Matemáticas de la Gestión de Datos, Grado 12, Preparación para la Universidad

Código: MDM4UGrado: 12Tipo: Preparación universitariaCréditos: 1.0
Descripción del curso

This course broadens students’ understanding of mathematics as it relates to managing data. Students will apply methods for organizing and analysing large amounts of information; solve problems involving probability and statistics; and carry out a culminating investigation that integrates statistical concepts and skills. Students will also refine their use of the mathematical processes necessary for success in senior mathematics. Students planning to enter university programs in business, the social sciences, and the humanities will find this course of particular interest.

Expectativas generales

Al final de este curso, los estudiantes desarrollarán las siguientes habilidades en estas diferentes áreas:

1. Mathematical Processes
1.1Mathematical processes will be integrated into student learning throughout the course  and include: problem-solving, reasoning and proving, reflecting, selecting tools and  computational strategies, connecting, representing, and communicating.
2. Counting and Probability
2.1solve problems involving the probability of an event or a combination of events for  discrete sample spaces; 
2.2solve problems involving the application of permutations and combinations to  determine the probability of an event.
3. Probability Distributions
3.1demonstrate an understanding of discrete probability distributions, represent them numerically, graphically, and algebraically, determine expected values, and solve related  problems from a variety of applications;
3.2demonstrate an understanding of continuous probability distributions, make connections  to discrete probability distributions, determine standard deviations, describe key features  of the normal distribution, and solve related problems from a variety of applications.
4. Organization of Data for Analysis
4.1demonstrate an understanding of the role of data in statistical studies and the variability  inherent in data, and distinguish different types of data; 
4.2describe the characteristics of a good sample, some sampling techniques, principles of  primary data collection, and collect and organize data to solve a problem.
5. Statistical Analysis
5.1analyse, interpret, and draw conclusions from one-variable data using numerical and  graphical summaries;  
5.2analyse, interpret, and draw conclusions from two-variable data using numerical,  graphical, and algebraic summaries;
5.3demonstrate an understanding of the applications of data management used by the  media and the advertising industry and in various occupations.
6. Culminating Data Management Investigation
6.1design and carry out a culminating investigation* that requires the integration and  application of the knowledge and skills related to the expectations of this course;
6.2communicate the findings of an investigation and provide constructive critiques  of the investigations of others.
Resumen del contenido del curso
Tiempo asignado
1. Probability and Counting Techniques

Probability vocabulary and notation are introduced involving simple counting;  students will explore theoretical versus experimental probability; Venn diagrams  and Set theory are introduced exploring complements and principles of inclusion  and exclusion. Counting permutations and combinations; tree diagrams, Pascal’s  triangle and the additive and multiplicative counting principles are explored.  Students will learn to use mathematical notation to describe the number of  permutations and combinations, solve counting problems, and solve probability  problems involving the application of permutations and combinations.

24 hours (12 hrs online/ 12 hrs offline)
2. Collecting, Organizing and Visualizing Data

Students will demonstrate an understanding of how data is organized and the  role of data in statistical studies. Students will describe the characteristics of a  good sample and compare sampling techniques. Principles of primary data  collection are explored as students collect, organize and analyze data to solve a  problem. Students will learn about the applications of data management in the  media, the advertising industry and in various occupations.

18 hours (8 hrs online/ 10 hrs offline)
3. Statistics

Explore, analyse, interpret, and draw conclusions from one-variable and two variable data. Students will calculate, by hand and with technology, measures of  central tendency and spread with grouped and ungrouped data. The validity of  statistical summaries are analyzed and evaluated.

20 hours (12 hrs online/ 8 hrs offline)
4. Normal Distribution

Students will demonstrate an understanding of continuous probability  distributions, describe the features of a normal distribution, and make  connections to discrete probability distributions. Students will determine standard  deviations and find z-scores to solve related problems from a variety of  applications.

16 hours (6 hrs online/ 10 hrs offline)
5. Probability Distributions

Students will understand and apply binomial distribution and expansion using  Pascal’s triangle and represent discrete probability distributions numerically,  graphically and algebraically. Students will explore and connect Binomial and  Hypergeometric distributions, use Normal distributions to approximate binomial  distributions; determine expected values, and solve related problems from a  variety of applications.

14 hours (5 hrs online/ 9 hrs offline)
6. Independent Study Unit

Students will design and conduct and statistical investigation demonstrating  the integration and application of the knowledge and skills relating to the  concepts covered in the course; communicate the findings of an investigation  and provide constructive critiques of the investigations of others. 15% of  final grade

15 hours (12 hrs online/ 3 hrs offline)
7. FINAL EXAMINATION

Proctored exam worth 15% of final grade.

3 hours (online)
Total110 horas
Estrategias de enseñanza y aprendizaje

This course is organized into a semester format. Lessons and activities will be presented to  students via the internet. Lessons will be provided on-line, with regularly scheduled student  teacher conferences and student to student discussion forums.  

A variety of strategies will be used in the online delivery of this course. Instructional strategies  will include but are not limited to: 

  • Clases dirigidas por el profesor 
  • Aprendizaje cooperativo  
  • Investigación independiente 
  • Aprendizaje entre iguales 
  • Presentación multimedia 

Learning goals will be discussed at the beginning of each assignment and success criteria will  be provided to students. The success criteria are used to develop the assessment tools in this  course, including rubrics and checklists. 

The over-riding aim of this course is to help students use the language of mathematics  skillfully, confidently and flexibly. A wide variety of instructional strategies are used to provide  learning opportunities to accommodate a variety of learning styles, interests, and ability levels.  The following mathematical processes are used throughout the course as strategies for  teaching and learning the concepts presented.

Estrategias de evaluación del rendimiento de los estudiantes

Se requiere una variedad de métodos, estrategias e instrumentos de valoración y evaluación adecuados a la expectativa evaluada. Entre ellos se incluyen los de diagnóstico, formativos y sumativos dentro del curso y dentro de cada unidad.  

La evaluación PARA EL APRENDIZAJE y la evaluación COMO APRENDIZAJE se obtienen a través de diversos medios, entre los que se incluyen los siguientes:  

  • Ongoing descriptive feedback, including descriptive feedback on students’ plans for  their venture 
  • Self-assessment
  • Evaluación inter pares
  • Conferencias entre estudiantes y profesores con regularidad para: 
    • o verbalizar las observaciones 
    • o hacer preguntas 
    • o aclarar la comprensión 

Las pruebas de los logros de los alumnos (evaluación del aprendizaje) se recogen mediante observaciones continuas del trabajo más consistente, teniendo en cuenta el trabajo más reciente de diversas fuentes. 

La evaluación en este curso se basará en las expectativas del plan de estudios provincial. Los alumnos dispondrán de numerosas y variadas oportunidades para demostrar todo el alcance de sus logros. Las categorías de evaluación y los desgloses son los siguientes: 

  • Conocimientos 30% 
  • Investigación sobre el pensamiento 25%  
  • Aplicación 25%  
  • Comunicación 20% 

La nota final se determinará de la siguiente manera:  

  • Trabajo trimestral 70% 
  • Final Evaluation ISU 15% Exam 15%
Consideración para la planificación de programas

A los estudiantes con necesidades especiales y a los que aprenden inglés se les proporcionará alojamiento, incluyendo tiempo adicional, tecnología de asistencia y escriba cuando esté disponible.

Habilidades de aprendizaje

Las Capacidades de Aprendizaje que se enumeran a continuación son fundamentales para el éxito de los alumnos. Las Habilidades de Aprendizaje se evalúan independientemente de los logros y se determinan a través de la observación y la participación. Se utilizará una lista de comprobación y una conferencia del alumno para determinar el nivel en cada categoría.

  1. Responsabilidad  
  2. Organización  
  3. Trabajo independiente  
  4. Colaboración
  5. Iniciativa  
  6. Autorregulación
Recursos necesarios para el estudiante
  • Scientific calculator
Recursos proporcionados por el estudiante
  • PowerPoint and Video Lessons 
  • Activities and Assignments 
  • Recursos en línea

Comprar curso

$549.00

🇨🇦 Precio para estudiantes canadienses

ico-canaway

¿Necesitas ayuda?