MAT 127 – Introductory Statistics with Probability: Syllabus and Course Structure Overview

Course Overview

This study guide summarizes the structure, objectives, and content outline for MAT 127 – Introductory Statistics with Probability, as offered at SUNY Adirondack. The course provides foundational knowledge in statistics, focusing on data collection, graphical and numerical data summaries, probability, distributions, inferential statistics, and regression analysis.

Course Objectives and Student Learning Outcomes (SLOs)

• Interpret and draw inferences from mathematical models, including formulas, graphs, and tables.

• Represent mathematical information symbolically, visually, numerically, and verbally.

• Employ quantitative methods such as arithmetic, algebra, geometry, and statistics to solve problems.

• Construct and interpret statistical graphs and numerical statistics.

• Describe and distinguish between observational studies and experiments.

• Identify and demonstrate correct sampling methods.

• Apply basic probability rules.

• Perform normal and uniform distribution calculations, including finding areas and percentiles.

• Construct sampling distributions for sample means and proportions.

• Construct confidence intervals and perform significance tests for population means and proportions, including calculating p-values.

• Interpret confidence intervals and significance tests.

• Explain correlation and perform linear regression analysis.

• Recognize limitations of statistical methods.

Course Content Outline

The following table summarizes the weekly topics and their alignment with standard statistics curriculum chapters:

Week	Topics	Relevant Chapters
1	Data Collection	Ch. 1 - Data Collection
2	Graphically Summarizing Data	Ch. 2 - Summarizing Data in Tables and Graphs
3-4	Numerical Summaries	Ch. 3 - Numerically Summarizing Data
5	Probability	Ch. 5 - Probability
6-7	The Normal Probability Distribution	Ch. 7 - The Normal Probability Distribution
8	Sampling Distributions	Ch. 8 - Sampling Distributions
9-10	Confidence Intervals	Ch. 9 (not listed above, but standard in statistics)
11-12	Hypothesis Tests	Ch. 10 - Hypothesis Tests Regarding a Parameter
13	Correlation and Regression	Ch. 4 - Describing the Relation between Two Variables

Additional info: Confidence intervals are typically covered in a dedicated chapter (often Ch. 9), though not explicitly listed in the provided chapter titles.

Assessment and Grading

• Comprehensive Final Exam: 30%

• Midterm Exam: 25% (4 tests will be given)

• Weekly Quizzes: 30% (lowest quiz grade dropped)

• Online Homework Assignments: 10%

• Online Discussion and Participation: 5%

All major exams are proctored and must be taken in person or through approved proctoring services. No late work or make-up tests are allowed except in cases of official Incomplete status.

Course Policies and Expectations

• Academic Integrity: Cheating or plagiarism results in a failing grade and referral to the Dean for Academic Affairs.

• Attendance: Active participation is required; non-attendance may result in withdrawal and loss of financial aid.

• Disability Services: Accommodations are available through the Accessibility Services Office.

• Recording Policy: Audio/video recording is prohibited without explicit permission or approved accommodation.

• Student Support: Math Lab and Community Hub services are available for academic and basic needs support.

Required Materials

• Textbook: Fundamentals of Statistics, Sixth Edition (2022), by Michael Sullivan, III with MyStatLab Access Code

• Calculator: Any TI-83 or TI-84 graphing calculator

Summary of Key Topics (with Reference to Standard Chapters)

• Ch. 1: Data Collection – Sampling methods, observational studies, and experiments.

• Ch. 2: Summarizing Data in Tables and Graphs – Frequency tables, histograms, bar charts, and pie charts.

• Ch. 3: Numerically Summarizing Data – Measures of central tendency (mean, median, mode), measures of spread (variance, standard deviation, range).

• Ch. 4: Describing the Relation between Two Variables – Scatterplots, correlation, and regression analysis.

• Ch. 5: Probability – Basic probability rules, events, and counting techniques.

• Ch. 6: Discrete Probability Distributions – Binomial and other discrete distributions.

• Ch. 7: The Normal Probability Distribution – Properties of the normal curve, z-scores, and applications.

• Ch. 8: Sampling Distributions – Central Limit Theorem, distribution of sample means and proportions.

• Ch. 10: Hypothesis Tests Regarding a Parameter – Steps of hypothesis testing, significance levels, p-values.

• Ch. 11: Inference on Two Population Parameters – Comparing means and proportions between groups.

• Ch. 12: Additional Inferential Methods – Other statistical inference techniques as time permits.

Important Dates

• Midterm Exam: Week 7 (3/4 or 3/5)

• Final Exam: Week 15 (5/6 or 5/7)

Conclusion

This syllabus provides a comprehensive overview of the topics, expectations, and structure for MAT 127. Students are encouraged to use this guide to track their progress and ensure mastery of each statistical concept as outlined in the course calendar.