Statistical Analysis with R for Public Health

dc.contributor.author	Isnuwardana, Ronny
dc.date.accessioned	2022-01-14T06:34:44Z
dc.date.available	2022-01-14T06:34:44Z
dc.date.issued	2021-10-19
dc.identifier.other	coursera.org/verify/specialization/DQBFA629FZMY
dc.identifier.uri	http://repository.unmul.ac.id/handle/123456789/9344
dc.description	This Specialisation comprises four courses on formulating and testing hypotheses, correlation and three main types of regression, including testing model assumptions and dealing with real-world data problems through statistical analysis using R software. Successful participants can appreciate how key statistical concepts such as sample size and how the data were generated are important to modern public health research and practice. They are able to apply appropriate methods in order to formulate and examine statistical associations between variables within a data set using R. Finally, they can interpret the output from their analysis and appraise the role of chance and bias as potential explanations for their results.	en_US
dc.language.iso	en_US	en_US
dc.publisher	Coursera	en_US
dc.title	Statistical Analysis with R for Public Health	en_US
dc.type	Other	en_US