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Statistics 101

BeginnerCourse

Welcome to the Statistics 101 course, taught by Murtaza Haider, Assistant Professor at Ryerson University. Statistics is one of the most challenging topics to learn, but Murtaza brings a gentle introduction to statistics in practice. Learn about descriptive statistics, variance, probability, correlation, and data visualization. This course ends with a fully-guided statistics exercise exploring the “hot” topic of: do good looking professors get better teaching evaluations? A free trial of SPSS Statistics is included in this course.

4.6 (1k+ Reviews)

Language

  • English

Topic

  • Statistics

Industries

  • Financial Services

Enrollment Count

  • 6.21K

Skills You Will Learn

  • Financial Services, Data Analysis, Information Technology

Offered By

  • IBM

Estimated Effort

  • 3-4 Hours

Platform

  • SkillsNetwork

Last Update

  • May 11, 2025
About this Course
Split into five modules, this is a beginner's course covering the fundamentals of statistics. Start with mean, mode, and median. Then learn about standard deviation using examples from basketball. Learn about probability with dice. Learn what it means to group data by categorical variables, and how you can transform your data into appropriate graphs and charts.

In the final module, using an open dataset, learn whether good looking professors indeed get better teaching evalutions.

This course is taught using SPSS Statistics. No prior experience necesssary. A free trial is available through this course, available here: SPSS Statistics (Free Trial).

COURSE SYLLABUS

Module 1 - Welcome to Statistics!
  • Welcome to Statistics
  • Data visualization
  • All about data
  • SPSS Statistics
  • SPSS Statistics in 5 minutes
  • Lab exercises

Module 2 - Basic Statistics
  • Types of data
  • Measures of dispersion
  • Mean, median, mode
  • Statistics by data type
  • Probability
  • Lab exercises

Module 3 - Summarizing data
  • Statistics by groups
  • Visualization of group statistics
  • Pivoting
  • Cross-tabulations
  • Correlation
  • Lab exercises

Module 4- Data Visualization
  • Visualization fundamentals
  • Descriptive and statistical charts
  • Scatterplots
  • Statistical charts
  • Time series charts
  • Lab exercises

Module 5 - Does Beauty Pay?
  • Does Beauty Pay?
  • Weighted means, standard deviations
  • Data wrangling
  • Descriptive Statistics
  • Reproducibility with syntax in SPSS Statistics
  • Lab exercises

GENERAL INFORMATION
  • It is self-paced.
  • It can be taken at any time.
  • It can be audited as many times as you wish.

RECOMMENDED SKILLS PRIOR TO TAKING THIS COURSE
  • None

REQUIREMENTS
  • None

Instructors

Murtaza Haider

Associate professor of Real Estate Management at the Ted Rogers School of Management, Ryerson University, in Toronto. Murtaza is also the Director of a consulting firm Regionomics Inc. and an adjunct professor of engineering at McGill University

Murtaza Haider is an associate professor of Real Estate Management at the Ted Rogers School of Management, Ryerson University, in Toronto. Murtaza is also the Director of a consulting firm Regionomics Inc. and an adjunct professor of engineering at McGill University. Murtaza Haider is the author of Getting Started with Data Science: Making Sense of Data with Analytics,which was published by Pearson/IBM Press in 2016. Murtaza Haider specializes in applying analytics and statistical models to find solutions for socio-economic challenges. His research interests include business analytics, data science, forecasting housing market dynamics, transport/infrastructure/urban planning, and human development in Canada and South Asia. Murtaza Haider holds a Masters in transport engineering and planning and a Ph.D. in Civil Engineering (Urban Systems Analysis) from the University of Toronto.

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