Statistics 101
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Master the fundamentals of statistics with Statistics 101. Learn key concepts like probability, hypothesis testing, and statistical inference, and apply them to real-world data analysis and decision-making scenarios in various industries.
At a Glance
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.
In the final module, using an open dataset, learn whether good looking professors indeed get better teaching evalutions.
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
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