About this Course
최근 조회 52,366

다음 전문 분야의 3개 강좌 중 1번째 강좌:

100% 온라인

지금 바로 시작해 나만의 일정에 따라 학습을 진행하세요.

유동적 마감일

일정에 따라 마감일을 재설정합니다.

초급 단계

You will only need an interest in analysing quantitative data and familiarity with reading standard graphs and tables of data.

완료하는 데 약 10시간 필요

권장: 2-5 hours/week...

영어

자막: 영어

배울 내용

  • Check

    Defend the critical role of statistics in modern public health research and practice

  • Check

    Describe a data set from scratch, including data item features and data quality issues, using descriptive statistics and graphical methods in R

  • Check

    Select and apply appropriate methods to formulate and examine statistical associations between variables within a data set in R

  • Check

    Interpret the output from your analysis and appraise the role of chance and bias

귀하가 습득할 기술

Run basic analyses in RR ProgrammingUnderstand common data distributions and types of variablesFormulate a scientific hypothesis

다음 전문 분야의 3개 강좌 중 1번째 강좌:

100% 온라인

지금 바로 시작해 나만의 일정에 따라 학습을 진행하세요.

유동적 마감일

일정에 따라 마감일을 재설정합니다.

초급 단계

You will only need an interest in analysing quantitative data and familiarity with reading standard graphs and tables of data.

완료하는 데 약 10시간 필요

권장: 2-5 hours/week...

영어

자막: 영어

강의 계획 - 이 강좌에서 배울 내용

1
완료하는 데 4시간 필요

Introduction to Statistics in Public Health

Statistics has played a critical role of statistics in public health research and practice, and you’ll start by looking at two examples: one from eighteenth century London and the other by the United Nations. The first task in carrying out a research study is to define the research question and express it as a testable hypothesis. With examples from the media, you’ll see what does and does not work in this regard, giving you a chance to define a research question from some real news stories.

...
5 videos (Total 23 min), 7 readings, 2 quizzes
5개의 동영상
Uses of Statistics in Public Health5m
Introduction to Sampling3m
How to Formulate a Research Question3m
Formulating a research question for the Parkinson's disease and supplement studies4m
7개의 읽기 자료
About Imperial College & the Team10m
How to be successful in this course10m
Grading policy10m
Data set and Glossary10m
Additional Reading10m
John Snow and the Cholera outbreak of 184920m
Instructions for Quiz10m
2개 연습문제
Parkinson's Disease Study Issues15m
Research Question Formulation1h
2
완료하는 데 4시간 필요

Types of Variables, Common Distributions and Sampling

This module will introduce you to some of the key building blocks of knowledge in statistical analysis: types of variables, common distributions and sampling. You’ll see the difference between “well-behaved” data distributions, such as the normal and the Poisson, and real-world ones that are common in public health data sets.

...
6 videos (Total 34 min), 3 readings, 5 quizzes
6개의 동영상
Overview of types of variables4m
Well-behaved Distributions7m
Real-world Distributions and their Problems5m
The Role of Sampling in Public Health Research8m
How to choose a Sample4m
3개의 읽기 자료
Types of variables and the special case of age10m
More on the 95% Confidence Interval10m
Using your sample to estimate the population mean20m
5개 연습문제
Types of variables20m
Special case of age20m
Well-behaved Distributions20m
Ways of Dealing with Weird Data15m
Sampling10m
3
완료하는 데 3시간 필요

Introduction to R and RStudio

Now it’s time to get started with the powerful and completely free statistical software R and its popular interface RStudio. With the example of fruit and vegetable consumption, you’ll learn how to download R, import the data set and run essential descriptive analyses to get to know the variables.

...
2 videos (Total 20 min), 10 readings, 2 quizzes
2개의 동영상
How to Load Data and run Basic Tabulations in R13m
10개의 읽기 자료
How to Calculate Percentiles10m
Introduction to R20m
R Resources10m
Practice with R: Perform Descriptive Analysis10m
Feedback: Descriptive Analysis10m
How to judge visually if a variable is normally distributed in R10m
Practice with R - trying it out for yourself10m
Extra features in R10m
Practice with R: Extra features10m
Feedback: Extra features10m
2개 연습문제
Distributions and Medians20m
Calculations: Percentiles by Hand20m
4
완료하는 데 5시간 필요

Hypothesis Testing in R

Having learned how to define a research question and testable hypothesis earlier in the course, you’ll learn how to apply hypothesis testing in R and interpret the result. As all medical knowledge is derived from a sample of patients, random and other kinds of variation mean that what you measure on that sample, such as the average body mass index, is not necessarily the same as in the population as a whole. It’s essential that you incorporate this uncertainty in your estimate of average BMI when presenting it. This involves the calculation of a p value and confidence interval, fundamental concepts in statistical analysis. You’ll see how to do this for averages and proportions.

...
4 videos (Total 20 min), 14 readings, 5 quizzes
4개의 동영상
Hypothesis Testing6m
Choosing the Sample Size for your Study4m
Summary of Course2m
14개의 읽기 자료
The Coin Tossing Experiment: Part I10m
The Coin Tossing Experiment: Part II10m
The Coin Tossing Experiment: Feedback20m
Degrees of Freedom 20m
The chi-squared test with fruit and veg20m
Feedback: Sample Size and Variation10m
Comparing Two Means10m
Practice with R: Hypothesis Testing10m
Feedback: Hypothesis Testing in R10m
The Difference between t-test and Chi-squared test10m
Practice with R: Running a New Hypothesis Test10m
P values and Thresholds10m
Deaths data set for the end-of-course Assessment10m
Final R code10m
5개 연습문제
Hypothesis Testing10m
The Coin Tossing Experiment: Evaluation30m
Results: Running a New Hypothesis Test20m
Hypothesis Testing15m
End-of-course Assessment20m
4.7
22개의 리뷰Chevron Right

67%

이 강좌를 수료한 후 새로운 경력 시작하기

40%

이 강좌를 통해 확실한 경력상 이점 얻기

Introduction to Statistics & Data Analysis in Public Health의 최상위 리뷰

대학: LAMay 26th 2019

Was a very nicely done and clear course to build or re-build foundation for most common statistical concepts and an intro to using R via R-Studio for your work with them on the basics.

대학: MNApr 8th 2019

Wonderful explanation and introduction to R programing. With minimal additional self learning you can easily master all of the content of the course.

강사

Avatar

Alex Bottle

Reader in Medical Statistics
School of Public Health

Start working towards your Master's degree

이 강좌은(는) 임페리얼 칼리지 런던의 100% 온라인 Global Master of Public Health 중 일부입니다. 전체 프로그램을 수료하면 귀하의 강좌가 학위 취득에 반영됩니다.

임페리얼 칼리지 런던 정보

Imperial College London is a world top ten university with an international reputation for excellence in science, engineering, medicine and business. located in the heart of London. Imperial is a multidisciplinary space for education, research, translation and commercialisation, harnessing science and innovation to tackle global challenges. Imperial students benefit from a world-leading, inclusive educational experience, rooted in the College’s world-leading research. Our online courses are designed to promote interactivity, learning and the development of core skills, through the use of cutting-edge digital technology....

Statistical Analysis with R for Public Health 전문 분야 정보

Statistics are everywhere. The probability it will rain today. Trends over time in unemployment rates. The odds that India will win the next cricket world cup. In sports like football, they started out as a bit of fun but have grown into big business. Statistical analysis also has a key role in medicine, not least in the broad and core discipline of public health. In this specialisation, you’ll take a peek at what medical research is and how – and indeed why – you turn a vague notion into a scientifically testable hypothesis. You’ll learn about key statistical concepts like sampling, uncertainty, variation, missing values and distributions. Then you’ll get your hands dirty with analysing data sets covering some big public health challenges – fruit and vegetable consumption and cancer, risk factors for diabetes, and predictors of death following heart failure hospitalisation – using R, one of the most widely used and versatile free software packages around. This specialisation consists of four courses – statistical thinking, linear regression, logistic regression and survival analysis – and is part of our upcoming Global Master in Public Health degree, which is due to start in September 2019. The specialisation can be taken independently of the GMPH and will assume no knowledge of statistics or R software. You just need an interest in medical matters and quantitative data....
Statistical Analysis with R for Public Health

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