Month 4 of 7 · 20–22 hours
Statistics for Data Analysis
Statistics gives you the vocabulary and tools to describe data honestly. This course explains the ideas in plain language with small worked examples before any formulas. You will summarize data with averages and spread, learn the basics of probability, recognize common data shapes, measure relationships with correlation, find outliers and bring it all together in an exploratory analysis.
Weeks
- Week 1Descriptive Statistics: Mean, Median and ModeSummarize a set of numbers with a single typical value, and know which one to trust.4–5 hours · 2 videosDone
- Week 2Standard Deviation and Probability BasicsMeasure how spread out data is, and reason about how likely events are.5 hours · 3 videosDone
- Week 3Data Distributions and Correlation AnalysisSee the shape of your data and measure how two variables move together.5–6 hours · 3 videosDone
- Week 4Outlier Detection and Exploratory AnalysisFind unusual values and follow a repeatable process to explore any new dataset.6 hours · 4 videosDone
- FinalExploratory Data Analysis ReportGraded project with a rubric.
What you will be able to do
- Calculate and interpret the mean, median and mode, and choose the right one.
- Measure spread with range, variance and standard deviation.
- Calculate simple probabilities and explain independent events.
- Describe the shape of a distribution, including the normal distribution and skew.
- Measure and interpret correlation, and explain why correlation is not causation.
- Detect outliers with the IQR rule and carry out a structured exploratory analysis.
Before you start
Prerequisites: Basic arithmetic. Course 1 (Excel) is helpful for the hands-on work.
Tools: Excel or Google Sheets for every exercise. Learners who took Course 3 can repeat the exercises in Python with pandas.
Schedule
| Week | Topics | Time |
|---|---|---|
| Week 1 | Descriptive Statistics: Mean, Median and Mode | 4 to 5 hrs |
| Week 2 | Standard Deviation and Probability Basics | 5 hrs |
| Week 3 | Data Distributions and Correlation Analysis | 5 to 6 hrs |
| Week 4 | Outlier Detection and Exploratory Analysis | 6 hrs |
Each week includes learning objectives, plain-language lessons with examples, beginner videos, a practice activity, a self-check quiz with answers and a graded assignment.