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Understanding how probabilities work is essential in Statistics. An important concept here is the "Addition Rule of Probability." This rule helps in finding the probability of either one event or another occurring. If two events can happen but not at the same time (called mutually exclusive events), you simply add their probabilities to find the combined likelihood.
For instance, in this exercise, knowing if a grocery chain makes an income between \(1 million and \)20 million, or $20 million or more, requires adding these separate probabilities together. Since these two events can't happen simultaneously, adding them fits our rule.
The rule is written as: \[ P(A \text{ or } B) = P(A) + P(B) \]As shown in the problem, after calculating each probability, simply add them to find the result. Understanding this concept will help you see how separate events combine in real-world scenarios.

Probability is simply a way to measure how likely an event is to happen. It’s calculated by dividing the number of successful outcomes by the total number of possible outcomes.
For this problem, you were given three income categories for grocery chains. To find the probability that a chain makes an income under \(1 million, you take the number of chains (102) in this bracket and divide it by the total number of chains (200). This calculation gives a probability of 0.51, meaning there's a 51% chance a randomly picked grocery chain earns under \)1 million.
The following formulas were used:

• Income Under \(1 Million: \( P = \frac{102}{200} = 0.51 \)
• Between \)1 Million and \(20 Million: \( P = \frac{61}{200} = 0.305 \)
• Income \)20 Million or More: \( P = \frac{37}{200} = 0.185 \)

These calculations show how to break down and understand probability using everyday business data.

Statistical Analysis is a critical skill in business to make informed decisions. By understanding probabilities, businesses can gauge risks and opportunities.
Analyzing incomes of grocery chains, like the example given, lets businesses understand financial landscapes. Suppose you're an investor deciding where to place money. You'd want to know which chains are most likely to succeed based on their income brackets.
Making data-driven decisions involves:

• Collecting accurate data
• Performing probability calculations
• Interpreting results to foresee trends and make predictions

This approach is invaluable for risk management, strategic planning, and optimizing profit margins. By mastering statistical tools, businesses harness more precise insights into their operations and external market conditions.