Review the key concepts, formulae, and examples before starting your quiz.
🔑Concepts
Random Experiment and Outcomes: A random experiment is a process where the result cannot be predicted with certainty. For example, tossing a fair coin is an experiment where the possible outcomes are Heads () or Tails (). Visualize a coin spinning in the air; until it lands, the outcome is unknown, but we know it must be one of these two results.
Sample Space (): The set of all possible outcomes of a random experiment is called the sample space. For a single throw of a six-sided die, the sample space is , which can be visualized as the six distinct faces of the cube labeled with dots.
Event (): An event is a subset of the sample space consisting of one or more outcomes. For instance, in a die roll, the event 'getting an even number' corresponds to the set . Visualize this as highlighting only the specific outcomes you are looking for within the entire sample space.
Equally Likely Outcomes: Outcomes are said to be equally likely if none of them is expected to occur in preference to others. In a well-shuffled deck of cards, every card has the same chance of being picked. Visualize a balanced scale where every individual outcome carries the same 'weight' or chance.
Probability Scale: The probability of an event is always a real number between and inclusive. Visualize a number line where represents an 'Impossible Event' (like rolling a on a standard die) and represents a 'Sure Event' (like rolling a number less than on a standard die).
Complementary Events: For every event , there is an event 'not ' (denoted as or ) which occurs when does not occur. Visualize a Venn diagram where a rectangular box is the whole sample space and a circle inside represents ; the region outside the circle but inside the box is . The sum of their probabilities is always .
Deck of Cards Composition: A standard deck contains cards divided into suits: Hearts, Diamonds, Spades, and Clubs. Visualize cards in each suit (). Hearts and Diamonds are red ( cards), while Spades and Clubs are black ( cards). There are 'face cards' (Jacks, Queens, Kings) in total.
Theoretical Probability: This is the ratio of the number of outcomes favorable to an event to the total number of possible outcomes in a sample space. Visualize this as a fraction where the 'target' outcomes are the numerator and the 'total' possibilities are the denominator.
📐Formulae
or
(Probability of an impossible event)
(Probability of a sure event)
💡Examples
Problem 1:
A bag contains red balls, white balls, and green balls. A ball is drawn at random from the bag. Find the probability that the ball drawn is (i) white, (ii) not green.
Solution:
Step 1: Find the total number of outcomes . Total balls . So, . \nStep 2: For (i), let be the event of drawing a white ball. The number of favorable outcomes . \nStep 3: Calculate . \nStep 4: For (ii), let be the event of drawing a green ball. . The event 'not green' is . \nStep 5: Calculate . (Alternatively, favorable outcomes for 'not green' are red or white balls: )
Explanation:
This problem uses the basic definition of probability and the concept of complementary events. We first identify the total count (sample space) and then the specific counts for the target events.
Problem 2:
A card is drawn from a well-shuffled pack of playing cards. Find the probability that the card drawn is (i) a face card, (ii) a red king.
Solution:
Step 1: Total number of possible outcomes . \nStep 2: For (i), face cards are Jacks, Queens, and Kings. There are face cards in each of the suits. Total face cards . \nStep 3: . Simplifying by dividing both by , we get . \nStep 4: For (ii), identify red kings. The red suits are Hearts and Diamonds. Each has king. Total red kings . \nStep 5: .
Explanation:
To solve card problems, you must know the composition of the deck. We identify the subset of cards that satisfy the condition (face cards or red kings) and divide by the total number of cards.