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Data Handling - Calculating Simple Probabilities

Grade 6IB

Review the key concepts, formulae, and examples before starting your quiz.

🔑Concepts

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Probability is a measure of how likely an event is to happen, represented by a value between 00 and 11 inclusive. It can be expressed as a fraction, a decimal, or a percentage.

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The Probability Scale is a visual tool used to describe the likelihood of events. Imagine a horizontal number line starting at 00 (Impossible) and ending at 11 (Certain). The midpoint 0.50.5 or 12\frac{1}{2} represents an 'Even Chance' (like a coin flip). Outcomes between 00 and 0.50.5 are 'Unlikely,' while outcomes between 0.50.5 and 11 are 'Likely.'

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The Sample Space is the set of all possible outcomes of an experiment. For example, if you visualize a standard spinner divided into four equal sections colored Red, Blue, Green, and Yellow, the sample space is {Red,Blue,Green,Yellow}\{Red, Blue, Green, Yellow\}.

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An Event is a specific outcome or a collection of outcomes from the sample space that we are interested in. For instance, if rolling a six-sided die, the event 'rolling an even number' includes the outcomes {2,4,6}\{2, 4, 6\}.

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Equally Likely Outcomes occur when every possible result in an experiment has the same chance of happening. For example, on a fair six-sided die, each face (1, 2, 3, 4, 5, and 6) has an equal probability of 16\frac{1}{6}.

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Theoretical Probability is calculated based on reasoning about the possible outcomes. If you have a bag of 1010 marbles and 33 are blue, you can logically determine the chance of picking a blue marble without actually performing the experiment.

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Complementary Events represent the probability of an event NOT occurring. If the probability of it raining is P(A)P(A), then the probability of it not raining is P(not A)P(\text{not } A), and the sum of these two probabilities always equals 11.

📐Formulae

P(E)=Number of favorable outcomesTotal number of possible outcomesP(E) = \frac{\text{Number of favorable outcomes}}{\text{Total number of possible outcomes}}

P(not E)=1−P(E)P(\text{not } E) = 1 - P(E) archaeology

0≤P(E)≤10 \le P(E) \le 1

Sum of all probabilities=1\text{Sum of all probabilities} = 1

💡Examples

Problem 1:

A bag contains 55 red balls, 33 blue balls, and 22 yellow balls. If one ball is picked at random, what is the probability that it is blue?

Solution:

  1. Identify the number of favorable outcomes (blue balls): 33
  2. Calculate the total number of possible outcomes: 5+3+2=105 + 3 + 2 = 10
  3. Apply the formula: P(blue)=310P(\text{blue}) = \frac{3}{10}
  4. Express as a decimal or percentage: 0.30.3 or 30%30\%

Explanation:

We divide the number of blue balls by the total number of balls in the bag to find the theoretical probability.

Problem 2:

A fair six-sided die is rolled once. What is the probability of rolling a number greater than 44?

Solution:

  1. List the sample space: S={1,2,3,4,5,6}S = \{1, 2, 3, 4, 5, 6\}. Total outcomes = 66
  2. Identify outcomes greater than 44: {5,6}\{5, 6\}. Number of favorable outcomes = 22
  3. Apply the formula: P(>4)=26P(>4) = \frac{2}{6}
  4. Simplify the fraction: 26=13\frac{2}{6} = \frac{1}{3}

Explanation:

To solve this, we identify which numbers on the die satisfy the condition 'greater than 4' and divide that count by the total faces on the die.