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Course Outline Stat 251 C Introductory Statistics

Winter 2021 Michael Chi

Class Time: Asynchronous Lecture Videos; F 2:00 pm – 2:50 pm Synchronous Class Group Discussions (Note : These live sessions will be recorded for those that cannot attend)

Class Location: Online through Blackboard (live classes will be through Blackboard Collaborate Ultra)

Lab Time: W 3:30 pm – 5:20 pm or F 8:00 am – 9:50 am or F 10:00 am – 11:50 am

Lab Location: Online through Blackboard Collaborate Ultra

Office Phone: Due to the current COVID-19 situation and restricted access to campus, I will not be taking any phone calls during the Fall semester. Therefore all students are asked to contact me directly by email with any questions/concerns etc. they may have.

Office Hours: By appointment through Blackboard Collaborate Ultra. See instructions for booking an appointment on Blackboard.

E-mail: michael.chi@rdc.ab.ca Preferred Contact: Email or office hours. I will try to reply emails within the next business day.

Credit Hours: 3-0-2 Prerequisite: Math 30-1 or 30-2

Academic Calendar Entry: (Prerequisite: Math 30-1 or 30-2, Credit Hours: 3-0-2) Explore methods for the collection, organization and summarization of data. Interpret the concepts of probability and distributions in order to make inferences about quantitative problems in applied settings. Delivery: This class will be delivered online. It will primarily be a mix of synchronous and asynchronous

Asynchronous: – Instruction and learning does not take place in real time but does include student and instructor collaboration and engagement. Instructors facilitate discussion boards, provide feedback on student assessments and assist students with content-related questions about course work. Learners complete lessons on their own or in collaboration with other classmates by accessing course content, materials, assignments, discussion boards, grades, etc. through Blackboard. Synchronous: Some or all instruction and learning takes place in real time using an online virtual classroom. Learners will access the online class at predetermined dates and times and will be greeted and guided through course content by an Instructor. Learners will access the course content, materials, assignments, discussion boards, grades, etc. through Blackboard.

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Required Texts and Equipment:

Blackboard: This course will be delivered in an online format. We will use Blackboard and Blackboard Collaborate Ultra for live class sessions. Students are advised to become familiar with the course layout as soon as possible. Flexible Learning at RDC provides supports and resources for students. If you have any questions about the course, please contact me. If you have general questions about online learning and system requirements, please check out the supports at:

https://rdc.ab.ca/programs/flexible-learning/flexible-learning

There is no required textbook for this course. My lecture notes will be posted to Blackboard.

Electronic devices are required to access the online assessments (computer, laptop, or tablet) and to capture handwritten work (phone or scanner). Windows 10 or Mac OS X 10.15 is highly recommended for the lab sessions.

Recommended Readings and Resources: I will be using the following textbook as a main reference:

De Veaux et al. (2018). Stats Data and Models (3rd Canadian Edition): Pearson Course Outcomes:

State the objectives of Descriptive and Inferential Statistics.

Present data with clarity using graphs and fundamental statistics.

Employ basic probability rules.

Calculate descriptive and inferential measures using appropriate formulas.

Construct and interpret confidence intervals for population means and proportions.

Perform one and two tail tests of hypotheses for one and two sample experiments.

Interpret and critique elementary research studies.

Interpret Pearson’s correlation coefficient and the coefficient of determination.

Apply Linear Regression Equations to make predictions.

Use statistical software to clearly present data and perform a variety of hypothesis tests. Course Topics:

Statistical Terminology, Descriptive Statistics,

Correlation and Regression,

Probability, Probability Distributions,

Confidence Intervals,

Introduction to Inference, Hypothesis Testing,

Inferences from One and Two Samples,

Chi-Squared Tests, ANOVA Learning Activities: Lecture notes will be posted on Blackboard and video lectures will be used to present the course material. It is expected that you watch the videos and write your own notes. It is strongly recommended that you review these problems in preparation for the quizzes and exams. Live synchronous sessions will provide an opportunity for you to participate with the instructor and other students once per week. Attendance is not mandatory but participation will

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award bonus marks to your grade. If you cannot attend the live sessions, then there are other opportunities to receive bonus marks (challenge problems). Labs will be used to work through the assignments. You will have an opportunity to ask the instructor for assistance or interact with other students using Blackboard Collaborate Ultra. Assessment, Assignments and Exams: Your final grade will be calculated using the following assessments: Assessment ______ Lab Assignments: 20% Midterm 1: 20% Midterm 2: 20% Final: 40% Total: 100% All assignments and assessments in this course must be submitted electronically through Blackboard or Gradescope using the appropriate tool in Blackboard or Gradescope. Tentative Schedule for Midterms: Monday, Feb 8th and Monday, Mar 15th Midterms: Midterms are open book and a calculator is allowed. Topics covered on each midterm will be posted on Blackboard. Final: The final will be open book and a calculator is allowed. The final is cumulative and will cover all topics with a larger emphasis on the material towards the end of the course. Late Penalties and Alternate/Make-up Assessments Late submissions will not be accepted without a legitimate reason. I recognize that life can conflict with your studies and in the event that something happens, please email me as soon as possible to discuss options. I will endeavor to reply within 24 hours. Attendance Requirements: There are no formal attendance requirements. It is strongly recommended to attend the live synchronous sessions if you feel that you are struggling with the course or book an appointment to get help as soon as possible. Grading Scale:

Letter Grade Grade Points % Range

A+ 4.0 89.50 – 100.00

A 4.0 84.50 – 89.49

A- 3.7 79.50 – 84.49

B+ 3.3 76.50 – 79.49

B 3.0 72.50 – 76.49

B- 2.7 69.50 – 72.49

C+ 2.3 66.50 – 69.49

C 2.0 62.50 – 66.49

C- 1.7 59.50 – 62.49

D+ 1.3 56.50 – 59.49

D 1.0 49.50 – 56.49

F 0.0 <49.50

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Please note that a passing grade of D/D+ may not transfer to all receiving institutions; check with the receiving institution for clarification. Mid-Term Feedback: Mid-Term feedback will be provided on Blackboard during the week of Mar 1st. If you are struggling with the course or feel that your final grade may be jeopardized, then you should make an appointment with your instructor as soon as possible. The RDC Final Examinations Policy: In courses with Final Examinations, the RDC Final Examinations Policy and Final Examinations Guidebook will apply. Please review these documents to ensure that you understand the contents and implications of the policy. Academic Misconduct:

Academic misconduct in all its forms is a serious offence. Academic misconduct is the giving, taking, or presenting of information or material that unethically or dishonestly aids oneself or another on any work which, under normal circumstances, is to be considered in the determination of a grade or the compilation of academic requirements or the enhancement of that student’s record or academic career. The two key areas of academic misconduct are plagiarism and cheating. Please read the definitions that follow. Plagiarism:

The use or close imitation of language, paintings, films, prototypes and ideas of another author and representation of them as one's own original work. The most common forms of plagiarism are copying or paraphrasing another author’s work without proper acknowledgement, using the ideas or lines of reasoning of another author’s work without proper acknowledgement, submitting work to which someone else has made substantial improvements to the content, and submitting the same work for multiple courses without approval. Plagiarism can be judged to have occurred if the instructor has both the submitted material and original source that was copied, or if the student is unable to explain the terminology or ideas of a submission. Cheating:

Any attempt to give or obtain unsanctioned assistance in a formal academic exercise (e.g., examination). Some examples of cheating are unauthorized cheat sheets in a test or exams, the unauthorized use of electronic devices during an exam, and copying from an adjacent student.

Student Academic Integrity and Academic Misconduct Student Academic Integrity and Academic Misconduct Guidebook

Student Misconduct: Non-Academic

Student Misconduct: Non-Academic Guidebook

Student Appeals

Student Appeals Guidebook

Student Rights and Responsibilities Policy:

Red Deer College (RDC) is a learning community dedicated to the pursuit of knowledge and to ensuring that the adult learners it serves have the knowledge, skills, and competencies to develop to their full potential. The essential conditions for a learning community are an atmosphere of freedom, respect, and appreciation for the basic rights and responsibilities of all

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members of the community. Students should familiarize themselves with the RDC Students Rights and Responsibilities Policy and follow the guidelines defined within the policy. It is the student’s responsibility to be familiar with the information contained in this Course Outline and to clarify any areas of concern with the instructor. It is also the student’s responsibility to be familiar with all RDC Policies. Audio-Visual Recording:

Audio or video recording, digital or otherwise, of lectures, labs, seminars, or any other teaching environment by students is allowed only with the prior written consent of the instructor or as a part of an approved accommodation plan. Student or instructor content, digital or otherwise, created and/or used within the context of the course is to be used solely for personal study, and is not to be used or distributed for any other purpose without prior written consent from the content author(s). Important Red Deer College Dates –Winter 2021

Prior Learning Assessment: This course may be eligible for Recognition of Prior Learning. Students should refer to the RDC Academic Calendar for a list of excluded courses. Student Services on Campus

Students should be aware that Personal Counselling, Career, Learning and Disability Resources are provided by RDC. Students may inquire about locations at the Information Desk. It is the responsibility of students to discuss their specific learning needs with the appropriate service provider. Flexible Learning: (support for online learners at RDC) Academic Support: (Library: 403-342-3264, help_learn@rdc.ab.ca )

• Writing Skills Centre (writingskills@rdc.ab.ca) • Math Learning Centre (math concepts and advanced theoretical math) • Learning Strategies (note-taking, studying, and exam-writing strategies)

~ Winter 2021 January 1st New Year’s Day – College closed January 4th First Day of Classes for Winter Term 2021 January 4th Mid-term feedback for Full year 2020-2021 courses January 8th Last day to apply for Supplemental Exams for Fall term 2020 January 11th Last day to register, add or drop Winter term 2021 courses January 11th Last day for tuition refund January 16th Supplemental Exams written for Fall term 2020 February 15th Family Day – College closed February 16th – 19th Reading Week Break March 1st Mid-term feedback for Winter term 2021 courses March 2nd Emergency Response Day March 12th Final Exam Schedule posted April 2nd April 5th

Good Friday – College closed Easter Monday – College open, no credit classes

April 9th Last day to withdraw from Winter term 2021 and Full term 2020-21 courses and receive a WD April 9th Last day of classes for Winter term 2021 and Full year 2020-21 courses April 13th – 17th Final exams written April 20st Deferred Exams for Winter term 2021 and Full-year 2020-2021 courses April 22nd Last day for submission of final grades for Winter term 2020 and Full year 2019-2020 courses April 23rd Final grades available for Winter term 2021 April 30th Last day to apply for Supplemental Exams for Winter 2021 May 8th Supplemental exams for Winter term 2021 written

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• Peer-Assisted Study / Tutoring (one-on-one tutoring by students)

Disability Resources (Library: 403-357-3629, disabilityservices@rdc.ab.ca) • Coordination of services (tutoring, alternate format text, note-taking, and so on) • Academic accommodations, including exam accommodations

Counselling and Career Centre (Room 1402: 403-343-4064, counselling@rdc.ab.ca)

Changes to the Course Outline

It is the student’s responsibility to be familiar with the information contained in this course outline and to clarify any areas of concern with the instructor. Students should refer to the Appeals: Student Appeals and Student Appeals Guidebook, and Student Academic Integrity and Academic Misconduct and Student Academic Integrity and Academic Misconduct Guidebook and Student Misconduct: Non-Academic and Student Misconduct: Non-Academic Guidebook, should questions or concerns about the Course Outline not be resolved directly with the instructor. No changes will be made to this course outline without the consent of the class and the approval of the Associate Dean of the School of Arts & Sciences and the School of Creative Arts.

Dr. Robbie J. Halonen Associate Dean, School of Arts & Sciences and School of Creative Arts Reading/Class Schedule (subject to adjustments as required or in consultation with the class) Week 1 & 2: Descriptive Statistics Week 3: Measures of Central Tendency and Variability Week 4: Probability Week 5: Random Variables & Probability Distributions Week 6: Sampling Distributions Week 7 & 8: Confidence Intervals and Hypothesis Testing for Proportions Week 9: Chi-Squared Tests Week 10 & 11: Confidence Intervals and Hypothesis Testing for Means Week 12: ANOVA Week 13: Linear Regression Week 14: Review