Course Description

This course explores the study of collecting, classifying, calculating, and interpreting cross-sectional data for analysis and decision making. We journey through topics within data science and statistics including: Fundamental statistical calculations, visual representations of data, experiment design, data spread, probability, regression, correlation, causation, hypothesis testing, and applications of data analysis. Within applications of data analysis we explore: Privacy, studies, experiments, journal article mathematics, and software data use.

Essential Employability Skills

This course contributes to your program by helping you achieve the following Essential Employability Skills:

EES 1 COMMUNICATION: Communicate clearly, concisely and correctly in the written, spoken and visual form that fulfills the purpose and meets the needs of the audience. (P)
EES 2 COMMUNICATION: Respond to written, spoken or visual messages in a manner that ensures effective communication. (P)
EES 3 NUMERACY: Execute mathematical operations accurately. (T, P, E)
EES 4 CRITICAL THINKING & PROBLEM SOLVING: Apply a systematic approach to solve problems. (T, P, E)
EES 5 CRITICAL THINKING & PROBLEM SOLVING: Use a variety of thinking skills to anticipate and solve problems. (T, P, E)
EES 6 INFORMATION MANAGEMENT: Analyze, evaluate and apply relevant information from a variety of sources. (T, P, E)
EES 7 INFORMATION MANAGEMENT: Locate, select, organize and document information using appropriate technology and information systems. (T, P, E)
EES 8 INTERPERSONAL: Show respect for diverse opinions, values, belief systems and contributions of others. (P)
EES 9 INTERPERSONAL: Interact with others in groups or teams in ways that contribute to effective working relationships and the achievement of goals. (P)
EES 10 PERSONAL: Manage the use of time and other resources to complete projects. (P)
EES 11 PERSONAL: Take responsibility for one's own actions, decisions and consequences. (P)
Assessment Levels —T: Teach P: Practice E: Evaluate C: Culminate 

Optional Vocational Learning Outcomes

This course provides the opportunity for you to achieve the following outcomes.

R101 - General Arts and Science

VLO 1 R101/MTCU 54701 PLO1: Develop, through general knowledge gained in a wide range of subjects, insight into both self and society. (P)
VLO 2 R101/MTCU 54701 PLO2: Develop flexibility and clarity of both thought and expression in order to develop communications competence to a level required by business and industry. (T, P)
VLO 3 R101/MTCU 54701 PLO3: Understand and utilize critical thinking processes and problem solving techniques. (T, P, E)
VLO 5 R101/MTCU 54701 PLO5: Employ basic vocational, skills drawn from the areas of the Humanities, Social and Behavioural Sciences of Vocational Studies (Business, Technology). (T, P, E)

R104 - General Arts and Science - One-Year

VLO 2 R104/MTCU 44700 PLO2: Develop flexibility and clarity of both thought and expression in order to develop communications competence to a level required by business and industry. (T, P)
VLO 3 R104/MTCU 44700 PLO3: Understand and utilize critical thinking processes and problem solving techniques. (T, P, E)
VLO 5 R104/MTCU 44700 PLO5: Employ basic vocational, skills drawn from the areas of the Humanities, Social and Behavioural Sciences of Vocational Studies (Business, Technology). (T, P, E)
Assessment Levels —T: Teach P: Practice E: Evaluate C: Culminate 

Course Learning Outcomes

When you have earned credit for this course, you will have demonstrated the ability to:

1.
Collect and classify data.
2.
Represent data distribution mathematically and graphically.
3.
Determine the relationship between two sets of variables.
4.
Analyze data using the principles of probability.
5.
Use an investigative process to estimate population parameters.
6.
Use statistical calculations to achieve reliable and verifiable interpretations.

Learning Activities

This course will be delivered via interactive lessons, class demonstrations, and in-class student inquiry and discussion. Students are expected to be on-time and in attendance for:
  • Interactive exploration of new content
  • Group application trial and discovery
  • In-class review of homework sets
  • In-class group learning with peer support
  • In-class assessments

Learning Resources

Required textbook:

Illowsky, B., & Dean, S. (2013). Introductory Statistics. OpenStax. https://openstax.org/books/introductory-statistics/pages/1-introduction
 
Authors: Barbara Illowsky, Susan Dean
Publisher/website: OpenStax
Book title: Introductory Statistics
Publication date: Sep 19, 2013
Location: Houston, Texas
Book URL: https://openstax.org/books/introductory-statistics/pages/1-introduction
Section URL: https://openstax.org/books/introductory-statistics/pages/1-introduction

Course Related Information

Pre-defined Evaluation / Earning Credit

The following list provides evidence of this course's learning achievements and the outcomes they validate:

Quiz / Quizzes (10%)

Validates Outcomes:  CLO 1, CLO 2, EES 4, EES 7

    R101  :   VLO 3, VLO 5

    R104  :   VLO 3, VLO 5

Test 1 (5%)
Review

Validates Outcomes:  CLO 3, EES 3, EES 4, EES 5, EES 6

    R101  :   VLO 3, VLO 5

    R104  :   VLO 3, VLO 5

Test 1 (30%)

Validates Outcomes:  CLO 1, CLO 2, CLO 3, CLO 4, EES 3, EES 4, EES 5, EES 6, EES 7

    R101  :   VLO 3, VLO 5

    R104  :   VLO 3, VLO 5

Test 2 (5%)
Review

Validates Outcomes:  CLO 4, CLO 5, EES 3, EES 4, EES 5, EES 6, EES 7

    R101  :   VLO 3, VLO 5

    R104  :   VLO 3, VLO 5

Test 2 (30%)

Validates Outcomes:  CLO 1, CLO 2, CLO 3, CLO 4, CLO 5, CLO 6, EES 3, EES 4, EES 5, EES 6, EES 7

    R101  :   VLO 3, VLO 5

    R104  :   VLO 3, VLO 5

Assignment(s) (20%)
Weekly activities exploring course content.

Validates Outcomes:  CLO 1, CLO 2, CLO 3, CLO 4, CLO 5, CLO 6, EES 3, EES 4, EES 5, EES 6, EES 7

    R101  :   VLO 3, VLO 5

    R104  :   VLO 3, VLO 5

Prior Learning Assessment and Recognition

Students who wish to apply for Prior Learning Assessment and Recognition (PLAR) need to demonstrate competency at a post-secondary level in all outlined course learning outcomes. Evidence of learning achievement for PLAR candidates includes:

  • This course is PLAR eligible, please see Program Coordinator/Chair for more information.

Grade Scheme

The passing grade for this course is 50% / "D"
Final Grade Percentage Weight
A+ 90-100 4.0
A 86-89 4.0
A- 80-85 3.7
B+ 77-79 3.3
B 73-76 3.0
B- 70-72 2.7
C+ 67-69 2.3
C 63-66 2.0
C- 60-62 1.7
D+ 57-59 1.3
D 50-56 1.0
Below 50 0.0

Refer to the Evaluation System on this outline for information on how marks are distributed. More detailed information on assessments may also be found in your Course Section document.

As per Office of the Registrar Policies:

“A” Range = GPA 4.0-Consistently exceeds (course) requirements; shows evidence of being well-organized; shows original and creative thinking and a superior grasp of subject matter.

“B” Range = GPA 3.0-Shows consistent performance and evidence of being well-organized, shows elements of original and creative thinking; has a strong grasp of subject matter

“C” Range = GPA 2.0-Applies the subject matter appropriately; comprehends the subject matter.”

"D" Range = GPA 1.0-The student inconsistently applies and communicates knowledge of the subject matter

"F" Range = GPA 0.0-The student fails to apply and communicate an understanding of the subject matter.

Additional information regarding grading for this course may also be found in the "Course Related Information" section of this course outline.