The course develops quantitative and computational skills necessary in the collection, organization, and interpretation of data. Topics include techniques in sampling and data organization, measures of central tendency and dispersion, an introduction to correlation and linear regression, elementary probability, confidence intervals and an introduction to hypothesis testing. The course is project-oriented and the laboratory component emphasizes the use of calculators, computers and statistically-oriented software.
|Prerequisites:||Fundamentals of Mathematics 105 or satisfactory performance on the mathematics placement exam|
|Notes:||Recommended for first-year students; available to first-semester sophomores|