Untitled

APPLY NOW

Web Schedules

Fall 2026
Spring 2026
Summer 2026

One Credit Courses

Fall 2026
Spring 2026
Summer 2026

No Cost Textbook/Resources Courses

Fall 2026
Spring 2026
Summer 2026

Low Cost Textbook/Resources Courses

Fall 2026
Spring 2026
Summer 2026

Course Planning by Program

2026-27

Essential Objectives

Course Syllabus


Revision Date: 18-Jun-26
 

Fall 2026 | MAT-2021-VO02 - Statistics


Online Class

Online courses take place 100% online via Canvas, without required in-person or Zoom meetings.

Location: Online
Credits: 3 (45 hours)
Day/Times: Meets online
Semester Dates: 09-08-2026 to 12-21-2026
Last day to add this section: 09-17-2026
Last day to drop without a grade: 09-21-2026 - Refund Policy
Last day to withdraw (W grade): 11-09-2026 - Refund Policy
This section is waitlisted (0). Please contact your nearest center for availability.

Faculty

Bill Sacco
View Faculty Credentials
View Faculty Statement
Hiring Coordinator for this course: Julie Dalley

General Education Requirements


This section meets the following CCV General Education Requirement(s) for the current catalog year:
Mathematics
    Note
  1. Many degree programs have specific general education recommendations. In order to avoid taking unnecessary classes, please consult with additional resources like your program evaluation, your academic program catalog year page, and your academic advisor.
  2. Courses may only be used to meet one General Education Requirement.

Course Description

This course is an introduction to the basic ideas and techniques of probability and statistics. Topics may include numerical and graphical descriptive measures, probability, random variables, the normal distribution, sampling theory, estimation, hypothesis testing, correlation, and regression. The use of technology may be required. Prerequisite: Math & Algebra for College or equivalent skills.


Essential Objectives

1. Outline the general development of statistical science and list a number of common applications of statistical methodology.
2. Distinguish between descriptive and inferential statistics.
3. Create and apply various techniques used to describe data, such as pie charts, bar graphs, frequency tables, and histograms.
4. Define three common measures of central tendency (mean, median, and mode), and demonstrate the ability to calculate each manually from a series of small data sets.
5. Describe common methods of measuring variability, including range, percentiles, variance, and standard deviation and calculate each from a series of small data sets.
6. Explain the Normal Probability Distribution, techniques of sampling, the Central Limit Theorem, and the concept of standard error, and compute probabilities associated with normally distributed samples.
7. Test hypotheses about the value of the mean assuming the normal distribution and large sample results.
8. Select and perform common statistical tests including one- and two-tailed tests.
9. Define linear regression and correlation and discuss their applications.
10. Interpret and evaluate the validity of statistical data and reports.
11. Demonstrate proficiency in understanding, interpreting, evaluating and applying quantitative data and information.
12. Apply mathematical reasoning to analyze social justice problems in a variety of different contexts and consider whether these approaches are just and equitable.


Required Technology

More information on general computer and internet recommendations is available on the CCV computer recommendations Support page.

Please see CCV's Digital Equity Statement (pg. 45) to learn more about CCV's commitment to supporting all students access the technology they need to successfully finish their courses.


Required Textbooks and Resources


*** This is a no cost textbook or resource class. ***

This course only uses free Open Educational Resources (OER) and/or library materials. For details, see the Canvas Site for this class.


Artificial Intelligence(AI) Policy Statement

CCV recognizes that artificial intelligence (AI) and generative AI tools are widely available and becoming embedded in many online writing and creative applications.

Prohibited: The use of generative AI is not allowed in this course, with the exception of spellcheck, grammar check and similar tools. This course rests in the value of students engaging in the learning process without relying on AI-generated content. Students will develop critical thinking and problem-solving skills independently, owning their learning journey from start to finish. If you use these tools, your actions would be considered academically dishonest and a violation of CCV's Academic Integrity Policy.

This course allows the student to utilize class notes and the course textbook when taking course quizzes and exams. There are number of statistical theories that are slightly different form each other and can lead to different answers on some questions. In this course we will only utilize the formula's and principles stated in the course textbook and my weekly class notes.

The student project must be completed by the student to a specific format that most AI routines will not incorporate per the requirements of the project resulting in the student possibly receiving a failing grade for the project.



Methods

TEACHING METHODS:

1 . Discussion - Online discussion forum for weekly topics on statistical principles.

2. Readings in textbook and review of select videos (links in Canvas)

3. Completion of selected statistical problems. This include completing assignments and quizzes in Canvas.

4. Review of statistical data and reports from various sources.

5. Individual projects.


Evaluation Criteria

EVALUATION CRITERIA:

Grades will be comprised of:

Canvas Assignments and Quizzes 20%

Midterm Exam 25%

Final Exam 25%

Project 20%

Weekly Participation in class online discussion forums 10%


Grading Criteria

CCV Letter Grades as outlined in the Evaluation System Policy are assigned according to the following chart:

 HighLow
A+10098
A Less than 9893
A-Less than 9390
B+Less than 9088
B Less than 8883
B-Less than 8380
C+Less than 8078
C Less than 7873
C-Less than 7370
D+Less than 7068
D Less than 6863
D-Less than 6360
FLess than 60 
P10060
NPLess than 600


Weekly Schedule


Week/ModuleTopic  Readings  Assignments
 

1

Sampling and Data

  

Chapter 1 of course text "Introductory Statistics" from OpenStax.

Link to course text pdf file:Introductory Statistics - OpenStax

  

Individual Student Exercise.

 

2

Descriptive Statistics

  

Chapter 2 of course text "Introductory Statistics" from OpenStax.

Link to course text pdf file:Introductory Statistics - OpenStax

  

Individual Student Exercise.

 

3

Probability Topics

  

Chapter 3 of course text "Introductory Statistics" from OpenStax.

Link to course text pdf file:Introductory Statistics - OpenStax

  

Individual Student Exercise.

 

4

Discrete Random Variables

  

Chapter 4 (Sections 4-1, 4-2 and 4-3 Only) of course text "Introductory Statistics" from OpenStax.

Link to course text pdf file:Introductory Statistics - OpenStax

  

Online Quiz

 

5

Continuous Random Variables

  

Chapter 5 (Sections 5-1 and 5-2 Only) of course text "Introductory Statistics" from OpenStax.

Link to course text pdf file:Introductory Statistics - OpenStax

  

Individual Student Exercise.

 

6

The Normal Distribution

  

Chapter 6 of course text "Introductory Statistics" from OpenStax.

Link to course text pdf file:Introductory Statistics - OpenStax

  

Individual Student Exercise.

 

7

Mid-Term Exam

  

Exam is on Chapter's 1 thru 6 of the course text.

  

Take online Mid-Term Exam

 

8

The Central Limit Theorem

  

Chapter 7 of course text "Introductory Statistics" from OpenStax.

Link to course text pdf file:Introductory Statistics - OpenStax

  

Online Quiz

 

9

Confidence Intervals

  

Chapter 8 of course text "Introductory Statistics" from OpenStax.

Link to course text pdf file:Introductory Statistics - OpenStax

  

Online Quiz

 

10

Hypothesis Testing with One Sample

  

Chapter 9 of course text "Introductory Statistics" from OpenStax.

Link to course text pdf file:Introductory Statistics - OpenStax

  

Individual Student Exercise.

 

11

Hypothesis Testing with Two Sample

  

Chapter 10 of course text "Introductory Statistics" from OpenStax.

Link to course text pdf file:Introductory Statistics - OpenStax

  

Individual Student Exercise.

 

12

The Chi-Square Distribution (Section 5-1)

Begin Linear Regression (Sections 12-1 and 12-2)

  

Chapter 11 of course text "Introductory Statistics" from OpenStax.

Link to course text pdf file:Introductory Statistics - OpenStax

  

Online Quiz

 

13

Linear Regression and Correlation

Sections 12-3 thru 12-6

  

Chapter 12 of course text "Introductory Statistics" from OpenStax.

Link to course text pdf file:Introductory Statistics - OpenStax

  

Online Quiz

 

14

Individual Student Class Projects Due

  

Submitted projects must meet the format established in Canvas. This format and a sample project for guidance are in the Course Resource Page that is found in the modules section (at the top) on the course canvas page.

  

Submit Student Project

 

15

Final Exam

    

Take online Final Exam

 

Attendance Policy

Regular attendance and participation in classes are essential for success in and are completion requirements for courses at CCV. A student's failure to meet attendance requirements as specified in course descriptions will normally result in a non-satisfactory grade.

  • In general, missing more than 20% of a course due to absences, lateness or early departures may jeopardize a student's ability to earn a satisfactory final grade.
  • Attending an on-ground or synchronous course means a student appeared in the live classroom for at least a meaningful portion of a given class meeting. Attending an online course means a student posted a discussion forum response, completed a quiz or attempted some other academically required activity. Simply viewing a course item or module does not count as attendance.
  • Meeting the minimum attendance requirement for a course does not mean a student has satisfied the academic requirements for participation, which require students to go above and beyond simply attending a portion of the class. Faculty members will individually determine what constitutes participation in each course they teach and explain in their course descriptions how participation factors into a student's final grade.


Missing & Late Work Policy

  • Course Quizzes and Assignments scheduled prior to the midterm exam must be completed and submitted by 10/26/2026. No submissions on this material will be accepted after that date.
  • Course Quizzes and Assignments sheduled after the midterm exam including student projects must be completed and submitted by 12/14/2026. No submissions onthis material will be accepted after that date.
  • Note: The course Mid-Term and Final Exams must be taken in the week they are assigned! The course Mid-Term exam must be completed and submitted by 10/26/2026. The course final exam must be completed and submitted by 12/21/2026
  • Late work is not accepted in the discussion forum. Interacting with classmates is an essential part of online discussions and cannot be made up after the fact. The discussion forum will account for your class participation grade. The class participation grade will account for 10% of your total grade.
  • Extensions will be granted only in extreme extenuating circumstances. If a medical problem or other emergency, personal issue will result in missing weekly discussions and/or assignments, please contact your instructor and student advisor as soon as possible. Generally speaking extensions will not be granted.

Accessibility Services for Students with Disabilities:


CCV strives to mitigate barriers to course access for students with documented disabilities. To request accommodations, please
  1. Provide disability documentation to the Accessibility Coordinator at your academic center. https://ccv.edu/student-support/accessibility-services/
  2. Request an appointment to meet with accessibility coordinator to discuss your request and create an accommodation plan.
  3. Once created, students will share the accommodation plan with faculty. Please note, faculty cannot make disability accommodations outside of this process.


Academic Integrity


CCV has a commitment to honesty and excellence in academic work and expects the same from all students. Academic dishonesty, or cheating, can occur whenever you present -as your own work- something that you did not do. You can also be guilty of cheating if you help someone else cheat. Being unaware of what constitutes academic dishonesty (such as knowing what plagiarism is) does not absolve a student of the responsibility to be honest in his/her academic work. Academic dishonesty is taken very seriously and may lead to dismissal from the College.

Apply Now for this semester.

Register for this semester: March 30 - December 21, 2026