STAT-C1000 Introductory Statistics Syllabus and Course Structure Study Guide

Course Overview

Introduction to STAT-C1000

STAT-C1000 is an introductory statistics course offered at Glendale Community College, designed to provide students with foundational knowledge in statistics and data analysis. The course is delivered asynchronously online, utilizing lecture videos, guided notes, and the MyLab online platform for assignments and assessments. The electronic textbook used is Informed Decisions Using Data by Sullivan Michael, III (7th Edition).

• Course Duration: 8 weeks (August 31 – October 24, 2026)

• Delivery Mode: 100% online, asynchronous

• Instructor: Zorayr Nalbandyan

• Assessment Platform: MyLab (Pearson)

• Statistical Software: StatCrunch (free via MyLab)

Course Learning Outcomes (CLOs)

Key Objectives

Upon successful completion of STAT-C1000, students will be able to:

• Analyze and describe studies, data sets, and probability models.

• Apply confidence intervals and hypothesis testing to form conclusions about realistic data.

These outcomes align with the following core chapters in introductory statistics:

• Ch. 1 - Data Collection

• Ch. 2 - Organizing and Summarizing Data

• Ch. 3 - Numerically Summarizing Data

• Ch. 5 - Probability

• Ch. 6 - Discrete Probability Distributions

• Ch. 7 - The Normal Probability Distribution

• Ch. 8 - Sampling Distributions

• Ch. 9 - Estimating the Value of a Parameter

• Ch. 10 - Hypothesis Tests Regarding a Parameter

• Ch. 11 - Inference on Two Population Parameters

Course Structure and Assessment

Assessment Components

The course is structured around several assessment types, each contributing to the final grade:

• Homework Assignments (10%): Assigned for each section via MyLab, essential for learning and exam preparation.

• Chapter Quizzes (15%): One quiz per chapter, with two lowest scores dropped.

• In-Person Exams (45%): Three exams covering Chapters 1–11 (excluding Chapter 4), lowest score dropped.

• Final Exam (30%): Cumulative, in-person, mandatory attendance.

Exam Schedule and Coverage

• Exam 1: Chapters 1–3, 5

• Exam 2: Chapters 6–8

• Exam 3: Chapters 9–11

• Final Exam: Cumulative (Chapters 1–11, excluding Chapter 4)

Grading Scale

Grade	Percentage
A	90-100%
B	80-89%
C	70-79%
D	60-69%
F	59% and below

Course Materials and Technology

Required and Recommended Resources

• Textbook: Electronic version of "Informed Decisions Using Data" (Sullivan, 7th Edition)

• MyLab Access: Required for homework, quizzes, and exams

• StatCrunch: Free statistics software for advanced calculations and graphing

• Graphing Calculator: Recommended for manual calculations

• Formula Card: Allowed during exams (8.5 x 11 inches, both sides)

Technology Requirements

• Reliable computer and internet access

• Up-to-date browser (Chrome or Firefox recommended)

• Regular use of Canvas for course materials and announcements

• Valid GCC email account

Course Topics and Chapter Coverage

Core Chapters (Based on Syllabus and Exam Coverage)

• Ch. 1 - Data Collection: Methods for gathering data, types of studies, sampling techniques.

• Ch. 2 - Organizing and Summarizing Data: Frequency tables, graphical representations (histograms, bar charts).

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

• Ch. 5 - Probability: Basic probability concepts, rules, and models.

• Ch. 6 - Discrete Probability Distributions: Binomial, Poisson distributions.

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

• Ch. 8 - Sampling Distributions: Distribution of sample statistics, Central Limit Theorem.

• Ch. 9 - Estimating the Value of a Parameter: Confidence intervals for means and proportions.

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

• Ch. 11 - Inference on Two Population Parameters: Comparing means/proportions from two populations.

Additional info: Chapter 4 (Describing the Relation Between Two Variables) is excluded from exam coverage, but may be included in homework or quizzes.

Study and Success Strategies

Recommended Practices

• Watch lecture videos and take handwritten notes for each section.

• Read guided notes and textbook sections for deeper understanding.

• Complete all homework assignments before attempting quizzes and exams.

• Utilize StatCrunch for statistical calculations and graphing.

• Attend office hours or visit the Math Discovery Center for additional support.

• Maintain a consistent study schedule (recommended 10–20 hours per week).

• Develop critical thinking and growth mindset through "exploring" exercises.

Academic Policies and Resources

Important Policies

• Drop Policy: Drop early if unable to keep up; deadlines provided in syllabus.

• Cheating Policy: Academic dishonesty results in zero grade and possible expulsion.

• Accommodation: Students with disabilities should contact the Center for Students with Disabilities for timely arrangements.

Support Resources

• Math Discovery Center (MDC): Remote assistance for homework and study.

• Canvas and Zoom tutorials available for technical support.

Registration Instructions for MyLab

Step-by-Step Guide

1. Go to Pearson MyLab Enrollment.

2. Sign in with your Pearson student account or create a new account.

3. Select access option: enter prepaid code, buy instant access, or get temporary access.

4. Go to your course: Stat 1000C-Online-GCC-Fall 2026.

5. For support, provide course ID: nalbandyan62387.

Summary Table: Course Assessment Breakdown

Assessment	Weight
Homework	10%
Chapter Quizzes	15%
Exams	45%
Final Exam	30%
Total	100%

Conclusion

STAT-C1000 provides a comprehensive introduction to statistics, covering essential topics such as data collection, probability, statistical inference, and hypothesis testing. Success in the course requires consistent engagement with lecture materials, completion of assignments, and utilization of available resources. The course emphasizes both conceptual understanding and practical application using statistical software.