Quantitative Techniques

By the end of this course, learners will be able to:

• Develop a comprehensive understanding of statistical concepts and their practical application.

• Make valid inferences about a population based on both random and non-random samples.

• Explore data effectively to gain insights about the world and draw meaningful conclusions.

• Master measurement techniques and linear regression analysis for data interpretation and prediction.

• Acquire knowledge of probability trees, the law of large numbers, and decision making processes.

• Grasp the logic behind hypothesis testing, construct confidence intervals, and appreciate the significance of accounting for uncertainty in statistical inferences.

• Apply their knowledge to conduct robust data analyses that generate accurate and reliable insights for informed decision making.

Course Outline

Module 1:  Sampling and Adjustment

Module 2: Learning from Data; Exploratory Data Analysis

Module 3: Measurement

Module 4:  Introduction to Linear Regression

Module 5:  Understanding Linear Regression

Module 6:  Multiple Regression

Module 7:  Causal Identification

Module 8:  Uncertainty and the Scientific Process

Module 9:  Probability Trees

Module 10:  Law of Large Numbers

Module 11:  Decision Making

Module 12:  Putting it all Together