An Example of a First-Order Model with Three Predictor Variables $\beta$

question 3

Multiple Choice

An example of a first-order model with three predictor variables is

• A) y = \(\beta\)₀ + \(\beta\)₁x₁ + \(\beta\)₂x₂ +\(\beta\)₃x₃ +\(\varepsilon\)
• B) y = \(\beta\)₀ + \(\beta\)₁x₁ + \(\beta\)₂x₂ + \(\varepsilon\)
• C) y = \(\beta\)₀ + \(\beta\)₁x² +\(\beta\)₃x₃+ \(\varepsilon\)
• D) y² = \(\beta\)₀ + \(\beta\)₁x₁ + \(\beta\)₂x₂+\(\beta\)₃x₃ + \(\varepsilon\).

---

Definitions:

Probability Distributions

Mathematical functions that provide the probabilities of occurrence of different possible outcomes for an experiment.

Expected Value

A calculated average of all possible values in a random variable, weighted by each value's probability of occurrence.

Perfect Information

A situation in which all participants have access to all relevant information without any restrictions.

Expected Monetary Value

This calculates the predicted value of a financial decision by weighing possible outcomes by their probabilities and summing the results.