Statistical Analysis in R
Skills Covered: Statistical Inference, Modelling Using R, Central Limit Theorem, Hypothesis Testing, P-values, Statistical Significance, Practical Significance, Data Visualisation Using R, Analysis of Variance (ANOVA), Design of Experiments (DOE), Data Analysis Using R, Generalised Linear Models (GLMs), Linear Regression Models, Model Selection
ABOUT THIS PROFESSIONAL CERTIFICATION
Applied Statistical Data Analysis Using R professional certificate is directed at people with limited statistical background and no practical experience who have to do data analysis, as well as those who are “out of practice”. The course is practice orientated, aiming to give learners an understanding of why the method works, how to implement it using R, when to apply it and where to look if the particular method is not applicable in the specific situation.
WHAT YOU WILL LEARN
- Basics of statistical inference, confidence intervals and hypothesis testing. Commonly used tests. Pvalues, statistical and practical significance.
- Analysis of Variance (ANOVA) and post-hoc tests. Diagnostics, implementation and interpretation using R.
- Numerical Methods: The use of simulations, nonparametric bootstrap and permutation tests using R.
- Linear Regression, Analysis of Variance with Covariates (ANCOVA), Generalised Linear Models (GLMs) and Mixed Effects Linear models using R.
- Basics of power analysis (sample size evaluation) and some thoughts on experimental design.
- The data analysis skills provided by this course will improve your employment and career prospects, whatever your area or interest.
- Data analytic skills are widely employed in epidemiology, ecology, forestry, agriculture, meteorology, marketing, (and pretty much everywhere).
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