Why math, statistics, and Python?
Module 0
Math, Statistics, and Python Starter
A practical bridge into econometrics with beginner-friendly notation, summary statistics, uncertainty, and Python data workflows.
20 lessons4 to 6 hours
Start first lessonLessons
1Why do we need math, statistics, and Python for econometrics?How do math, statistics, and Python help us answer economic questions with data?Open2Variables, equations, and functionsHow can we write economic ideas in a compact way?Open3Reading simple mathematical notationHow do we read common symbols without getting lost?Open4Summation notationHow do we write 'add all these values' in one symbol?Open5Mean, median, variance, and standard deviationHow can we describe the center and spread of a variable?Open6Covariance and correlationHow do we describe whether two variables move together?Open7Probability basicsHow do we talk about uncertainty in a disciplined way?Open8Random variablesHow can one variable have uncertain possible values?Open9Normal distributionWhy does the bell curve show up so often?Open10Sampling and sample vs. populationWhat is the difference between the data we have and the group we care about?Open11Hypothesis testing intuitionHow do we decide whether a data pattern is surprising?Open12Confidence intervals intuitionHow can we report uncertainty without pretending to know the exact answer?Open13Introduction to PythonWhy is Python useful for learning econometrics?Open14Python variables and basic calculationsHow does Python remember values and calculate with them?Open15Working with pandas DataFramesHow does Python store a dataset like a spreadsheet?Open16Loading CSV data in PythonHow do we bring a dataset into Python?Open17Descriptive statistics in PythonHow can Python quickly summarize a dataset?Open18Creating simple graphs in PythonHow can graphs make data patterns easier to see?Open19Mini Python practice labCan we combine loading, summarizing, and graphing in one short workflow?Open20Module 0 review quizAre you ready to start econometrics with the basic tools in place?Open
Scored review quiz
Module 0 review
These questions sample ideas from across the module. Answer all questions, submit once, then review the explanations and score.
0/20 answered
Variables, equations, and functions
2. In wage = f(education, experience), what is the best interpretation of the function?
Reading mathematical notation
3. In wage_i, what does the subscript i help us track?
Summation notation
4. If a formula uses a summation over i = 1 to n, what is it asking us to do?
Mean, median, variance, and standard deviation
5. A wage variable has a high standard deviation. What does that most directly tell us?
Covariance and correlation
6. A correlation between education and wage is positive. What is the strongest accurate interpretation at this stage?
Probability basics
7. If P(employed) = 0.92, which statement correctly uses the complement rule?
Random variables
8. Before observing a graduate's first wage offer, why can the wage be treated as a random variable?
Normal distribution
9. Why is the normal distribution useful in an introductory econometrics course?
Sampling and sample vs. population
10. A survey of 1,000 workers is used to learn about all workers in a region. What is the population?
Hypothesis testing intuition
11. In a test of whether education is related to wage, what does H0: beta1 = 0 usually represent?
Confidence intervals intuition
12. Why is a confidence interval often more informative than only reporting one estimate?
Introduction to Python
13. Why is reproducible Python code valuable in data analysis?
Python variables and basic calculations
14. If hourly_wage = 20 and hours = 35, what is Python doing when it calculates hourly_wage * hours?
Working with pandas DataFrames
15. In a DataFrame for wage data, what does one row usually represent?
Loading CSV data in Python
16. After running df = pd.read_csv('wage_sample.csv'), what is df?
Descriptive statistics in Python
17. Why should students run df.describe() before estimating a model?
Creating simple graphs in Python
18. What is the main learning value of a scatter plot of education and wage?
Mini Python practice lab
19. Which sequence best reflects a careful first Python workflow?
Module 0 review
20. What is the main purpose of Module 0 in this course?
Choices are shuffled each time the review starts.