MDM4U

Mathematics of Data Management, Grade 12, University Preparation

Course Code:   MDM4U

Course Title: Mathematics of Data Management, Grade 12, University Preparation.

Department: Mathematics

Course Developer(s): Wilson Li

Development Date: April, 2018

Revision Number: 0

Revision Date:  May 20, 2019

Ministry Document: Mathematics, The Ontario Curriculum, Grades 11 and 12, 2007

Credit value: 1.0

Credit Hours: 110

Prerequisite(s): MCR3U Functions, Grade 11, University Preparation; OR MCF3M – Functions and Applications, Grade 11, University/College Preparation

Co-requisite(s): None

Textbook(s): Mathematics of Data Management, McGraw-Hill Ryerson (2010)

Course Code:   MDM4U

Course Title: Mathematics of Data Management, Grade 12, University Preparation.

Department: Mathematics

Course Developer(s): Wilson Li

Development Date: April, 2018

Revision Number: 0

Revision Date:  May 20, 2019

Ministry Document: Mathematics, The Ontario Curriculum, Grades 11 and 12, 2007

Credit value: 1.0

Credit Hours: 110

Prerequisite(s): MCR3U Functions, Grade 11, University Preparation; OR MCF3M – Functions and Applications, Grade 11, University/College Preparation

Co-requisite(s): None

Textbook(s): Mathematics of Data Management, McGraw-Hill Ryerson (2010)

Course Code:   MDM4U

Course Title: Mathematics of Data Management, Grade 12, University Preparation.

Department: Mathematics

Course Developer(s): Wilson Li

Development Date: April, 2018

Revision Number: 0

Revision Date:  May 20, 2019

Ministry Document: Mathematics, The Ontario Curriculum, Grades 11 and 12, 2007

Credit value: 1.0

Credit Hours: 110

Prerequisite(s): MCR3U Functions, Grade 11, University Preparation; OR MCF3M – Functions and Applications, Grade 11, University/College Preparation

Co-requisite(s): None

Textbook(s): Mathematics of Data Management, McGraw-Hill Ryerson (2010)

Course Content

Length

Unit 1 Probability                             

  • Basic Probability Concepts.
  • Odds.
  • Mutually Exclusive & Non-mutually Events.
  • Independent & Dependent Events.
    (15 hours)

Unit 2    Permutations                                      

  • Organized & Fundamental Counting.
  • Permutations & Factorials.
  • Rule of Sum.
  • Probability Problems Using Permutations.
(15 hours)

Unit 3    Combinations

  • Permutations with Identical Elements.
  • Combinations.
  • Problem solving with combinations.
  • Pascal’s triangle.
  • Combinations & Pascal’s Triangle & the Binomial Theorem
  • Probabilities Using Combinations
 (15 hours)

Mid-term:                                                        

  (2 hours)

Unit 4    Organization of Data for Analysis 

  • Data Concepts & Graphical Summaries
  • Sampling Techniques & Bias.
  • Collecting Data.
 (15 hours)

Unit 5    Probability Distributions          

  • Probability Distributions.
  • Uniform Distributions.
  • Binomial Distributions.
  • Hyper geometric Distributions.
  • Comparing & Selecting Discrete Probability Distributions
 (15 hours)

 Unit 6   The Normal Distributions                      

  • Continuous Distribution.
  • Normal Distribution.
  • Modelling Normal Distribution
 (15 hours) 

 Unit 7    One Variable Statistics & Two Variable Statistics    

  • One Variable Statistics.
  • Two Variable Statistics
(16 hours)

 Final Examination     

   (2 hours)
 

Total: 110 hours

 

Assessment for Learning

Assessment as Learning

Assessment of Learning

Student Product
  • Journals/Letters/Emails (checklist)
  • Entrance Ticket
  • Exit Tickets
  • Journals/Letters/Emails (checklist)
  • Assignments
  • Rough Drafts (rubric)
  • Research Paper (rubric)
  • Quizzes (Scale/Rubric)
  • Posters (Scale/Rubric)
  • Vocabulary notebooks (anecdotal)
  • Essays (rubric)
  • Peer Feed Back (anecdotal/checklist)
  • Journals/Letters/Emails (checklist)
  • Assignments
  • Research Paper (rubric)
  • Tests (Scale/Rubric)
  • Posters (Scale/Rubric)
  • Portfolio/ISU (Scale/Rubric)
  • Essays (rubric)
  • Exam
Observation
  • Class Discussion (anecdotal)
  • Self-Proof reading (checklist)
  • Class Presentations (anecdotal)
  • Performance Task (anecdotal/scale)
  • PowerPoint Presentations (rubric)
  • Debate (rubric)
  • PowerPoint Presentations (rubric)
  • Performance Task (anecdotal/scale)
  • Debate (rubric)
Communication 
  • Student teacher conference (checklist)
  • Group Discussion (checklist)
  • Pair work (checklist)
  • Debates/Opinion (rubric)
  • Peer Feed Back (anecdotal)
  • Peer editing (anecdotal)
  • Oral Quizzes/Tests (Scale/Rubric)
  • Student teacher conference (checklist)
  • Question Answer session (checklist)
  • Oral Tests (Scale/Rubric)

 

Assessment and Evaluation of Student Performance

  • Learning Skills:

Responsibility, Organizational, Independent Work, Collaboration, Initiative, Self-Regulation

  • Assessment of Learning Skills:

In-class observations, self-evaluations, homework and assignment checklists, participation rubrics

  • Achievement Categories:

Knowledge and Understanding, Thinking, Communication, Application

  • Assessment and Evaluation of Achievement Categories:

Checklists, Class Discussions, Presentations, Homework Checks, Individual Projects, Peer Evaluation, Quizzes, Rubrics, Teacher Observation, Written Tests

Academic Honesty

Students are expected to submit only their own original work. Incidents of plagiarism or cheating will be
investigated and a mark of zero will be given for the assignment. The teacher and/or Principal will decide whether the student will be given another opportunity to demonstrate his/her learning.

Term Summative Evaluations (70% Term Work)

Through the course work students will demonstrate mastery of all the overall expectations of the course. Students’ marks will be affected by any missing, late or incomplete assignments, as per OMC Late Policy.

Prior to assessment and evaluation, ample opportunities to enhance skills relating to achievement of the curriculum expectations will be provided to students.

Major evaluations will be announced at least one week in advance.

In the event that a student needs to miss a scheduled evaluation due to acceptable reasons, as listed in Policy, students must notify teachers in advance to re-schedule evaluation. In the case of unexpected absence, a note must be present, signed by a parent or guardian, immediately upon their return to explain the absence.

Cheating is strictly unacceptable and will be dealt with accordingly.

30% Summative Evaluation

A final exam will be administrated during the exam time period and a performance task evaluation will be conducted during the final four weeks of the course.

The Final Grade

  • The grade appearing on the final report card will be the weighted sum of term work and final exam marks.

Final Mark Calculation

The assessment evaluation of students in this course is in accordance with the Ministry curriculum guidelines.

Assessment

Weight

Final grade

Weight

Levels of Achievement

Knowledge and Understanding

25%

   

Level D: 50 – 59%

Applications

25%

Term Work 70%

Level C: 60 – 69%

Thinking and Inquiry

25%

   

Level B: 70 – 79%

Communication

25%

Final Exam 30%

Level A: 80 – 100%

 

Program Planning Consideration

  • Technology helps to make students more powerful learners by giving them the means to explore mathematical concepts more effectively. By using technology, students can explore fundamental ideas in greater depth, develop higher skill levels and explore more application. Various forms of technology have application in many different areas of mathematics learning. Calculators save students time in performing complex arithmetic calculations. Graphing utilities enable students to explore properties of graphs of function. The use of technology in learning and doing mathematics also gives students opportunities to develop their abilities in algorithmic thinking. for example, by writing sequences of instructions in application programs as part of a problem-solving process.

Students’ understanding of the role of mathematics in daily life and its relation to career opportunities will be promoted by exploring applications of concepts, by providing opportunities for career-related project work, and by promoting independent investigations. Such activities allow students the opportunity to investigate mathematics-related careers compatible with their interests, aspirations and abilities.

Mathematics anxiety is a state of mind relating to a student’s perception of his or her ability to do mathematics. To alleviate this anxiety in classroom, teachers should be accepting, patient and understanding; defuse tense situation If they arise; make mathematics relevant by connecting Hanson International Academy I Program Planning Considerations 15 the students’ life experience; comment positively on material that is assessed, be aware of cultural biases and set up programs for peer tutoring.