Description
This course covers statistical data analysis with an emphasis on hypothesis testing including parametric tests (e.g., t-tests, ANOVA) and non-parametric tests (e.g., Kruskal-Wallis, Friedman, chi-square), correlation and linear regression. Provides an introduction to probability theory and distributions (e.g. binomial, normal).
Prerequisites
- Prerequisite(s): Restricted to students in the BIT degree program.
Conditions and arrangements
- Precludes additional credit for Precludes additional credit for BIT 2000 , DATA 1517 , ECON 2210 , ENST 2006 , GEOG 2006 , STAT 2507 , STAT 2606, and STAT 3502 .
- Prerequisite(s): Restricted to students in the BIT degree program.
- Lectures three hours a week, tutorial/laboratory one hour a week.
Reference text in its original language
This course covers statistical data analysis with an emphasis on hypothesis testing including parametric tests (e.g., t-tests, ANOVA) and non-parametric tests (e.g., Kruskal-Wallis, Friedman, chi-square), correlation and linear regression. Provides an introduction to probability theory and distributions (e.g. binomial, normal).
- Prerequisite(s): Restricted to students in the BIT degree program.
- Precludes additional credit for Precludes additional credit for BIT 2000 , DATA 1517 , ECON 2210 , ENST 2006 , GEOG 2006 , STAT 2507 , STAT 2606, and STAT 3502 .
- Lectures three hours a week, tutorial/laboratory one hour a week.
Sources and references
Dates and sources are retained to help you verify the information. Translations are provided to facilitate reading; the official source governs conditions and requirements.
Source reference : https://calendar.carleton.ca/undergrad/courses/BIT/