Select Page
JHU coronavirus analysis end 2020

JHU coronavirus analysis end 2020

by | 2021, Jan, Sun | Computer coding, Education, Machine learning

INTRODUCTION

There are numerous analyses on the internet and in research papers regarding COVID-19. Data from the pandemic is very useful for creating educational material. The Johns-Hopkins University (JHU) data repository contains large open data sets on the pandemic.

In this notebook, I showcase the use of this data resource. The aims are as follows:

Use the JHU data as teaching material for the R language
Use the JHU data as teaching material for data analysis
Compare data between countries (South Africa, Germany, United Kingdom)
Look ahead at what may happen in South Africa in early 2021

View the complete RPub document here 

 

View the complete RPub document here

CONCLUSION

South Africa lags behind in the time line of COVID-19. Cases in South Africa were much higher after the first wave. It may be that the case load will be very high in the first part of 2021.

While we do consider that a current strain of SARS-CoV-2 is more infective, there might be confounding factors as there is great concern about human activities and interactions, especially since the progressive lifting of restrictions. The festive season may worsen upcoming case numbers.

Seroprevalence studies in South Africa are showing a a much higher level of infection than confirmed cases report. Vaccines will take the better part of 2021 to reach large parts of South Africa.

R tutorial: Just getting started with R? Here is a post on inspecting univariate data

by | 2018, Jun, Thu | Computer coding, Computer languages, Medical Statistics, The Klopper Research Group

R tutorial: Just getting started with R? Here is a post on inspecting univariate data

If you are new to R, then perhaps a look at simple univariate data is a good place to start.  In this RPubs post, I take a look at both categorical and numerical data.  It is quite easy to calculate descriptive statistics of univariate data and to visualize it using plots.  Click the link and have a look.

By the way, the file is also available on GitHub.

World Bank data on maternal mortality using R

by | 2018, Jun, Tue | Computer coding, Computer languages, Medical Statistics, The Klopper Research Group, Uncategorized

World Bank data on maternal mortality using R

The World Bank provides open data for many indicators across most countries, spanning the last few decades.

This data is available online with searches available by country codes (iso2c and iso3c), indicator names, and by dates. The indicators can be viewed here. It can also be accessed via an application programming interface (API).  The WDI library in R provides access through this API, allowing for easy search and retrieval of data.

In this post, written as an R-markdown file, and available on RPubs and GitHub, I showcase the WDI library by looking at maternal mortality rates for the United States, Brazil, and South Africa.

Follow the links and have a look.

R tutorial: Testing assumptions for parametric tests

by | 2018, Jun, Mon | Computer coding, Computer languages, Education, Medical Statistics, The Klopper Research Group

R tutorial: Testing assumptions for parametric tests

In this post, written as an R-markdown file and posted on RPubs, I discuss the assumptions for the use of parametric tests in R.

Parametric tests such as the various t tests, analysis of variance (ANOVA), and correlations are only valid if certain assumptions are met. When these assumptions are not met, the use of these tests in your research may lead to false claims.

In the post I show you the most important assumptions and how to test for them using the R programming language.

The post is available on RPubs and the markdown file is on GitHub.

Rpubs markdown files and YouTube videos on R

by | 2018, Jun, Fri | Computer coding, Education, Medical Statistics, The Klopper Research Group

Rpubs markdown files and YouTube videos on R

R is a programming language designed by statisticians for statistical analysis. It is a free programming language and is available for download (Windows, Mac, and Linux).

Bar a few eccentricities, it is quite easy to learn R. We make extensive use of it in the Klopper Research Group, where, alongside other programming languages, I use it to teach my students how to conduct proper data analysis.

I have started to create a series of R markdown files that are published on the Rpubs website . I am also making a series of YouTube videos on the use of R. The first set is on the use of the Plotly library to create interactive HTML widget plots in R.