Normal distribution tables - part 2

In this lesson

1. 0:00 Understanding confidence levels and value at risk
2. 2:02 How normal distribution explains investment outcomes
3. 5:02 Using z scores to calculate confidence ranges
4. 6:00 Reading normal distribution tables for z scores
5. 10:18 Applying 99% confidence level calculations

About this lesson

You'll discover how to determine the probability that an actual return falls within a specific range, and how to identify the worst-case scenario you can expect with 95% or 99% confidence. This technique is particularly useful when evaluating whether a project will meet your minimum acceptable return, and it's a common requirement across CIMA and ACCA papers dealing with financial decision-making. The lesson walks you through the mechanics of reading normal distribution tables to find z scores. You'll learn that a 95% confidence level captures 95% of all possible outcomes (with only a 5% chance of a worse result), while a 99% confidence level is more conservative, leaving just a 1% probability of underperformance. The key z scores you'll use are 1.645 for 95% confidence and 2.326 for 99% confidence—these tell you how many standard deviations to move left from your expected value to find the lower boundary of your range. By the end, you'll be able to calculate value at risk for any project or investment scenario. This means you can quantify downside risk and make confident decisions about whether a project's worst-case outcome (within your chosen confidence level) is acceptable. This practical application bridges theory and real-world financial analysis, making it directly relevant to case study questions and strategic decision-making contexts you'll encounter in your qualification.

Duration: 13m