Brush up on essential stats
Have you ever found yourself referring to statistical concepts such as p values or normal distributions without truly understanding them – and hoping nobody notices?
In this 2-hour training, Prof. Amanda Salis will succinctly draw together plain-language explanations of statistical concepts frequently used in quantitative research such as meta-analyses and regression analyses. No statistical jargon and undefined abbreviations: just everyday language and concrete examples. The intention is that you’ll never need to strain your brain again to think about what these statistical concepts actually mean, enabling you to more confidently progress through the more advanced statistical adventures of your research. Topics covered are listed below.
- Variable types (e.g., continuous, categorical, binary)
- Normal distribution
- Standard deviation
- Standard score/z-score
- Standardized mean difference
- Standard error (also known as standard error of the mean or standard error of the sample mean)
- Confidence interval
- P value
- Effect size (also known as effect estimate or estimate of effect)
- Risk ratio (also known as relative risk or relative risk ratio)
- Odds ratio
- Risk difference
- Regression analysis
- Correlation coefficient
- R squared
Who is this training for?
Any researcher from any institution seeking to quickly brush up their understanding of statistical concepts underlying more complex statistical analyses such as meta-analyses, regression analyses and survival analyses.
- Honours students
- Higher degree research students (e.g., Masters and PhD students)
- Junior postdoctoral fellows
- Senior researchers