What does it mean when two events are complements?
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- 1. Intro to Stats and Collecting Data1h 14m
- 2. Describing Data with Tables and Graphs1h 56m
- 3. Describing Data Numerically2h 5m
- 4. Probability2h 16m
- 5. Binomial Distribution & Discrete Random Variables3h 6m
- 6. Normal Distribution and Continuous Random Variables2h 11m
- 7. Sampling Distributions & Confidence Intervals: Mean3h 23m
- Sampling Distribution of the Sample Mean and Central Limit Theorem19m
- Distribution of Sample Mean - ExcelBonus23m
- Introduction to Confidence Intervals15m
- Confidence Intervals for Population Mean1h 18m
- Determining the Minimum Sample Size Required12m
- Finding Probabilities and T Critical Values - ExcelBonus28m
- Confidence Intervals for Population Means - ExcelBonus25m
- 8. Sampling Distributions & Confidence Intervals: Proportion2h 10m
- 9. Hypothesis Testing for One Sample5h 8m
- Steps in Hypothesis Testing1h 6m
- Performing Hypothesis Tests: Means1h 4m
- Hypothesis Testing: Means - ExcelBonus42m
- Performing Hypothesis Tests: Proportions37m
- Hypothesis Testing: Proportions - ExcelBonus27m
- Performing Hypothesis Tests: Variance12m
- Critical Values and Rejection Regions28m
- Link Between Confidence Intervals and Hypothesis Testing12m
- Type I & Type II Errors16m
- 10. Hypothesis Testing for Two Samples5h 37m
- Two Proportions1h 13m
- Two Proportions Hypothesis Test - ExcelBonus28m
- Two Means - Unknown, Unequal Variance1h 3m
- Two Means - Unknown Variances Hypothesis Test - ExcelBonus12m
- Two Means - Unknown, Equal Variance15m
- Two Means - Unknown, Equal Variances Hypothesis Test - ExcelBonus9m
- Two Means - Known Variance12m
- Two Means - Sigma Known Hypothesis Test - ExcelBonus21m
- Two Means - Matched Pairs (Dependent Samples)42m
- Matched Pairs Hypothesis Test - ExcelBonus12m
- Two Variances and F Distribution29m
- Two Variances - Graphing CalculatorBonus16m
- 11. Correlation1h 24m
- 12. Regression3h 33m
- Linear Regression & Least Squares Method26m
- Residuals12m
- Coefficient of Determination12m
- Regression Line Equation and Coefficient of Determination - ExcelBonus8m
- Finding Residuals and Creating Residual Plots - ExcelBonus11m
- Inferences for Slope31m
- Enabling Data Analysis ToolpakBonus1m
- Regression Readout of the Data Analysis Toolpak - ExcelBonus21m
- Prediction Intervals13m
- Prediction Intervals - ExcelBonus19m
- Multiple Regression - ExcelBonus29m
- Quadratic Regression15m
- Quadratic Regression - ExcelBonus10m
- 13. Chi-Square Tests & Goodness of Fit2h 21m
- 14. ANOVA2h 28m
4. Probability
Complements
Problem 5.2.38c
Textbook Question
38. Getting to Work According to a survey, the probability that a randomly selected worker primarily rides a bicycle to work is 0.792. The probability that a randomly selected worker primarily takes public transportation to work is 0.071. (c) What is the probability that a randomly selected worker does not ride a bicycle to work?
Verified step by step guidance1
Identify the probability that a worker rides a bicycle to work, which is given as \(P(\text{bicycle}) = 0.792\).
Recall that the probability that a worker does not ride a bicycle to work is the complement of the probability that they do ride a bicycle.
Use the complement rule formula: \(P(\text{not bicycle}) = 1 - P(\text{bicycle})\).
Substitute the given value into the formula: \(P(\text{not bicycle}) = 1 - 0.792\).
Calculate the result to find the probability that a randomly selected worker does not ride a bicycle to work.
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Key Concepts
Here are the essential concepts you must grasp in order to answer the question correctly.
Probability of an Event
Probability measures the likelihood of an event occurring, expressed as a number between 0 and 1. A probability of 0 means the event cannot happen, while 1 means it is certain. For example, the probability that a worker rides a bicycle to work is 0.792, indicating a high likelihood.
Recommended video:
Probability of Multiple Independent Events
Complement Rule
The complement rule states that the probability of an event not occurring is 1 minus the probability that it does occur. If P(A) is the probability of event A, then P(not A) = 1 - P(A). This rule helps find the probability of the opposite outcome, such as not riding a bicycle to work.
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Conditional Probability Rule
Mutually Exclusive Events
Mutually exclusive events cannot happen at the same time. For example, a worker cannot both ride a bicycle and take public transportation to work simultaneously. Understanding this helps in correctly calculating probabilities without overlap.
Recommended video:
Probability of Mutually Exclusive Events
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