Biostatistics is the application of statistical reasoning to the life sciences, and it is the key to unlocking the data gathered by researchers and the evidence presented in the scientific literature. In this course, we'll focus on the use of statistical measurement methods within the world of public health research. Along the way, you'll be introduced to a variety of methods and measures, and you'll practice interpreting data and performing calculations on real data from published studies. Topics include summary measures, visual displays, continuous data, sample size, the normal distribution, binary data, the element of time, and the Kaplan-Meir curve.
Этот курс входит в специализацию ''Специализация Biostatistics in Public Health '
Summary Statistics in Public Health
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Об этом курсе
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Чему вы научитесь
Calculate continuous data measures
Interpret data visualizations
Analyze binary data
Analyze time to event data
Приобретаемые навыки
StatisticsNormal Distributionsummary measuresbinary data
Программа курса: что вы изучите
Неделя
11 ч. на завершение
The Role of Statistics in Public Health Research
Within this learning module, you will learn how statistics are used within public heath research. Topics covered include study design types, data types, and data summarization. You will complete a practice quiz before completing a graded quiz.
6 видео ((всего 64 мин.)), 1 тест
6 видео
Welcome47
Introduction and Overview11мин
Samples Versus Population11мин
Considerations with Regard to Study Design22мин
Data Types and Summarization8мин
Additional Examples9мин
1 практическое упражнение
Practice Quiz: The Role of Statistics in Public Health Research
4 ч. на завершение
Continuous Data Measures
Module two involves several lectures, a practice quiz and a graded quiz. Topics include summary statistics, visual displays, role of sample size, and continuous data.
6 видео ((всего 88 мин.)), 2 тестов
6 видео
Introduction2мин
Useful Summary Statistics24мин
Visual Displays16мин
The Role of Sample Size on Sample Based Estimates16мин
Comparing Distributions of Continuous Data16мин
Additional Examples11мин
2 практического упражнения
Practice: Continuous Data Measures1ч
Continuous Data Measures1ч 20мин
Неделя
23 ч. на завершение
The Normal Distribution
The focus of this module is on normal distribution. Topics covered include defining the standard normal distribution, and application of principles of normal distribution to sample data. There is a practice quiz where you can test your knowledge before completing the graded quiz.
5 видео ((всего 75 мин.)), 2 тестов
5 видео
Introduction3мин
The Standard Normal Distribution Defined19мин
Applying the Principles of the Normal Distribution to Sample Data to Estimate Characteristics of Population Data26мин
What Happens When We Apply the Properties of the Normal Distribution to Data Not Approximately Normal: A Warning13мин
Additional Examples12мин
2 практического упражнения
Practice: The Normal Distribution30мин
The Normal Distribution1ч
Неделя
33 ч. на завершение
Binary Data
Module four covers binary data and its significance. In addition to lectures, you will complete a practice quiz and a graded quiz.
6 видео ((всего 78 мин.)), 2 тестов
6 видео
Introduction2мин
Binary Data: Definition and Summarization (Binomial Distribution, P-Hat, SD)11мин
Comparing Distributions of Binary Data: Risk Difference and Relative Risk22мин
Comparing Distributions of Binary Data: Odds Ratios16мин
A Brief Note About Ratios (Will Also Be Revisited Later in the Course)12мин
Additional Examples13мин
2 практического упражнения
Practice: Binary Data20мин
Binary Data1ч
Неделя
42 ч. на завершение
Dealing with the Element of Time
In module five, you will explore how time is defined and studied in relation to data and learn about the Kaplan-Meir curve. In addition to a practice quiz, you will complete a graded quiz and project.
6 видео ((всего 85 мин.)), 2 тестов
6 видео
Introduction3мин
Time to Event Data: Definition (Censoring) and Numerical Summary Measures (Incidence Rates)24мин
Numerically Comparing Groups on Time to Event Outcomes11мин
Summarizing Time-to-Event Data, Graphically27мин
Graphically Comparing Groups on Time to Event Outcomes9мин
Additional Examples10мин
2 практического упражнения
Practice: Dealing with the Element of Time
Dealing with Elements of Time1ч
2 ч. на завершение
Course Project
During this module, you get the chance to demonstrate what you've learned by putting yourself in the shoes of biostatistical consultant on two different studies, one about asthma medication and the other about self-administration of injectable contraception. The two research teams have asked you to help them interpret previously published results in order to inform the planning of their own studies.
1 материал для самостоятельного изучения, 1 тест
1 материал для самостоятельного изучения
Biostatistical Consulting Project30мин
1 практическое упражнение
Course Project Quiz1ч
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Лучшие отзывы о курсе Summary Statistics in Public Health
Great course. The lecturer makes things so easy to understand. I love that there are additional examples available. I will definitely recommend this course to everyone in healthcare
This is a well structured content. The course is presented in the most simplest form to accommodate complete novices. I found it very educative, practical and lucidly intense.
Преподаватели
John McGready, PhD, MS
Associate Scientist, BiostatisticsBloomberg School of Public Health
О Университет Джонса Хопкинса
The mission of The Johns Hopkins University is to educate its students and cultivate their capacity for life-long learning, to foster independent and original research, and to bring the benefits of discovery to the world.
Специализация Biostatistics in Public Health : общие сведения
This specialization is intended for public health and healthcare professionals, researchers, data analysts, social workers, and others who need a comprehensive concepts-centric biostatistics primer. Those who complete the specialization will be able to read and respond to the scientific literature, including the Methods and Results sections, in public health, medicine, biological science, and related fields. Successful learners will also be prepared to participate as part of a research team.
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