IndietroSTA 2023 Statistical Methods – Course Syllabus and Study Guide
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STA 2023 Statistical Methods – Course Syllabus and Study Guide
Course Overview
This course provides an introduction to the fundamental concepts and methods of statistics, focusing on both descriptive and inferential statistical techniques. Students will learn to analyze, interpret, and draw conclusions from data using appropriate statistical tools and technology. The course is designed for students across a variety of disciplines and emphasizes practical applications of statistical reasoning.
Course Learning Outcomes
Visualize and summarize data using descriptive statistics.
Apply basic probability concepts to draw reasonable conclusions.
Employ concepts of random variables, sampling distributions, and the central limit theorem to analyze and interpret data.
Choose and apply appropriate inferential statistical methods, including confidence intervals and hypothesis testing, to make decisions about populations based on sample data.
Model linear relationships between quantitative variables using correlation and linear regression.
Develop quantitative reasoning skills in mathematical calculations, data interpretation, and communication.
Course Topics
Chapter 1: Introduction to Statistics
Section 1.1: An Overview of Statistics
Section 1.2: Data Classification
Section 1.3: Data Collection and Experimental Design
Chapter 2: Descriptive Statistics
Section 2.1: Frequency Distributions and Their Graphs
Section 2.2: More Graphs and Displays
Section 2.3: Measures of Central Tendency
Section 2.4: Measures of Variation
Section 2.5: Measures of Position
Chapter 3: Probability
Section 3.1: Basic Concepts of Probability and Counting
Section 3.2: Conditional Probability and the Multiplication Rule
Section 3.3: The Addition Rule
Section 3.4: Additional Topics in Probability and Counting
Chapter 4: Discrete Probability Distributions
Section 4.1: Probability Distributions
Section 4.2: Binomial Distributions
Chapter 5: Normal Probability Distributions
Section 5.1: Introduction to Normal Distribution and Standard Normal Distribution
Section 5.2: Normal Distributions: Finding Probabilities
Section 5.3: Normal Distributions: Finding Values
Section 5.4: Sampling Distributions and the Central Limit Theorem
Chapter 6: Confidence Intervals
Section 6.1: Confidence Intervals for the Mean (sigma Known)
Section 6.2: Confidence Intervals for the Mean (sigma Unknown)
Section 6.3: Confidence Intervals for Population Proportions
Chapter 7: Hypothesis Testing with One Sample
Section 7.1: Introduction to Hypothesis Testing
Section 7.2: Hypothesis Testing for the Mean (sigma Known)
Section 7.3: Hypothesis Testing for the Mean (sigma Unknown)
Section 7.4: Hypothesis Testing for Proportions
Chapter 8: Hypothesis Testing with Two Samples
Section 8.1: Testing the Difference Between Means (Independent Samples, sigma Known)
Section 8.2: Testing the Difference Between Means (Independent Samples, sigma Unknown)
Section 8.3: Testing the Difference Between Means (Dependent Samples)
Section 8.4: Testing the Difference Between Proportions
Chapter 9: Correlation and Regression
Section 9.1: Correlation
Section 9.2: Linear Regression
Grading Scale
Total Average Score | Grade |
|---|---|
90% - 100% | A |
88% - 89% | B+ |
80% - 87% | B |
78% - 79% | C+ |
70% - 77% | C |
68% - 69% | D+ |
60% - 67% | D |
0% - 59% | F |
Note: Final grades are rounded to the nearest whole number (0.5 and above rounds up).
Grade Categories and Weights
Category | Weight |
|---|---|
MyMathLab Homework (2 lowest dropped) | 15% |
Lesson Assignments (Canvas Video/Quiz, Group Work/Quizzes, Explorative Activities, Individual Quizzes) | 20% |
Participation | 5% |
Chapter Exams (1 lowest dropped) | 40% |
Final Exam (cannot be dropped) | 20% |
Course Schedule (Selected Weeks)
Week | Topics/Assignments |
|---|---|
1 | Chapter 1.1-1.3 |
2 | Chapter 2.1-2.3 |
3 | Chapter 2.4-2.5 |
4 | Exam 1 (Ch. 1-2), Chapter 3.1-3.2 |
5 | Chapter 3.3-3.4 |
6 | Chapter 4.1-4.2 |
7 | Exam 2 (Ch. 3-4), Chapter 5.1-5.2 |
8 | Chapter 5.3-5.4 |
9 | Chapter 6.1-6.3 |
10 | Chapter 7.1-7.2, Exam 3 (Ch. 5-6) |
11 | Chapter 7.3-7.4 |
12 | Chapter 8.1-8.2 |
13 | Chapter 8.3-8.4 |
14 | Exam 4 (Ch. 7-8), Chapter 9.1 |
15 | Chapter 9.2, Final Exam Review |
16 | Final Exam (Ch. 1-9) |
Required Materials
Textbook: MyLab Statistics with Pearson eText (Larson, 9th Edition)
Calculator: TI-83 Plus or TI-84 graphing calculator
Attendance and Participation Policy
Attendance is recorded every class session.
Active participation in discussions and activities is required.
Arriving more than 20 minutes late or leaving early results in a zero for participation that day.
Assignment and Exam Policies
Strict deadlines for all assignments; 10% penalty per day late, not accepted after 3 days.
Make-up work allowed only with valid documentation for excused or authorized absences.
Use of unauthorized electronic devices or AI tools is strictly prohibited during exams and assignments.
Academic Integrity
This course is AI-free: No generative AI tools are permitted on any assignment.
All work must be completed independently.
Violations may result in a zero for the assignment/exam and referral for academic misconduct.
General Education Statement
This course fulfills general education requirements and aims to develop critical thinking, quantitative reasoning, and effective communication skills. It encourages inquiry, creativity, and the integration of knowledge across disciplines.
Contact and Support
Instructor: Tanya Huffman
Email: thuffman@fgcu.edu
Office: Whitaker 204
Office Hours: 9:00am-10:00am, 2:00pm-2:45pm (subject to change)
Important Dates
Last Day to Drop/Withdraw (100% Refund): August 21
Last Day to Drop/Withdraw (25% Refund): September 11
Last Day to Drop/Withdraw (0% Refund): October 23
Final Exam: December 1, 10:00am-12:15pm
