Motivation to do Track 04
Theme: an important practical question would be what is the expected value of illegal containers found in the baseline scenario? The random inspection rate is fixed, with 100 random inspections and 1000 containers in total. We know that there are 50 containers that are illegal. What is the probability of selecting the first container, and finding an illegal container in this situation? Or how to use historically based statistics to calculate probability given that information?
This learning path is designed to develop the concepts related to probability definition:
Understand the concept of experiment, observation, and sample space.
Sample space representations: Venn diagram and Tree diagram.
Simple and composite events and how their probabilities could be computed.
Three definitions for probability
Law of large numbers and how to use frequency as an approximation to probability.
This learning path is designed to develop the following skills:
Construct a coin simulator that will help to relate frequencies of events and their probabilities.
Construct a six-face dice simulator that will help to relate frequencies of events and their probabilities.
How to compute the frequency of each category using information from a database.
Construct tables about the frequencies of each category.
Compute simple or marginal probabilities from frequencies extracted from a database.
Compute conditional probabilities from frequencies extracted from a database.
The next links will help in this learning journey. Have a good learning journey.
The journey map of Track 04
Badges
WITS Customs
Data Clean
Python LVL 4
STATS & PROB 3
DICE Simulator
COIN Simulator
GET PROB 1
Inspect LVL 1
1. Concepts & Definitions
1.1. Experiment, observation, and sample space
1.2. Sample space: Venn and Tree diagram
1.3. Simple and composite events
1.4. Three definitions of probability
1.5. Law of large numbers and its consequences
1.6. Frequency and empirical probability
2. Problem & Solution
2.4. Frequency of categories from tables
2.5. Simple and marginal probabilities
2.6. Conditional probabilities
1. Concepts & Definitions
2. Problem & Solution