency
- 閱讀: Key notes: Measures of central tendency
- Видео: Measures of dispersion
- 閱讀: Key notes: Measures of dispersion
- 閱讀: Visual representation of data
- Видео: (Optional) Setting up spreadsheet software to do your own analysis
- Видео: (Optional) Descriptive statistics using spreadsheet software
- 練習測驗: Test your knowledge: Measures of central tendency and dispersion
- Видео: Making inferences: Sampling
- 閱讀: Key notes: Sampling
- Видео: Types of sampling
- 閱讀: Key notes: Types of sampling
- 練習測驗: Test your knowledge: Sampling
- Видео: Case study 1
- 討論提示: Share an example of clinical research
Оцениваемый: Week 2 Graded Quiz
НЕДЕЛЯ 3
Building an intuitive understanding of statistical analysis
There is hardly any healthcare professional who is unfamiliar with the p-value. It is usually understood to have a watershed value of 0.05. If a research question is evaluated through the collection of data points and statistical analysis reveals a value less that 0.05, we accept this a proof that some significant difference was found, at least statistically.In reality things are a bit more complicated than that. The literature is currently full of questions about the ubiquitous p-vale and why it is not the panacea many of us have used it as. During this week you will develop an intuitive understanding of concept of a p-value. From there, I'll move on to the heart of probability theory, the Central Limit Theorem and data distribution.
14 видео, 12 материала для самостоятельного изучения, 3 тренировочных теста
- 閱讀: Key notes: P-values
- Видео: Working out the probability: Rolling dice
- 閱讀: Key notes: Rolling dice
- Видео: Area under the curve: Continuous data types
- 閱讀: Key notes: Continuous data types
- 練習測驗: Test your knowledge: Probability
- Видео: Introduction to the central limit theorem: The heart of probability theory
- 閱讀: Introduction to the central limit theorem
- Видео: Asymmetry and peakedness: Skewness and Kurtosis
- 閱讀: Key notes: Skewness and kurtosis
- Видео: Learning from the lotto: Combinations
- 閱讀: Key notes: Combinations
- Видео: Approximating a bell-shaped curve: The central limit theorem
- 閱讀: Key notes: Central limit theorem
- 練習測驗: Test your knowledge: The central limit theorem
- Видео: Patterns in the data: Distributions
- 閱讀: Key notes: Distributions
- Видео: The bell-shaped curve: Normal distribution
- 閱讀: Key notes: Normal distribution
- Видео: Plotting a sample statistic: Sampling distribution
- 閱讀: Key notes: Sampling distribution
- Видео: Standard normal distribution: Z distribution
- 閱讀: Key notes: Z-distribution
- Видео: Estimating population parameters: t-distribution
- 閱讀: Key notes: The t-distibution
- Видео: (Optional) Generating random data point values using spreadsheet software
- 練習測驗: Test your knowledge: Distributions
- Видео: Case study 2
Оцениваемый: Week 3 Graded Quiz
НЕДЕЛЯ 4
The important first steps: Hypothesis testing and confidence levels
In general, a researcher has a question in mind that he or she needs an answer to. Everyone might have an opinion on the question (or answer), but an investigator looks for the answer by designing an experiment and investigating the outcome. In the first lesson we will look at hypotheses and how they relate to ethical and unbiased research and reporting.We'll also tackle Confidence intervals which I believe are one of the least understood and often misrepresented values in healthcare research. The most common tests used in the literature to compare numerical data point values are t-tests, analysis of variance, and linear regression. In the last lesson we take a closer look at these tests, but perhaps more importantly, their strict assumptions.
8 видео, 6 материала для самостоятельного изучения, 2 тренировочных теста
- Видео: Testing assumptions: Null and alternative hypothesis
- 閱讀: Key notes: Null and alternative hypothesis
- Видео: Is there a difference?: Alternative Hypothesis
- 閱讀: Key notes: Alternative hypothesis
- Видео: Type I and II: Hypothesis testing errors
- 閱讀: Key notes: Hypothesis errors
- 練習測驗: Testing your knowledge: Hypothesis
- Видео: Introduction to confidence intervals
- 閱讀: Key notes: Introduction to confidence intervals
- Видео: How confident are you?: Confidence levels
- 閱讀: Key notes: Confidence levels
- Видео: Interval estimation: Confidence intervals
- 閱讀: Key notes: Confidence intervals
- Видео: (Optional) Calculating confidence intervals using spreadsheet software
- 練習測驗: Test your knowledge: Confidence intervals
Оцениваемый: Week 4 Peer review
НЕДЕЛЯ 5
Which test should you use?
The most common statistical test that you might come across in the literature is the t-test. There are, in actual fact, a few t-tests, but the one most are familiar with, is of course, Student’s t-test and its ubiquitous p-value. Not everyone, though, knows that the name Student was actually a pseudonym, used by William Gosset (1876 - 1937). Parametric tests have very strict assumptions that must be met before their use is justified. In this lesson we take a closer look at these tests, but perhaps more importantly, their strict assumptions. Once you know these, you will be able to identify when these tests are used inappropriately.
15 видео, 6 материала для самостоятельного изучения, 2 тренировочных теста
- 閱讀: Key notes: Parametric tests
- Видео: Student's t-test
- 閱讀: Key notes: Student's t-test
- Видео: ANOVA
- 閱讀: Key notes: ANOVA
- Видео: Linear Regression
- 閱讀: Key notes: Linear regression
- Видео: (Optional) Student's t-test in action
- 練習測驗: Test your knowledge: Parametric tests
- Видео: Introduction to nonparametric tests
- Видео: Checking for normality
- 閱讀: Key notes: Nonparametric tests
- Видео: Thinking nonparametrically
- Видео: Comparing paired observations: Signs
- Видео: Ordering values: Ranking
- Видео: Paired comparisons: Sign ranks
- Видео: Summation of ranks: Rank sums
- Видео: Comparing two populations: Mann-Whitney-U test
- Видео: More nonparametric tests
- 閱讀: Key notes: Nonparametric tests
- 練習測驗: Test your knowledge: Non-parametric tests
- Видео: Case study 3
Оцениваемый: Week 5 Graded Quiz
НЕДЕЛЯ 6
Categorical data and analyzing accuracy of results
Congratulations! You've reached the final week of the course Understanding Clinical Research. In this lesson we will take a look at how good tests are at picking up the presence or absence of disease, helping us choose appropriate tests, and how to interpret positive and negative results. We’ll decipher sensitivity, specificity, positive and negative predictive values. You'll end of this course with a final exam, to test the knowledge and application you've learned in this course. I hope you've enjoyed this course and it helps your understanding of clinical research.
8 видео, 4 материала для самостоятельного изучения, 2 тренировочных теста
- Видео: Observed frequencies: Contingency tables
- Видео: Comparing observed and expected values: Chi-square test
- Видео: Association between two variables: Fisher's exact test
- 閱讀: Key notes: Comparing categorical data
- Видео: (Optional) Calculating chi-square test using spreadsheet software
- 練習測驗: Testing your knowledge: Comparing categorical data
- Видео: Introduction to sensitivity and specificity
- Видео: Measuring performance: Sensitivity and specificity
- Видео: Proportions of results: Positive and negative predictive values
- 閱讀: Keynotes: Sensitivity, specificity, positive and negative predictive values
- 練習測驗: Test your knowledge: Sensitivity, specificity and predictive values
- 閱讀: Interesting online videos
- 閱讀: Congratulations on completing the course
Оцениваемый: Week 6 Final examination
Часто задаваемые вопросы
Как это работает
課程作業
每門課程都像是一本互動的教科書，具有預先錄製的視頻、測驗和項目。
來自同學的幫助
與其他成千上萬的學生相聯繫，對想法進行辯論，討論課程材料，並尋求幫助來掌握概念。
證書
獲得正式認證的作業，並與朋友、同事和雇主分享您的成功。
Авторы
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.
Рейтинги и отзывы
A great and very easy to understand course. It gives you an idea of commonly used statistical analysis, but without going too deep into the math. Great if you are tired of reading articles and not understanding what a p-value or a paired t-test is. thumps up!
Very organised course and clearly explain the basics of Statistics needed by Medical researchers. It doesn't get very deep in explaining the math behind the tests, however it gets you a good start for understanding the results section in any article you read. Any one who need to start medical research should go by this course.
I'm so glad to complete that great course ♥
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杨
This course is really helpful for my understanding oin clinical research and paper writing