The course provides students with a detailed overview of methods for statistical modeling and inference. The course focuses on fundamental data science topics such as descriptive analysis, basic probability theory, parameter estimation, procedures for making inference, and regression analysis. Throughout the course, students will make use of statistical software for data handling tasks and model estimation.
- Univariate and bivariate descriptive statistics and plots.
- Causation, randomization, sampling, bias and variability.
- Probability models, random variables, characteristics of random variables, and linear combinations of random variables.
- The distribution of the sample mean and the central limit theorem.
- Parameter estimation.
- Inference under exact normality and inference under more realistic conditions.
- Linear regression analysis.
- One-way ANOVA.
This is an excerpt from the complete course description for the course. If you are an active student at BI, you can find the complete course descriptions with information on eg. learning goals, learning process, curriculum and exam at portal.bi.no. We reserve the right to make changes to this description.