STAT 2300: Statistical Methods I – Syllabus and Course Overview

Course Overview

Introduction to Statistical Methods I (STAT 2300)

This course provides an introduction to the fundamental concepts and methods of statistics, focusing on statistical inference and the application of statistical techniques to real-world data. Students will learn how to collect, organize, analyze, and interpret data, as well as how to use statistical software for data analysis. The course is designed to build mathematical literacy and critical thinking skills essential for interpreting research and making informed decisions based on data.

Course Topics

• Introduction to Statistics and Data Collection

• Describing Data with Tables and Graphs

• Describing Data Numerically

• Probability and Probability Distributions

• Binomial and Normal Distributions

• Sampling Distributions

• Confidence Intervals (Means and Proportions)

• Hypothesis Testing (Means and Proportions, One and Two Samples)

• Correlation and Simple Linear Regression

Course Structure and Requirements

Prerequisites

• Credit for any MATH or STAT course, or qualifying standardized test scores.

• Not open to students with credit for MATH 3020 or STAT 3090.

Required Materials

• Course Packet (lecture notes)

• MyLab Statistics access code (with eBook: Statistics: Informed Decisions Using Data, 7th edition by Michael Sullivan)

• iClicker remote or app subscription

• Scientific or graphing calculator (e.g., TI-30 or TI-84)

• JMP® Statistical Software (free for Clemson students)

Technology Requirements

• Computer with audio, webcam, and reliable internet

• LockDown Browser for exams

• Regular access to Canvas and university email

Course Learning Objectives

• Distinguish between populations and samples; explain statistical inference

• Design and conduct data collection for clear answers to research questions

• Identify variable types and select appropriate statistical techniques

• Create and interpret graphical and numerical data summaries

• Apply probability rules and understand probability distributions

• Understand sampling distributions and their role in inference

• Calculate and interpret confidence intervals for means and proportions

• Conduct hypothesis tests and draw conclusions

• Analyze relationships between quantitative variables using regression

Grading Scheme

Component	Weight
Lab Assignments	20%
MyLab Stat Homework	15%
Section Grade (in-class activities/polls)	5%
Exams (Best 3 of 3 unit tests and final exam)	60%
Total	100%

Grading Scale: A: 90–100, B: 80–89, C: 70–79, D: 60–69, F: below 60

Course Schedule (Selected Topics)

Week	Lecture Topics	Lab Topics
1	Syllabus & Introduction, Data Collection	Introduction to Statistics & JMP
2	Describing Data (Tables, Graphs)	Descriptive Statistics
3	Numerical Summaries	Comparing Distributions & Regression
4	Probability Concepts	Probability
5	Discrete & Binomial Distributions	Discrete Probability Distributions
6	Normal Distribution	Normal Distribution
7	Sampling Distributions & Confidence Intervals	Confidence Intervals
8	Hypothesis Testing	Hypothesis Tests
9	Correlation & Regression	Review & Application

Additional info: The full schedule includes exam dates, holidays, and deadlines for assignments. Refer to Canvas for the most up-to-date schedule and materials.

Academic Integrity and Policies

• Strict adherence to Clemson University’s academic integrity policy is required.

• AI tools are not permitted on exams or lab assignments; limited use is allowed for homework with proper understanding.

• Accommodations are available for students with disabilities through Student Accessibility Services.

• Emergency procedures and academic continuity plans are in place for disruptions.

Student Support Resources

• Math/Stat Help Center: Drop-in homework help

• Academic Success Center: Tutoring, PAL, academic coaching, workshops

• Writing Lab: Assistance with writing assignments

• Clemson Libraries: Research, citation, and data visualization support

• Technical Support: IT Help Desk, Canvas guides

Important Dates

• Last day to add a class: August 25

• Last day to drop without a W: September 2

• Last day to withdraw without final grades: October 27

• Unit Tests: September 22, October 27, December 1

• Final Exam: December 7

Contact Information

• Instructor: Sanduni Caldera ([e-mail])

• Office: Martin M-306, Office Hours: Monday 2:15–3:15 PM

• Course Coordinator: Dr. Paran Norton ([e-mail])

For full details, refer to the official course syllabus and Canvas site.