Statistics Using R
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By the end of this 10-week course, you’ll be able to:
- Use the R language for statistical analysis of large, complex data sets.
- Apply statistical methods to data associated with a problem to answer questions about the problem.
- Select appropriate statistical tests for a problem and interpret and present the results of the analysis.
- Introduction to R and RStudio
- Measures of central tendency and dispersion
- Working with normal distribution, probability calculations, and R
- Sampling distribution, central limit theorem, and confidence intervals
- Elementary hypothesis testing with one sample of data
- Elementary hypothesis testing with more than two samples of data (ANOVA)
- Relationships in data: correlation and linear regression
- Qualitative data: probability and Chi-square tests
No eligibility requirements
No additional requirements
In this course, you’ll be introduced to a powerful statistical computing software called R. R is a software with built-in functionalities to assist you in statistically analysing and visualising big sets of data with ease. As an open-source software, developers also continuously build packages and libraries that can be loaded into R to simplify complex statistical operations.
This course revisits basic concepts of statistics such as measures of centrality and distributions. You’ll also be introduced to different methods of hypothesis testing, as well as other statistical concepts. By the end of this course, you’ll leave with the skills to use R to analyse and solve statistical problems in various contexts.
UniSA Online’s 10-week short courses give you the flexibility to upskill in a certain area, stay current with developments in your field, diversify your knowledge, or even explore a new direction in your career – without having to commit to the time and cost of a full university degree.
Delivered 100% online, you’ll be able to study where and when it suits you. Access online academic and student support seven days a week, fit study around work and life commitments, view learning resources 24/7, and log in to the interactive online environment anywhere, any time and on any device.
This is a third-year course from UniSA Online’s Bachelor of Data Analytics degree. Please note: you are responsible for completing any relevant prerequisite courses before enrolling in this course.
Should your course have an exam it will be scheduled for Australian Central Standard Time or Australian Central Daylight Time, depending on the time of the year.
- Project - 3000 words (50%)
- Other (50%)
Current study term: 26 Jun 22 to 02 Sep 22
Textbooks are not required.