Untitled

Web Schedules

Fall 2024
Spring 2024
Summer 2024

One Credit Courses

Fall 2024
Spring 2024
Summer 2024

No Cost Textbook/Resources Courses

Fall 2024
Spring 2024
Summer 2024

Low Cost Textbook/Resources Courses

Fall 2024
Spring 2024
Summer 2024

Course Planning by Program

2024-25

Essential Objectives

Course Syllabus


Revision Date: 18-Dec-23
 

Spring 2024 | MAT-2021-VU02 - Statistics


In Person Class

Standard courses meet in person at CCV centers, typically once each week for the duration of the semester.

Location: Winooski
Credits: 3 (45 hours)
Day/Times: Thursday, 03:00P - 05:45P
Semester Dates: 01-25-2024 to 05-02-2024
Last day to drop without a grade: 02-11-2024 - Refund Policy
Last day to withdraw (W grade): 03-24-2024 - Refund Policy
This course has started, please contact the offering academic center about registration

Faculty

Jane Kay
View Faculty Credentials

Hiring Coordinator for this course: Nick Molander

General Education Requirements


This section meets the following CCV General Education Requirement(s) for the current catalog year:
VSCS 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. 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 IT Support page. https://support.ccv.edu/general/computer-recommendations/

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 low cost ($50 or less) 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.


Methods

Students learn math by doing math. Class time will be dedicated to explanations, examples and practice of concepts. You will practice statistical concepts outside of class using the Sofia online learning system. My goal for all students is that you leave with a foundation in statistics that you will be able to apply to future courses and endeavors.


Evaluation Criteria

Your final grade will be calculated as follows:

Weight Item Delivery Method
10% Classroom engagement
30% Homework Online in Canvas using Sofia
30% Problem Sets Paper, Pencil, All work shown
20% Exams In Class hour exams
10% Final In class 2 hour exam

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

Introduction to Statistics

Data collection and organization

  

Openstax PreCalculus

1.1 - 1.4

  

Sofia Assignments

Problem Set 1 assigned

 

2

Descriptive Statistics part 1

  

2.1 - 2.3

  

Sofia Assignments

Continue work on Problem Set 1

 

3

Descriptive Statistics part 2

  

2.4 - 2.7

  

Sofia Assignments

Complete Problem Set 1

 

4

Test on Chapters 1 and 2

Probability part 1

  

3.1-3.3

  

Test 1 (1 hour in class)

Hand in Problem Set 1

Problem Set 2 Assigned

Sofia Assignments

 

5

Probability Part 2

Discrete random Variables

  

3.4 -3.5

4.1 - 4.3

  

Sofia Assignments

Continue work on Problem Set 2

 

6

Continuous Random Variables

  

5.2 - 5.2

  

Sofia Assignments

Continue work on Problem Set 2

 

7

The Normal Distribution

  

6.1 - 6.4

  

Sofia Assignments

Complete Problem Set 2

 

8

Test 2 on Chapter 3 - 6

The Central Limit Theorem

  

7.1 and 7.3

  

Test 2 (1 hour, in class)

Hand in Problem Set 2

Sofia Assignments

Problem Set 3 Assigned

 

9

Confidence Intervals

  

8.1 - 8.6

  

Sofia Assignments

Continue work on Problem set three.

 

10

Hypothesis Testing with one sample

  

9.1 - 9.6

  

Sofia assignments

Continue work on Problem Set 3

 

11

Review and catch up on inferential Statistics

  

Chapters 7-9

  

Sofia Assignments

Continue work on Problem Set 3.

 

12

Test 3 Chapters 7 , 8 and 9

Hypothesis testing with two samples

  

10.1 -10.5

  

Test 3 (1 hour in class)

Hand in Problem Set 3

Sofia Assignments

Problem Set 4 handed out

 

13

Linear regression and Correlation

  

12.1 - 12.9

  

Sofia Assignments

Problem Set 4 - Review for Final exam

 

14

The Chi square tests

Review for Final

  

11.1 - 11.3

  

Sofia Assignments

Continue work on Problem Set 4

 

15

Final Exam

    

Hand in Problem Set 4

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.


Participation Expectations

You will receive a classroom engagement grade for each class period. To get full points:

  • Be Present
  • Be on time
  • Ignore your phone except for emergencies
  • Engage in all learning activities.


Missing & Late Work Policy

  • Pay attention to all due dates in Canvas.
  • Sofia assignments are assigned each class and are due a week later. Sofia assignments are officially due at 11:59 pm on the night of your next class. This is to allow you a class period for asking questions,
  • Any deliverable (Sofia, problem sets) is reduced 2.86% for each day late. This is the equivalent of two letter grades per week.
  • You are responsible for materials and information should you miss class. All assignments, handouts, notes are available in Canvas.

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.