STA1010 · Statistical methods for science

Overview

Descriptive statistics, scatter plots, correlation, line of best fit. Elementary probability theory. Confidence intervals and hypothesis tests using normal, t and binomial distributions. Use of computer software. Formal treatment of statistical analyses and the role of probability in statistical inference.

Areas of study: Applied mathematics Financial and insurance mathematics Mathematical statistics Mathematics

Offerings

Assessment

The Handbook lists an examination for this unit.

Assessment details may change. Please refer to the assessment information in Moodle closer to the start of the teaching period.

Requisites

The Handbook lists no prerequisite, corequisite or prohibition for this unit.

Learning outcomes

1. Demonstrate a comprehensive understanding of the principles of statistical data collection, analysis, and interpretation using both descriptive and inferential techniques;
2. Select, justify, and apply appropriate statistical methods to solve real-world scientific problems, including hypothesis testing, estimation, and model evaluation;
3. Use Microsoft Excel and other computational tools to perform statistical analyses, generate numerical summaries, and produce effective visual representations of data;
4. Evaluate, synthesise, and communicate statistical findings clearly and effectively in written scientific reports and presentations, demonstrating critical thinking and data-driven decision-making.

Workload

• Three hours of seminars; • One 2-hour applied class (in weeks 2-12) and • 7 hours of independent study per week.

Student experience, not official rules. Nothing here changes what the Handbook says.