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2025-26

Essential Objectives

Course Syllabus


Revision Date: 24-Dec-24
 

Statistics




Credits:
Semester Dates: Last day to drop without a grade: 02-03-2025 - Refund Policy
Last day to withdraw (W grade): 03-24-2025 - Refund Policy
This course has started, please contact the offering academic center about registration

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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. Students must take a math assessment for placement purposes prior to registration. 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 course uses one or more textbooks/books/simulations.

Spring 2025 textbook details will be available on 2024-12-06. On that date a link will be available below that will take you to eCampus, CCV's bookstore. The information provided there will be specific to this class. Please see this page for more information regarding the purchase of textbooks/books.

The last day to use a Financial Aid Advance to purchase textbooks/books is the 3rd Tuesday of the semester. See your financial aid counselor at your academic center if you have any questions.


Methods

  • Lecture and Notetaking including examples and guided practice assessments
  • Hands on activities including technology and manipulatives
  • Working with a partner or in small groups.
  • Ongoing reflection in my teaching, and constantly checking students' understanding of the topic material and helping them if needed.

Evaluation Criteria

Evaluation Criteria

  • Weekly Class Attendance & Participation 20%

  • Homework 20%

  • Quizzes 25%

  • Tests 20%

  • Extra Practice:handout Assignments, and/or Khan Academy 5%

  • Final 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

Chapter 1: Introduction to statistics

1.1 Overview of Statistics

1.2 Data Classification

  

Elementary Statistics textbook,(by Larson and Farber, 6th edition ISBN13: 9780321911216), pages: 1-16.

  

Week's Assignment 1 Packet handout.

 

2

1.3 Data Collection and Experimental Design

  

Elementary Statistics textbook, pages: 17-28

  

Week's Assignment 2 Packet handout

 

3
  • Chapter 1 Review
  • Chapter Quiz
  

Elementary Statistics textbook, pages: 29-33

  

Quiz 1.

Test 1 Review

 

4
  • Test 1
  • Chapter 2: Descriptive Statistics
    2.1 Frequency Distributions and their Graphs
  

Elementary Statistics textbook, pages: 38-40.

  

Week's Assignment 3 Packet handout.

 

5

2.2 More Graphs and Displays

2.3 Measures of Central Tendency

  

Elementary Statistics textbook, pages: 40-81

  

Week's Assignment 4 Packet handout.

 

6

2.4 Measures of Variation

2.5 Measures of Position

  

Elementary Statistics texbook, pages: 82-102

  

Week's Assignment 5 Packet handout

 

7

Chapter 2 Summary

  • Chapter 2 Review
  • Quiz 2
  

Elementary Statistics textbook

  

Quiz 2.

Test 2 Review.

 

8

Test 2

Chapter 3: Probability

3.1 Basic Concepts of Probability and Counting

  

Elementary Statitistics textbook, pages: 128-146

  

Week's Assignment 6 Packet handout

 

9

3.2 Conditional Probability and the Multiplication Rule

3.3 The Additional Rule

  

Elementary Statistics textbook, pages: 147-167

  

Week's Assignment 7 Packet handout

 

10
  • Chapter 3 Summary
  • Quiz 3.
  • Test 3 Review
  

Textbook and class notes.

  

Chapter 3 Quiz and Test Review.

 

11

Test 3

Chapter 4: Binomial Distributions

4.1 Probability Distributions

4.2 Binomial Distributions

  

Elementary Statistics texbook, pages: 188-216

  

Week's Assignment 8 Packet handout

 

12

Chapter 5 Normal Probability Distributions

5.1 Introduction to Normal Distributions and Standard Normal Distributions

5.2 Normal Distributions

  

Elementary Statistics textbook, pages: 232-246

  

Week's Assignment 9 Packet handout

 

13

6.1 Confidence Intervals for the mean ( Sigma Known or unknown)

6.2 Confidence Intervals for Population Proportions, Variance and Standard Deviation.

  

Elementary Statistics textbook, pages: 296-330

  

Week's Assignment 10 Packet handout

 

14

Quiz 4.

Chapter 7/8: 7.1 Hypothesis Testing with One and Two Samples

Chapter 9: Correlation and Regression

  

Elementary Statistics textbook, pages: 346-393/468-497

  

Review for Final!

 

15

FINAL!

  

Textbook and Class notes

  

Final Test!

 

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.


Participation Expectations

Full participation requires active and thoughtful engagement in class each week. The following habits and skills are important. You'll have the opportunity to self-assess and receive my feedback on each of these areas at the mid-point and the end of the semester.

  • Attend class regularly, on-time and for the full session
  • Complete all of the week's reading and assignments before the start of class
  • Listen to others attentively and with an open mind
  • Positively contribute to class discussions and activities
  • Ask questions and seek help when you need it
  • Challenge yourself to do your best work


Missing & Late Work Policy

  • Assignments are due the following week, even when you need to be absent. Your work can be emailed or dropped off at the front desk.
  • Plan to complete homework for the next class meeting on time. Being absent is not an excuse for not completing any homework assigned that day.
  • Extensions will be granted only in extenuating circumstances. If a lengthy medical problem or other emergent personal issue will result in missing weekly class attendances and/or assignments, please contact me as soon as possible.
  • You are responsible for checking Canvas and getting any notes, materials and assignments for the class you missed. Please reach out and ask questions if anything is unclear.
  • Students who know they will not attend class for any given week should make arrangements with me to complete the required work prior to the absence.

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/discover-resources/students-with-disabilities/
  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: November 4, 2024 - January 17, 2025