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Statistics Syllabus and Course Structure: Foundations, Content, and Policies

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Course Overview

Prerequisite

This course requires successful completion of MATH 151 or higher, or equivalent placement. Credit will not be granted for both MATH 130 and MATH 235.

Course Content

Statistics is the art and science of collecting, organizing, and interpreting data. It provides a way to reason in the face of uncertainty and chance. The course covers:

  • Descriptive statistics: Methods for summarizing and describing data, including graphical and numerical techniques.

  • Inferential statistics: Drawing conclusions and making predictions based on data samples.

  • Probability: The mathematical foundation for statistical inference, including random variables and probability distributions.

  • Statistical significance: Understanding differences and relationships between data sets.

Course Goals and Objectives

Learning Outcomes

The main goal is to help students become knowledgeable consumers of statistics. Upon completion, students will be able to:

  • Interpret and summarize data using statistical methods.

  • Use basic tools to assess the likelihood of chance events.

  • Evaluate statistical arguments and communicate with statistics.

  • Utilize basic statistical software and internet resources for statistical analysis.

Textbook and Materials

Required Text

  • Textbook: The Art and Science of Learning from Data, 5th edition, by Agresti, Franklin, Klingenberg.

  • MyStatLab online homework system (Course ID: tyson87772).

Coursework and Grading

Assignments and Participation

  • Active participation is expected in all aspects of the course.

  • Assignments include homework, quizzes, and review assignments focusing on course material and statistical software.

  • Exams are scheduled throughout the semester and are cumulative.

Grading Scale

Grade

Description

A

Excellent performance

B

Good performance

C

Acceptable performance

D

Poor performance

F

Failing performance

Approximate Grade Distribution

Component

Points

Percentage of Grade

Exams (3)

100 points each

~46% of overall grade

Review assignments

100 points total

~15% of overall grade

MyStatLab assignments

100 points total

~15% of overall grade

Attendance, class, etc.

30 points total

~7% of overall grade

Comprehensive final exam

120 points

~17% of overall grade

Course Schedule (Selected Topics)

Week

Date

Topic

Assignments/Exams

1

Wed Aug 21

Introduction, Syllabus, Data Basics

2

Wed Aug 28

Different Types of Data, Graphical Summaries

3

Wed Sep 4

Measuring Center of Quantitative Data, Numerical Summaries

MyStatLab Ch.2 HW

4

Wed Sep 11

Association Between Two Categorical Variables, Predicting Outcomes

MyStatLab Ch.2 HW

5

Wed Sep 18

Association Between Two Quantitative Variables, Regression

MyStatLab Ch.3 HW

6

Wed Sep 25

Probability, Randomness

MyStatLab Ch.4 HW

10

Wed Oct 9

Exam 1 (Chs.1,2,3,4)

Exam 1

14

Wed Oct 23

Probabilities for Well-Shaped Distributions, The Normal Distribution

MyStatLab Ch.6 HW

17

Wed Nov 6

Probabilities When Each Observation Has Two Possible Outcomes

Exam 2

21

Wed Nov 20

Significance Tests About Proportions

MyStatLab Ch.9 HW

28

Wed Dec 11

Review for Final Exam

MyStatLab Ch.10 HW

Key Statistical Concepts

Descriptive Statistics

Descriptive statistics summarize and describe the main features of a data set. Common measures include:

  • Mean: The average value, calculated as

  • Median: The middle value when data are ordered.

  • Mode: The most frequently occurring value.

  • Standard deviation: Measures the spread of data,

Inferential Statistics

Inferential statistics use sample data to make generalizations about a population. Key concepts include:

  • Hypothesis testing: Assessing evidence against a null hypothesis.

  • Confidence intervals: Estimating population parameters with a range of values.

  • Significance tests: Determining if observed differences are likely due to chance.

Probability

Probability quantifies the likelihood of events. Important formulas:

  • Probability of event A:

  • Normal distribution:

University Policies and Support

  • Attendance is required; participation is essential for success.

  • Academic honesty is expected; violations may result in disciplinary action.

  • Disability accommodations are available through the Office of Learning Services.

  • Math Assistance Center provides tutoring and support for statistics and mathematics courses.

Important Dates

  • Last day to drop/add a class: Tuesday, September 02, 2025

  • Last day to withdraw from a class: Friday, October 31, 2025

Additional info:

  • Some details about weekly topics and assignments were inferred from the schedule and standard statistics curriculum.

  • Key formulas and definitions were added for completeness and study utility.

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