Variations in Assumptions - Sensativity Analysis

The video tutorial explains sensitivity analysis, a method used to assess how changes in one factor affect outcomes. It covers the types of variables involved, such as target and independent variables, and the role of assumptions in creating scenarios. The process involves using historical data to establish a baseline and making hypothetical changes to test outcomes. The tutorial emphasizes the importance of assumptions and the scientific method in validating hypotheses.

What is another name for sensitivity analysis?

• What-if analysis

• Risk assessment

• Cost-benefit analysis

• Market analysis

Which of the following is an example of an independent variable in a sensitivity analysis?

• Profitability

• Consumer demand

• Product cost

• Tax rate

What is the purpose of making assumptions in a sensitivity analysis?

• To eliminate variables

• To calculate exact outcomes

• To determine constant factors in a scenario

• To predict future trends

How are historical data used in sensitivity analysis?

• To predict future outcomes

• To calculate exact metrics

• To determine relevant factors for the outcome

• To eliminate irrelevant variables

What is the first step in conducting a sensitivity analysis?

• Testing hypotheses

• Looking at historical data

• Identifying target variables

• Making hypothetical changes

In sensitivity analysis, what is the role of a baseline?

• To serve as a control for comparison

• To predict future changes

• To eliminate variables

• To calculate exact outcomes

What is the final step in a sensitivity analysis?

• Testing hypotheses

• Collecting data

• Making assumptions

• Identifying variables