Course Overview
This is an introductory course in the collection, description, analysis, and summary of data. Concepts studied include graphical summaries of data, probability modelling, parameter estimation, and hypothesis testing. Statistical software (e.g. Minitab, ActivStats) is used throughout. Methodology will be applied to relevant real world examples.
Prerequisite(s)
- No prerequisites are required for this course.
Credits
4.0
- Retired
- This course has been retired and is no longer offered. Find other Flexible Learning courses that may interest you.
Learning Outcomes
At the end of this course the student will be able to:
- Prepare a comprehensive statistical description of sampled data including the calculation of appropriate measures of central tendency, dispersion, and the construction of appropriate tables and graphs.
- Discuss some of the issues and limitations associated with sampling, collecting, and interpreting data from surveys, polls, and other wood related statistical studies.
- Apply random sampling techniques to collect unbiased samples for study.
- Distinguish between discrete and continuous probability distribution models.
- Apply appropriate discrete probability models (hypergeometric or binomial) to solve a variety of industrial examples.
- Apply the normal probability distribution model to solve relevant problems.
- Calculate and interpret confidence intervals for population means and percentages.
- Apply hypothesis testing as a decision tool for problems involving population means and percentages.
- Apply the method of least squares to determine the relationship between a set of observations.
Effective as of Winter 2007
Programs and courses are subject to change without notice. Find out more about BCIT course cancellations.