COURSE OVERVIEW:
In some ways, probability and statistics are opposites. Statistics tells us general information about the world, even if we don’t understand the processes that made it happen. Probability is a way of calculating facts about the world, but only if we understand the underlying process.
One way that probability fits in with statistics is that, in order to prove that this or that statistical technique will actually do what it is supposed to do, statistical theoreticians make assumptions as to how the underlying process works and use probability theory to prove mathematically that statistics will give the right answer. Obviously, that kind of theoretical connection between probability and statistics isn’t too useful, although knowing that it is true can give us confidence that statistics actually works.
The most important way that probability fits in with statistics is that it shows us the way that numbers calculated from a sample relate to the numbers for the population. Every element of statistics that we actually use in business or elsewhere is calculated from the sample, because the population is just a theoretical abstraction. For every practical element of statistics based on the sample, there is a corresponding theoretical element based on the population.
Therefore, probability has an important role in statistical theory. In this course we use the notion of probability to introduce the important statistical notions of independence and distributions.
This course will help you understand what probability is and how probability fits in with statistics. Then we explain how to measure likelihoods and the three types of probability. Finally, we discuss how probability is used in statistics and the laws of probability.
LEARNING OUTCOMES:
By the end of this course, you will be able to understand:
- What is probability?
- How probability fits in with statistics?
- How to measure likelihoods?
- The simple numbers for chances
- The notion of odds
- Proportions and percentages
- When ratios greater than one
- The three concepts of probability
- The rule of insufficient reason for classical probability
- How to measure probabilities with proportions?
- The basic rules of probability
- Probabilities in the real world
- The mutually exclusive events
- The replication and the frequency approach
- Sampling with replacement
- Sampling without replacement
- Common sense and subjective likelihoods
- Subjective probability
- How to use probability for statistics?
- The conditional and unconditional likelihoods
- Mill’s method for detecting the true cause of something observed in the world
- What is a random variable?
- Statistical dependence and independence
- Why in statistics, the focus is almost always on statistical independence, rather than on statistical dependence?
- Errors in sampling
- What is a probability distribution?
- Theoretical distributions
- The laws of probability
- The rules that define how probabilities are measured
- The rules that define how probabilities are combined
COURSE DURATION:
The typical duration of this course is approximately 2-3 hours to complete. Your enrolment is Valid for 12 Months. Start anytime and study at your own pace.
COURSE REQUIREMENTS:
You must have access to a computer or any mobile device with Adobe Acrobat Reader (free PDF Viewer) installed, to complete this course.
COURSE DELIVERY:
Purchase and download course content.
ASSESSMENT:
A simple 10-question true or false quiz with Unlimited Submission Attempts.
CERTIFICATION:
Upon course completion, you will receive a customised digital “Certificate of Completion”.