QMS210: Applied Statistics for Business – Course Outline and Study Guide

Course Overview

Introduction to Applied Statistics for Business

This course, QMS210: Applied Statistics for Business, introduces students to both descriptive and inferential statistics, focusing on their application in managerial decision-making within business contexts. The curriculum covers a wide range of statistical concepts, including data collection, graphical and numerical summarization, probability theory, sampling distributions, hypothesis testing, and regression analysis.

Course Structure and Topics

Weekly Topics and Corresponding Chapters

The course is organized into weekly modules, each covering essential topics in business statistics. Below is a summary of the main topics and their alignment with standard business statistics chapters:

• Week 1: Types of Data, Measurement Scales, Graphical Presentation (Ch. 1, 2, 3)

• Week 2: Measures of Central Tendency and Variability, Skewness (Ch. 4)

• Week 3: Discrete Probability, Binomial and Poisson Distributions (Ch. 6)

• Week 4: Normal Distribution, Standard Normal (z) (Ch. 7)

• Week 5: Central Limit Theorem, Sampling Distributions (Ch. 8)

• Week 6: Confidence Interval Estimation for Mean and Proportion (Ch. 10)

• Week 7: Fundamentals of Hypothesis Testing, Type I & II Errors (Ch. 11)

• Week 8: Two-Sample Tests, F-test for Variances (Ch. 12)

• Week 9: Hypothesis Testing for Means and Proportions of Two Populations (Ch. 12)

• Week 10: One Way ANOVA (Ch. 13)

• Week 11: Simple Linear Regression (Ch. 15)

• Week 12: Multiple Regression (Ch. 16)

Learning Outcomes

Key Competencies Developed

• Present and Describe Information: Use numerical and graphical descriptive summary measures; interpret data from graphical presentations such as stem-and-leaf plots, frequency distributions, histograms, and OGIVE.

• Apply Probability Concepts: Decide when and how to use probability distributions (Binomial, Poisson, Normal) to quantify uncertainty and assess risk.

• Draw Conclusions from Samples: Estimate population parameters, perform hypothesis testing (including ANOVA and multiple tests), understand Type I and II errors, and use regression techniques for forecasting.

• Use Statistical Software: Apply SPSS and other tools to organize, analyze, and present data in business reports.

Assessment and Evaluation

Grading Components

The course grade is determined by the following components:

Component	Weight (%)	Coverage	Date
Midterm Test	25	Weeks 1-6	March 15
SPSS Individual Project	10	SPSS use for covered topics	March 29
MyLab Homework (Best 10 of 12 modules)	20	Weeks 1-12	Weekly
Final Exam	45	Weeks 1-12	TBA

Required Materials

Textbook, Calculator, and Software

• Textbook: Business Statistics, 15th custom edition for Toronto Metropolitan University (e-textbook via MyLab Statistics).

• Calculator: CASIO fx-9750GIII (or similar model).

• Software: SPSS (available free through university resources).

Academic Integrity and Policies

Key Policies and Expectations

• Academic Integrity: All submitted work must be original; use of generative AI is restricted to idea generation and study aid, not for submitted work.

• Copyright: Course materials are copyrighted and may not be shared without permission.

• Assessment Policies: No extensions for assignments or projects; strict procedures for missed tests/exams and accommodations.

• Grading Scale: Letter grades and grade point conversions are provided for performance evaluation.

Course Schedule

Weekly Breakdown

Week	Topic	Chapter	MyLab Module
1	Types of Data, Measurement Scale, Graphical Presentation	1, 2, 3	1
2	Central Tendency, Variability, Skewness	4	2
3	Discrete Probability, Binomial, Poisson	6	3
4	Normal Distribution, Standard Normal	7	4
5	Central Limit Theorem, Sampling Distribution	8	5
6	Confidence Interval Estimation	10	6
7	Hypothesis Testing Fundamentals	11	7
8	Two-Sample Tests, F-test	12	8
9	Hypothesis Testing for Two Populations	12	9
10	One Way ANOVA	13	10
11	Simple Linear Regression	15	11
12	Multiple Regression	16	12

Important Resources and Support

Student Support Services

• University Libraries: Research workshops and consultations.

• Student Life and Learning Support: Help with writing, math, study skills, and transition support.

• Academic Accommodation Support (AAS): Disability services and accommodations.

• Wellbeing Support: Mental health and crisis resources.

Course Policies and Procedures

Assessment, Accommodation, and Academic Appeals

• Strict adherence to deadlines for assignments and projects.

• Procedures for missed tests/exams require timely submission of Academic Consideration Request (ACR) forms and supporting documentation.

• Makeup tests/exams are available only upon approval and must be completed within specified timeframes.

• INC (Incomplete) grades are assigned for missed final exams with approved documentation and must be resolved within three months.

Grading Scale

Letter Grades and Grade Point Conversion

Letter Grade	Grade Point	Conversion Range (%)
A+	4.33	90-100
A	4.00	85-89
A-	3.67	80-84
B+	3.33	77-79
B	3.00	73-76
B-	2.67	70-72
C+	2.33	67-69
C	2.00	63-66
C-	1.67	60-62
D+	1.33	57-59
D	1.00	53-56
D-	0.67	50-52
F	0.00	0-49

Course Software and Tools

SPSS and MyLab Statistics

• SPSS: Required for statistical analysis and reporting; available free to students.

• MyLab Statistics: Platform for e-textbook, assignments, and practice modules.

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Additional Info

This course outline provides a comprehensive overview of the structure, content, and expectations for QMS210: Applied Statistics for Business. Students are encouraged to regularly consult the course website and D2L for updates, resources, and announcements.