Fall 2024  MAT2021VO02  Statistics
Online Class
Online courses take place 100% online via Canvas, without required inperson or Zoom meetings.
Location: Online
Credits: 3 (45 hours)
Day/Times: Meets online
Semester Dates: 09032024 to 12162024
Last day to drop without a grade: 09162024  Refund Policy
Last day to withdraw (W grade): 11042024  Refund Policy
Open Seats: 1 (as of 071324 3:05 PM)
To check live space availability, Search for Courses.
Faculty
Dan Lemay
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:
VSCS Mathematics
Note
 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.
 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 twotailed 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/computerrecommendations/
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.
Fall 2024 textbook details will be available on 20240520. 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.
MAT2021VO02
Link to Textbooks for this course in eCampus.
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.
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.
Allowed: This course's generative AI policy acknowledges technology, including generative AI, plays a supportive role in learning and feedback. During our class, we may use AI writing tools such as ChatGPT in certain specific cases. You will be informed as to when, where, and how these tools are permitted to be used, along with guidance for attribution. Any use outside of these specific cases constitutes a violation of CCV's Academic Integrity Policy.
Methods
Each week you will
 Take a quiz/exam on the previous week(s) work.
 Read the assigned sections/watch the author videos
 Complete online WebAssign HW out at WebAssign. You will have needed to buy access and have an activation code..
 Participate in the Canvas Discussion forum.
 Here is an FAQ about how I run this course
https://sites.google.com/view/faqstatistics/home
Evaluation Criteria
How your grade is determined:
600 points from tests (3 @ 200 points each) Test questions will be a combination of multiple choice questions and short response questions where you need to show work and explain your thinking. You will need to mail/email me your responses to the short response questions
550 points from a weekly quiz. (11 quizzes, 50 points each) These will take the form of a quiz in a variety of formats. Some will be available in Canvas and some out at WebAssign. Check in Canvas each week.
120 points from online hw exercises ( WebAssign ) (12 sets  50 points each week) . Each week you'll have a set of online exercises to complete out at . These need to be completed at least at a 70% level. You DO have to attempt every exercise.
120 points from Weekly Attendance posts (10 points each week 5 points for each post, 2 posts each week at a minimum) Each week you need to make a post responding to something from the current week’s material the two weekly discussion forums. The First post is due in the Post 1 forum by Saturday night at midnight and the second post by the end of the week on Monday night @ midnight. Asking questions about how to do an exercise, showing your work on how to an exercise, helping another student out, Finding the math we are studying in the wild are all good ways to meet this requirement.
While I welcome some "How's the weather" posts, posts made for attendance need to be related to course content.
Your grade is calculated by dividing the points you earned by the points you could have earned.
Late work/make up policy: Aside from the discussion forum posts, if you are running behind, and need some more time to get the week's work completed, send me an email before midnight Monday night asking for an extension. Please provide an estimate of how much more time you need. WebAssign has a built in extension request tool that you can use.
If you want to make up missing work (WebAssign/quizzes) from previous week's work that you missed, I'll allow this up to the week an exam is assigned on this material. For example Week 1 3 is tested during week 4. If you ask to make up week 1 work during Week 5, I can't allow this.
This is a fast paced course and falling behind is not advised.
Grading Criteria
CCV Letter Grades as outlined in the Evaluation System Policy are assigned according to the following chart:
 High  Low 
A+  100  98 
A  Less than 98  93 
A  Less than 93  90 
B+  Less than 90  88 
B  Less than 88  83 
B  Less than 83  80 
C+  Less than 80  78 
C  Less than 78  73 
C  Less than 73  70 
D+  Less than 70  68 
D  Less than 68  63 
D  Less than 63  60 
F  Less than 60  
P  100  60 
NP  Less than 60  0 
Weekly Schedule
Week/Module  Topic   Readings   Assignments 

1 
3. Create and apply various techniques used to describe data, such as pie charts, bar graphs, frequency tables, and histograms.
  ThinkDo Chapter 1   Discussion Forum posts
WebAssign Problem set


2  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.   ThinkDo Chapter 2
  Quiz on Chapter 1 content/ideas
Discussion forum posts
WebAssign Problem set


3 
3. Create and apply various techniques used to describe data, such as pie charts, bar graphs, frequency tables, and histograms.
11. Demonstrate proficiency in understanding, interpreting, evaluating and applying quantitative data and information.
  ThinkDo Chapter 3   Quiz on Chapter 1/2 content/ideas
Discussion forum posts
WebAssign Problem set


4  Assessment of
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.
11. Demonstrate proficiency in understanding, interpreting, evaluating and applying quantitative data and information.
  None, no new ideas   Optional practice exam work
Two part Exam 1


5 
Understanding relative frequency probability, Classical Probability.
Understanding how multiple events can affect each other.
Calculating probabilities of events.
This is leading us towards
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.
  ThinkDO chapter 4   Discussion forumposts
WebAssign problem set


6 
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
  ThinkDo Chapter 5
  Quiz on Chapter 4 work
Discussion forum posts
WebAssign problem set


7 
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.
  ThinkDo Chapter 6   Quiz on Chapter 5
Discussion Forum posts
WebAssign Problem set


8 
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.
  Assessment week
  Optional Practice Exam post
Two part Exam 2


9  2. Distinguish between descriptive and inferential statistics.
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.
  ThinkDO Chapter 7   Discussion Forum Posts
WebAssign problem Set


10 
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 twotailed tests.
  ThinkDo Chapter 8   Quiz on Chapter 7
Discussion Forum Posts
WebAssign problem Set


11 
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 twotailed tests.
  ThinkDo Chapter 9   Quiz on Chapter 8
Discussion forum posts
WebAssign Problem set


12  9. Define linear regression and correlation and discuss their applications
  ThinkDo Chapter 10
  Quiz on Chapter 9
Discussion Forum Post
WebAssign Problem set


13  8. Select and perform common statistical tests including one and twotailed tests. (Chisquare Goodness of Fit tests and ChiSquare tests for independence)   ThinkDO Chapter 11   Quiz on Chapter 10
Discussion Forum Post
WebAssign Problem set


14 
2. Distinguish between descriptive and inferential statistics.
10. Interpret and evaluate the validity of statistical data and reports.
  JAMA website   Discussion forum "Find a Study" 

15  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 twotailed 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.   Assessment Week   Optional Practice Exam review
Two part exam on Chapters 710


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 nonsatisfactory 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 onground 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
Each week you will
 Take a quiz/exam on the previous week(s) work.
 Read the assigned sections/watch the author videos
 Complete online WebAssign HW out at WebAssign. You will have needed to buy access either through eCampus or directly from WebAssign. This is the Course Key which identifies this course
https://www.getenrolled.com/?courseKey=ccv46194525
 Participate in the Canvas Discussion forum.
 Here is an FAQ about how I run this course
https://sites.google.com/view/faqstatistics/home
Missing & Late Work Policy
Late work/make up policy: Aside from the discussion forum posts, if you are running behind, and need some more time to get the week's work completed, send me an email before midnight Monday night asking for an extension. Please provide an estimate of how much more time you need. WebAssign has a built in extension request tool that you can use.
If you want to make up missing work (WebAssign/quizzes) from previous week's work that you missed, I'll allow this up to the week an exam is assigned on this material. For example Week 1 3 is tested during week 4. If you ask to make up week 1 work during Week 5, I can't allow this.
This is a fast placed course and falling behind is not advised.
Accessibility Services for Students with Disabilities:
CCV strives to mitigate barriers to course access for students with documented disabilities. To request accommodations, please

Provide disability documentation to the Accessibility Coordinator at your academic center. https://ccv.edu/discoverresources/studentswithdisabilities/

Request an appointment to meet with accessibility coordinator to discuss your request and create an accommodation plan.

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.
