1. Statistical inquiry. Making sense of experience. What is statistics? Descriptive and inferential statistics. Collecting a sample.
2. Describing our sample. Statistical variables. Error, accuracy and approximations.
3. Summarizing our data. Tables and diagrams. Central tendency (averages). Measures of dispersion.
4. The shape of a distribution. Skewed distributions. Introducing the normal distribution. Proportions under the normal curve. Comparing values.
5. From sample to population. Estimates and inferences. The logic of sampling. A distribution of sample-means. Estimating the population-mean. Estimating other parameters.
6. Comparing samples. From the same or different populations? Significance testing. The significance of significance. Comparing dispersions. Non-parametric methods.
7. Further matters of significance. One- versus two-tailed tests. z-tests and t-tests. Comparing several means. Comparing proportions.
8. Analysing relationships. Paired values. Three kinds of correlation. The strength of a correlation. The significance of a correlation coefficient. Interpreting a correlation coefficient. Prediction and regression.