Finite Mathematics covers mathematical concepts and techniques applicable to business and social sciences, including matrix algebra, linear programming, and probability.
Expected value tells us the average result we can expect from a random event over many trials. Variance measures how spread out the possible results are.
The expected value (\(E[X]\)) of a random variable \(X\) is:
\[ E[X] = \sum (x_i \times p_i) \]
where \(x_i\) is a possible outcome, and \(p_i\) is its probability.
Variance lets us know how much risk or variability is involved. High variance means outcomes can be very different from the average!
This knowledge is essential in finance, insurance, and any decision-making under uncertainty.
\[E[X] = \sum (x_i \times p_i)\]
Calculating the average winnings in a lottery game.
Determining how risky an investment is by measuring variance.
Expected value shows the likely outcome; variance tells us about the risk involved.