Introduction to Statistical Inference

The ability to apply Statistics in order to correctly interpret data is becoming increasingly important in several sectors such as finance, engineering and public health. In this course, we introduce the notion of descriptive statistics by covering univariate and bivariate statistics. In the next part, we cover data visualization by introducing the most important graphing tools. Furthermore, we study the most common discrete and continuous distributions. Finally, we introduce classical methods for statistical inference such Central Limit Theorem, Confidence interval and Hypothesis testing with applications.

Course Objective

This midlevel course is designed to introduce students to Statistical Inference tools.

Learning Outcome

After this course, students should have a broad overview of statistical tools for data analysis.

This course is open to the general public.

This course is open to the general public. 

1. I. Introduction to Statistics
2. II. Introduction to Statistics:
   1. 1) Univariate statistics
   2. 2) Bivariate statistics
3. III. Data visualization
   1. 1) Scatter Plots
   2. 2) Histograms
4. IV. Introduction to distributions
   1. 1) Discrete distributions
   2. 2) Continuous distributions
5. V. Classical statistical inference
   1. 1) Central Limit Theorem
   2. 2) Point Estimation
   3. 3) Confidence Intervals
   4. 4) Introduction to Hypothesis Testing