A data-driven introduction to statistics. Basic descriptive statistics, introduction to probability theory, random variables, discrete and continuous distributions, contingency tables, sampling distributions, distribution of sample mean, Central Limit Theorem, interval estimation and hypothesis testing. A statistical software package will be used. Includes: Experiential Learning Activity Precludes additional credit for BIT 2000, BIT 2009, BIT 2100 (no longer offered), BIT 2300 (no longer offered), DATA 1517, ECON 2201 (no longer offered), ECON 2210, ENST 2006, GEOG 2006, STAT 2601, STAT 2606, and STAT 3502. May not be counted for credit in any program if taken after successful completion of STAT 2559. Prerequisite(s): an Ontario Grade 12 university- preparation Mathematics or equivalent, or permission of the School of Mathematics and Statistics. Lectures three hours a week, laboratory one hour a week.
A data-driven introduction to statistics. Basic descriptive statistics, introduction to probability theory, random variables, discrete and continuous distributions, contingency tables, sampling distributions, distribution of sample mean, Central Limit Theorem, interval estimation and hypothesis testing. A statistical software package will be used. Includes: Experiential Learning Activity Precludes additional credit for BIT 2000, BIT 2009, BIT 2100 (no longer offered), BIT 2300 (no longer offered), DATA 1517, ECON 2201 (no longer offered), ECON 2210, ENST 2006, GEOG 2006, STAT 2601, STAT 2606, and STAT 3502. May not be counted for credit in any program if taken after successful completion of STAT 2559. Prerequisite(s): an Ontario Grade 12 university- preparation Mathematics or equivalent, or permission of the School of Mathematics and Statistics. Lectures three hours a week, laboratory one hour a week.
