Sampling and Hypothesis Testing
Multivariate Distributions, Sample Statistics, and Statistical Tests
About This Course
Course Information
On completion of this course course, you will be able to: Focus on the extensions required to understand multivariate random variables, including how expectations change, new moments, and additional characterisations of uncertainty. Describe how sample moments are used to estimate unknown population moments. outline the steps used to test hypotheses. This course accounts for 2 units of CPD . One unit is the equivalent of one hour of learning. A certificate will be issued once you have completed all 2 units.
Course Sections
This CPD course is made up of the following sections:
- Multivariate Radom Variables (video + quiz)
- Sample Moments (video + quiz)
- Hypothesis Testing (video + quiz)
- Additional reading materials
What You Will Learn
- Define joint probability mass functions and marginal distributions for multivariate random variables
- Explain the correlation operator and its relationship to covariance and standard deviation
- Calculate sample mean, variance, skewness, and kurtosis from observed data
- Describe co-skewness and co-kurtosis and what they reveal about the behaviour of paired variables
- Distinguish between Type I and Type II errors in hypothesis testing
- Apply decision rules using test statistics, critical values, and confidence intervals
Who This Course Is For
- Finance professionals who work with statistical models or data-driven risk analysis
- Accountants or analysts who need a grounding in quantitative methods for portfolio or risk assessment
- Professionals preparing for FRM or similar quantitative finance examinations
Prerequisites
- Working knowledge of basic probability concepts, including expected value and standard deviation
- Familiarity with single-variable random distributions
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