Ch 1 stats

Course Information

• Course Title: SCMA 1000 - Business Statistics

• Instructor: Professor Thomas Foard

• Office Location: GH 208-TBD

• Email: thomas.foard@guelphhumber.ca

Course Schedule

Week Dates and Topics

1. Jan 6 & 9

   • Chapter 1: Introduction, Statistics and Data

2. Jan 13 & 16

   • Chapter 2: Describing Data Using Tables and Graphs

3. Jan 20 & 23

   • Chapter 3: Description Using Numerical Measures

4. Jan 27 & 30

   • Chapter 4: Probabilities

   • Chapter 5: Discrete Probability Distributions

5. Feb 3 & 6

   • Chapter 6: Continuous Probability Distributions

   • Chapter 7: Sampling Distributions

6. Feb 10 & 13

   • Chapter 8: Interval Estimation

   • No Classes: Reading Week Feb 20 & 24

7. Feb 24 & 27

   • Assignment 1 Due

   • Midterm Exam (In Class with Computers)

8. Mar 3 & 6

   • Chapter 9: Hypothesis Testing

9. Mar 10 & 13

   • Chapter 10: Inference about Means and Proportions (2 Populations)

   • Chapter 11: Comparisons Involving Proportions

10. Mar 17 & 20

• Chapter 13: Experimental Design and Analysis

11. Mar 29 & 30

• Chapter 14: Simple Linear Regression

• Chapter 15: Multiple Regression

12. Apr 5 & 6

• Assignment 2 Due

• Review for Final Exam (Date TBD)

Evaluation Components

• Midterm Exam: 25% - Week Feb 24 & 27 (In Class with Computers)

• Final Exam: 30% - Week 12+ (Specific Date TBD)

• Quizzes: 25% (Best 10 out of 11 - lowest score dropped)

  • Quizzes open after each class and close before the next class

Required Textbook

• Title: Essentials of Statistics for Business and EconomicsAuthors: Camm, Cochran, Fry, Ohlmann, Anderson, Sweeney, WilliamsEdition: 15th Edition (ISBN: 978-0-357-71585-7)Publisher: South-Western

Instructor Background

• Name: Tom Foard, Ph.D

• Relevant Experience:

  • Clinical Psychologist

  • Organizational Psychologist

  • Human Resource Executive

  • Experience teaching Organizational Behavior at undergraduate and graduate levels

Introduction to Statistics

• Purpose of Statistics: To collect, analyze, present, and interpret data to make informed business decisions.

Understanding Student Perspectives

• Questions:

  • What are your assumptions about statistics?

  • Are statistics about math?

• Common Descriptions of Students:

  • Volunteer (Love Stats, Curious)

  • Victim (Scared, Bored)

Data Collection and Statistics Basics

• Situations Explored:

  • Evaluating the validity of taking averages in student groups.

  • Understanding sample vs. population significance.

Statistics Applications in Business and Economics

Applications Overview

• Fields Utilizing Statistics:

  • Accounting (audits)

  • Economics (forecasts)

  • Finance (investment advice)

  • Marketing (data collection)

  • Production (quality control)

  • Information Systems (performance assessment)

Data Types and Measurement Scales

Data Types

• Definitions:

  • Elements: Entities on which data is collected

  • Variables: Characteristics of interest

  • Observations: Set of measurements for entities

Measurement Scales

• Nominal: Labels or names (e.g., WTO Status)

• Ordinal: Ranks (e.g., Fitch Rating)

• Interval: Numeric intervals (e.g., SAT scores)

• Ratio: Numeric ratios (e.g., height, weight)

Data Classifications

• Categorical: Qualitative data categorized into groups

• Quantitative: Numerical data permitting mathematical operations

  • Includes interval and ratio analysis

Ethical Guidelines in Statistical Practice

• Ethics in Statistics:

  • Avoid misleading practices (e.g., improper sampling, biased interpretation)

  • American Statistical Association's report on ethical practices

Summary of Key Concepts

• Statistics as the science of data analysis

• Understanding measurement scales for accurate data interpretation

• Inference processes utilizing samples for population insights

• Importance of ethical standards in statistical applications.

Next Steps

• Tasks Before Next Class:

  • Read Chapter 2

  • Complete the Week 1 Quiz

  • Prepare a question about the content.