Depending upon the subject that you are studying, it is possible that you may need to use statistics at some point within your course. The Royal Statistical Society and the American Statistical Association both aim to advance the work of statistics and support statisticians. Some of their events may be useful or simply interesting to see how others research areas that may be of interest to you too. As an example, there are a number of Rugby related events and articles wrapped around Rugby World Cup 2019 that ran in the Autumn of 2019. Significance magazine has sections that relate to Sports, Business, Culture, Politics and Science.
More or Less, Counter Points and Wharton Moneyball (as shown on the Podcast list) are useful podcasts in relation to the use of statistics in sport and other areas and whilst there are a number of blogs and sites, fivethirtyeight also covers topics similar to the Science magazine.
Many Universities and course offer bespoke support, but these links may be of some value to some;
- What Is Statistics: Crash Course Statistics #1
- Mathematical Thinking: Crash Course Statistics #2
- Mean, Median, and Mode: Measures of Central Tendency: Crash Course Statistics #3
- Measures of Spread (Dispersion): Crash Course Statistics #4
- Charts Are Like Pasta - Data Visualization Part 1: Crash Course Statistics #5
- Plots, Outliers, and Justin Timberlake: Data Visualization Part 2: Crash Course Statistics #6
- The Shape of Data: Distributions: Crash Course Statistics #7
- Correlation Doesn’t Equal Causation: Crash Course Statistics #8
- Controlled Experiments: Crash Course Statistics #9
- Sampling Methods and Bias with Surveys: Crash Course Statistics #10
- Science Journalism: Crash Course Statistics #11
- Henrietta Lacks, the Tuskegee Experiment, & Ethical Data Collection: Crash Course Statistics #12
- Probability Part 1: Rules and Patterns: Crash Course Statistics #13
- Probability Part 2: Updating Your Beliefs with Bayes: Crash Course Statistics #14
- The Binomial Distribution: Crash Course Statistics #15
- Geometric Distributions & The Birthday Paradox: Crash Course Statistics #16
- Randomness: Crash Course Statistics #17
- Z-Scores and Percentiles: Crash Course Statistics #18
- The Normal Distribution: Crash Course Statistics #19
- Confidence Intervals: Crash Course Statistics #20
- How p-values help us test hypotheses: Crash Course Statistics #21
- P-Value Problems: Crash Course Statistics #22
- Playing with Power: P-Values Pt 3: Crash Course Statistics #23
- You know I’m all about that Bayes: Crash Course Statistics #24
- Bayes in science and everyday life: Crash Course Statistics #25
- Test Statistics: Crash Course Statistics #26
- T-Tests: A Matched Pair Made in Heaven: Crash Course Statistics #27
- Degrees of Freedom & Effect Sizes: Crash Course Statistics #28
- Chi-Square Tests: Crash Course Statistics #29
- P-Hacking: Crash Course Statistics #30
- The Replication Crisis: Crash Course Statistics #31
- Regression: Crash Course Statistics #32 (General Linear Model – GLM)
- ANOVA: Crash Course Statistics #33
- ANOVA Part 2: Dealing with Intersectional Groups: Crash Course Statistics #34
- Fitting Models Is like Tetris: Crash Course Statistics #35
- Supervised Machine Learning: Crash Course Statistics #36
- Unsupervised Machine Learning: Crash Course Statistics #37
- Intro to Big Data: Crash Course Statistics #38
- Big Data Problems: Crash Course Statistics #39
- Statistics in the Courts: Crash Course Statistics #40
- Neural Networks: Crash Course Statistics #41
- War: Crash Course Statistics #42
- When Predictions Fail: Crash Course Statistics #43
- When Predictions Succeed: Crash Course Statistics #44

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