MAT-122 Introductory Statistics II

A continuation of Introductory Statistics I (MAT-121) with an introduction to statistical research. Topics of statistical inference included are hypothesis testing and estimation for means, proportions, and variances; determination of sample size; uses of the Chi-square distribution; analysis of variance; and statistical research. The course will emphasize computer or calculator use (graphing calculator, Minitab, Excel, StatCrunch, etc.) to obtain results. This course carries SUNY General Education Mathematics (and Quantitative Reasoning) credit.

Credits

3

Prerequisite

MAT-121

Lecture Contact Hours

3

Lab Contact Hours

0

Other Contact Hours

0

Department

• Mathematics

Grading Scheme

• Letter

SUNY Gen Ed Credit

• Yes

Semesters Course Will Be Offered

• Fall
• Spring

Course Learning Outcomes

1. Understand and apply the Central Limit Theorem.
2. Select the appropriate probability distribution by validating the necessary conditions.
3. Build a confidence interval to estimate a population parameter and interpret the result.
4. Construct a hypothesis test to determine the validity of a claim.

View Course Outline

MAT 122: Introductory Statistics II

Department

Mathematics

Course Description

A continuation of Introductory Statistics I (MAT-121) with an introduction to statistical research. Topics of statistical inference included are hypothesis testing and estimation for means, proportions, and variances; determination of sample size; uses of the Chi-square distribution; analysis of variance; and statistical research. The course will emphasize computer or calculator use (graphing calculator, Minitab, Excel, StatCrunch, etc.) to obtain results. This course carries SUNY General Education Mathematics (and Quantitative Reasoning) credit.

Credit Hours

3

Contact Hours

Lecture	3
Lab	0
Other	0

Grading Scheme

Letter

Semester(s) Course Will Be Offered

Fall, Spring

Prerequisites

MAT-121

SUNY General Education Course

• Mathematics and Quantitative Reasoning

Course Learning Outcomes

1. Understand and apply the Central Limit Theorem.
2. Select the appropriate probability distribution by validating the necessary conditions.
3. Build a confidence interval to estimate a population parameter and interpret the result.
4. Construct a hypothesis test to determine the validity of a claim.