STAT 5002 Quantitative Methods for Managment PDF

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Summary

Class lecture of Quantitative Methods for Management...

Description

Non-Degree Course Outline

Faculty: Program Coordinators: Associate Dean:

Colleen Ball/Kate Zhang Mona Nouroozifar

Course Outline Academic Year: 2020 – 2021 Course Name: Quantitative Methods for Management - Online Land Acknowledgement Humber College is located in Adobigok, known as “Place of the Black Alders” in the Ojibwe Anishinaabe language. It is uniquely situated along GabeKanang Ziibi, the Humber River providing an integral connection for Indigenous peoples between the northern shore of Lake Ontario and the Lake Simcoe Georgian Bay region. In Honouring the Land, we are walking in the moccasin tracks of our ancestors and leaving our footprints for the future generations to come.

Faculty:

Faculty of Liberal Art & Sciences and Innovative Learning

Programs:

Global Business Management Post Graduate Certificate

Course Name:

Quantitative Methods for Management - (STAT 5002)

Pre-Requisite(s)

None

Co-Requisite(s)

None

Pre-Requisite(s) for:

None

Equates

None

Humber College Institute of Technology and Advanced Learning • This document is available in alternate format upon request.

Non-Degree Course Outline

Restrictions Credit Value

3

Total Course Hours

42

Developed By: Tan Le

Approved by: Associate Dean, Mona Nouroozifar

Course Description This is an introductory course in statistics and quantitative methods for business students. Emphasis is on the application of statistical and quantitative methods in business. Topics include break-even analysis, descriptive statistics, probability and probability distributions, estimation and hypothesis testing, correlation, simple linear regression, and introduction to time series forecasting methods.

Course Rationale Quantitative methods play a crucial part in the decision-making process. These methods include a number of mathematically oriented techniques necessary for success in today's business world.

Program Learning Outcomes Emphasized in this Course ▪

Collect, process and interpret data used to support international business.

Course Format: Course content will be delivered in the classroom through interactive lecture and discussion, with the support of Blackboard.

Course Learning Outcomes: 1. Use arithmetic and algebraic functions to solve basic business problems (e.g. a break-even analysis); 2. Distinguish between sample and population data; 3. Construct bar charts, line graphs, frequency histograms and box plots; Humber College Institute of Technology and Advanced Learning • This document is available in alternate format upon request.

Non-Degree Course Outline

4. Calculate mean, median and mode and understand the usefulness of these measures; 5. Calculate range, standard deviation, variance, and coefficient of variation and understand the usefulness of these measures; 6. Demonstrate understanding of the concepts of probability; 7. Calculate probabilities for Normal distribution using the Z table; 8. Explain sampling distribution and Central Limit Theorem; 9. Construct and explain confidence intervals for population mean using z and t tables; 10. Perform hypothesis testing for population mean; 11. Perform one-sided and two-sided hypothesis tests; 12. Perform hypothesis testing for difference of two population means; 13. Explain the strength of a linear relationship using the coefficient of correlation; 14. Explain simple linear regression analysis and multiple regression; 15. Calculate forecast using moving average, weighted moving average and exponential smoothing methods; 16. Use Excel to display and analyze data. OQF Category Depth and Breadth of Knowledge Knowledge of Methodologies Application of Knowledge Communication Skills Awareness of the Limits of Knowledge Professional Capacity/Autonomy

At the successful completion of this course the student will have demonstrated the ability to: ✓ ✓ ✓ ✓ ✓ ✓

Assessment Weighting Quizzes Assessments Mid-term Final Examination Total

Modules of Study

Humber College Institute of Technology and Advanced Learning • This document is available in alternate format upon request.

10% 30% 30% 30% 100%

Non-Degree Course Outline

UNIT

COURSE LEARNING OUTCOMES

RESOURCES

Module 1: Descriptive Statistics

Review of Algebraic functions (Break Even Analysis). Graphical presentation of data, bar chart, line chart, histograms, scatter plots, and box plots.

Module 2: Descriptive Statistics

Measure of central tendency: Mean, weighted mean, median and mode.

Descriptive Statistics

Measure of dispersion: Range, variance, standard deviation, and coefficient of variation.

Chapter 4: (Continued)

Module 3: Probability

Addition and multiplication rules of probability, conditional probability.

Chapter 6: Probability

Module 4: Probability Distribution Module 5: Statistical Inferences

Module 6: Statistical Inferences Module 7:

Probability tree. Normal distribution. Sampling distributions.

Professor's notes Chapter 1: What is Statistics? Chapter 2: Graphical Descriptive Techniques I. Chapter 3: Graphical Descriptive Techniques II. Chapter 5: Data Collection and Sampling. Chapter 4: Numerical Descriptive Techniques.

Chapter 8: Continuous Probability Distribution.

Central Limit Theorem. Estimation of population mean.

Chapter 9: Sampling Distribution. Chapter 10: Introduction to Estimation. Confidence intervals for population Chapter 12: Inference About a Population. mean. Midterm Test: 30% Hypothesis testing of population mean.

Chapter 11: Introduction to Hypothesis Testing.

Student’s t-distribution.

Chapter 12: (Continued) Inference About a Population.

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ASSESSMENTS Ch. 1: 1.2, 1.4, 1.6 Ch. 2: 2.2, 2.4, 2.6, 2.8, 2.10 2.16, 2.42, 2.58 Ch. 3: 3.6, 3.10, 3.56, 3.60 Ch.5: 5.2, 5.4, 5.14, 5.16 Ch. 4: 4.2, 4.4, 4.14 Lab Assignment #1: 7% Ch. 4: 4.30, 4.34, 4.38, 4.44, 4.58, 4.60, 4.62, 4.66 Ch. 6: 6.2, 6.5, 6.8, 6.20, 6.32, 6.34, 6.38, 6.42, 6.46, 6.64, 6.68, 6.96, 6.97, 6.108, 6.118 Ch. 8: 8.20, 8.22, 8.26, 8.28, 8.30, 8.38, 8.40, 8.42, 8.56, 8.62, 8.64, 8.70, 8.94, 8.96 Ch. 9: 9.15, 9.26, 9.30, 9.40 Ch.10: 10.16, 10.18, 10.26, 10.30, 10.58, 10.60, 10.62 Ch. 12: 12.2, 12.4, 12.6, 12.8, 12.10 Ch. 11: 11.4, 11.8, 11.10, 11.12, 11.14, 11.36, 11.38, 11.40, 11.42 Ch. 12: 12.12, 12.14, 12.16, 12.18, 12.20, 12.22,

Non-Degree Course Outline

UNIT

COURSE LEARNING OUTCOMES

RESOURCES

ASSESSMENTS

Statistical Inferences Module 8: Statistical Inferences

Small sample estimation and hypothesis testing. Hypothesis testing of difference between two population means.

Module 9: Correlation and Regression

Simple linear regression. Pearson’s correlation coefficients. Inferences of regression coefficients. Prediction using regression equation

Chapter 16: Simple Linear Regression and Correlation

Module 10: Multiple Regression Module 11: Forecasting

Multiple regression using Excel.

Chapter 17: Multiple Regression

Ch. 16: 16.2, 16.4, 16.6, 16.8 16.10, 16.12, 16.22, 16.26, 16.28, 16.30 Ch. 4: 4.86, 4.88, 4.90 Lab Assignment #3: 8% Ch. 17: 17.7, 17.8, 17.12

Time series decomposition. Moving average method. Exponential smoothing method. Forecast errors.

Chapter 20: Time-Series Analysis and Forecasting

Ch. 20: 20.1 – 20.17, 20.30, 20.32

Chapter 13: Inference About Comparing Two Populations.

Chapter 4: (Section 4.4)

12.24, 12.26, 12.28 Lab Major Assignment: 15% Ch. 13: 13.2, 13.4, 13.8, 13.10, 13.12, 13.16, 13.88, 13.90, 13.92 a

Professor’s notes Review Final Exam: 30%

Required Resources are online, Tools and/or Equipment: Statistics for Management and Economics, 11th Edition etextbook, https://www.cengage.com/coursepages/Humber_STAT1112and5002 SOFTWARE PACKAGES: Excel - Regular scientific calculator. Supplemental Resources: Additional resources may be introduced when useful to the course content or student experience

Humber College Institute of Technology and Advanced Learning • This document is available in alternate format upon request.

Non-Degree Course Outline

Prior Learning Assessment and Recognition (PLAR) Students who have prior learning in the material of this course may be eligible for a course credit in recognition of their prior learning. The following table indicates the method that is used to assess prior learning for this course, or it indicates that such an assessment is not available. Students must apply for consideration for a prior learning assessment through the Office of the Registrar, and there is usually a fee associated with the application. Portfolio

Challenge Exam

Skills Test

Interview

Other (Specify)

Not Available For PLAR

✓

Policies and Procedures It is the student’s responsibility to be aware of their obligations under Humber Policies and Procedures.

Academic Regulations It is the student’s responsibility to be aware of the College Academic Regulations. The Academic Regulations apply to all applicants to Humber and all current students enrolled in any program or course offered by Humber, in any location. Information about academic appeals is found in the Academic Regulations.

Accessible Learning Services Humber strives to create a welcoming environment for all students where equity, diversity and inclusion are paramount. Accessible Learning Services facilitates equal access for students with disabilities by coordinating academic accommodations and services. Staff in Accessible Learning Services are available by appointment to assess specific needs, provide referrals and arrange appropriate accommodations. If you require academic accommodations, contact: Accessible Learning Services: http://www.humber.ca/student-life/swac/accessible-learning North Campus: (416) 675-6622 X5090 Lakeshore Campus: (416) 675-6622 X3331

Academic Integrity Academic integrity is essentially honesty in all academic endeavors. Academic integrity requires that students avoid all forms of academic misconduct or dishonesty, including plagiarism, cheating on tests or exams or any misrepresentation of academic accomplishment. Humber College Institute of Technology and Advanced Learning • This document is available in alternate format upon request.

Non-Degree Course Outline

Disclaimer While every effort is made by the professor/faculty to cover all material listed in the outline, the order, content, and/or evaluation may change in the event of special circumstances (e.g. time constraints due to inclement weather, sickness, college closure, technology/equipment problems or changes, etc.). In any such case, students will be given appropriate notification.

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Humber College Institute of Technology and Advanced Learning • This document is available in alternate format upon request....