This course teaches the fundamentals of quantitative techniques essential in financial analysis. .
The course starts with concepts and techniques of time value of money which are a fundamental tool for financial analysis, corporate finance, valuation, and other investment decisions. We then introduce descriptive statistics that provides essential tools for describing and evaluating return and risk.
Furthermore, the course introduces some of the discrete and continuous probability distributions most commonly used to describe the behavior of random variables. We then move to probability theory and calculations that are widely used in finance, for example, in the field of investment and project valuation and in financial risk management. Probability theory concepts are needed to understand investment decision-making under conditions of uncertainty.
Then we explain how to estimate different parameters (e.g., mean and standard deviation) of a population if only a sample, rather than the whole population, can be observed. Hypothesis testing is a closely related topic. Finally, the course presents techniques that are used to accept or reject an assumed hypothesis (null hypothesis) about various parameters of a population.
Enroll now using the button above, or join our Data Science for Finance Membership to get access to all our courses. Learn more about membership.