Index of definitions and examples
Definitions
- 4.4 \(\chi^2\) distribution
- 6.4 \(p\)-value
- 4.7 Consistent estimator
- 1.5 Covariance
- 4.3 Estimators
- 1.4 Histogram
- 5.1 Interval estimate
- 1.2 Median and quartiles
- 1.6 Pearson’s correlation coefficient
- 1.1 Percentile/Quantile
- 9.1 Power
- 4.1 Sample mean
- 4.2 Sample variance
- 6.3 Size / level of significance
- 1.7 Spearman’s correlation coefficient
- 4.6 Standard error
- 5.2 Student \(t\) distribution
- 1.3 The interquartile range
- 6.1 Type I error
- 6.2 Type II error
- 4.5 Unbiased estimator
Examples
- 3.1 Choosing probability distributions to represent data.
- 5.2 Confidence interval for a binomial probability parameter: Scottish independence opinion polls
- 5.1 Confidence intervals for the mean and variance of a normal distribution: Netflix stock prices
- 5.3 Confidence intervals: calculating a 99% confidence interval for a binomial probability parameter
- 4.4 Consistency of sample mean and sample variance
- 4.7 Consistency of sample proportion
- 10.1 Hypothesis testing: \(\chi^2\) test for contingency table data. Analysing student module questionnaire results
- 8.1 Hypothesis testing: comparing binomial proportions. Can early release and tagging of prisoners affect the likelihood of reoffending?
- 7.1 Hypothesis testing: two-sample \(t\) test (\(p\)-value method). Is quitting Facebook good for you?
- 7.2 Hypothesis testing: two-sample \(t\) test (Neyman-Pearson method). Testing a new diabetes treatment.
- 9.1 Sample size and power calculation for a hypothesis test.
- 4.2 Standard error of the sample mean
- 4.6 Standard error of the sample proportion
- 4.3 Standard error of the sample variance
- 4.1 Unbiased estimators: sample mean and sample variance
- 4.5 Unbiased estimators: sample proportion