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

Department

• Mathematics

Semesters Course Will Be Offered

• Fall
• Spring

For more detailed course information view the 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.

Topic Outline

1. 1. Sample variability
2.     a. Sampling distributions
3.     b. The central limit theorem
4.     c. Applications of the central limit theorem
5. 2. Introduction to statistical inference
6.     a. The nature of hypothesis testing
7.     b. The hypothesis test: classical and probability-value approaches
8.     c. Estimation
9. 3. Inferences involving one population
10.     a. Inferences about the population mean
11.     b. Inferences about proportions (mention confidence intervals)
12.     c. Inferences about variance and standard deviation
13. 4. Inferences involving two populations
14.     a. Independent and dependent samples
15.     b. Inferences concerning the difference between two independent means (large samples)
16.     c. Inferences concerning two variances
17.     d. Inferences concerning the difference between two independent means (small samples)
18.     e. Inferences concerning two dependent means
19.     f. Inferences concerning two proportions
20. 5. Additional applications of chi-square
21.     a. Chi-square statistic
22.     b. Inferences concerning multinomial experiments
23.     c. Inferences concerning contingency tables
24. 6. Analysis of variance
25.     a. Introduction to the analysis of variance technique
26.     b. The logic behind ANOVA
27.     c. Applications of single-factor ANOVA