Suppose there are n independent trials of an experiment with k>3 mutually exclusive outcomes, where pi represents the probability of observing the ith outcome. The ____________ for each possible outcome are given by Ei = __.
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- 1. Intro to Stats and Collecting Data1h 14m
- 2. Describing Data with Tables and Graphs1h 55m
- 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 - Excel23m
- Introduction to Confidence Intervals15m
- Confidence Intervals for Population Mean1h 18m
- Determining the Minimum Sample Size Required12m
- Finding Probabilities and T Critical Values - Excel28m
- Confidence Intervals for Population Means - Excel25m
- 8. Sampling Distributions & Confidence Intervals: Proportion2h 10m
- 9. Hypothesis Testing for One Sample5h 9m
- Steps in Hypothesis Testing1h 6m
- Performing Hypothesis Tests: Means1h 4m
- Hypothesis Testing: Means - Excel42m
- Performing Hypothesis Tests: Proportions37m
- Hypothesis Testing: Proportions - Excel27m
- Performing Hypothesis Tests: Variance12m
- Critical Values and Rejection Regions28m
- Link Between Confidence Intervals and Hypothesis Testing12m
- Type I & Type II Errors17m
- 10. Hypothesis Testing for Two Samples5h 37m
- Two Proportions1h 13m
- Two Proportions Hypothesis Test - Excel28m
- Two Means - Unknown, Unequal Variance1h 3m
- Two Means - Unknown Variances Hypothesis Test - Excel12m
- Two Means - Unknown, Equal Variance15m
- Two Means - Unknown, Equal Variances Hypothesis Test - Excel9m
- Two Means - Known Variance12m
- Two Means - Sigma Known Hypothesis Test - Excel21m
- Two Means - Matched Pairs (Dependent Samples)42m
- Matched Pairs Hypothesis Test - Excel12m
- Two Variances and F Distribution29m
- Two Variances - Graphing Calculator16m
- 11. Correlation1h 24m
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- Linear Regression & Least Squares Method26m
- Residuals12m
- Coefficient of Determination12m
- Regression Line Equation and Coefficient of Determination - Excel8m
- Finding Residuals and Creating Residual Plots - Excel11m
- Inferences for Slope31m
- Enabling Data Analysis Toolpak1m
- Regression Readout of the Data Analysis Toolpak - Excel21m
- Prediction Intervals13m
- Prediction Intervals - Excel19m
- Multiple Regression - Excel29m
- Quadratic Regression15m
- Quadratic Regression - Excel10m
- 13. Chi-Square Tests & Goodness of Fit2h 21m
- 14. ANOVA2h 28m
4. Probability
Multiplication Rule: Independent Events
Problem 4.2.32
Textbook Question
Same Birthdays If 25 people are randomly selected, find the probability that no 2 of them have the same birthday. Ignore leap years.
Verified step by step guidance1
Step 1: Understand the problem. We are tasked with finding the probability that no two people in a group of 25 have the same birthday. This is a classic 'birthday problem' in probability, and we assume there are 365 days in a year (ignoring leap years).
Step 2: Recognize that this is a problem of permutations. If no two people share the same birthday, the first person can have any of the 365 days as their birthday, the second person can have any of the remaining 364 days, the third person can have any of the remaining 363 days, and so on, until the 25th person.
Step 3: Write the total number of ways to assign birthdays to 25 people without restriction. Since each person can have any of the 365 days, the total number of possible birthday assignments is \( 365^{25} \).
Step 4: Write the number of favorable outcomes where no two people share the same birthday. This is given by the product \( 365 \times 364 \times 363 \times \ldots \times (365 - 24) \), which can also be written as \( \frac{365!}{(365 - 25)!} \).
Step 5: Calculate the probability by dividing the number of favorable outcomes by the total number of possible outcomes. The probability is \( P = \frac{365 \times 364 \times 363 \times \ldots \times (365 - 24)}{365^{25}} \). Simplify this expression to find the final probability.
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Key Concepts
Here are the essential concepts you must grasp in order to answer the question correctly.
Probability
Probability is a measure of the likelihood that a particular event will occur, expressed as a number between 0 and 1. In this context, it helps quantify the chance that no two people among a group share the same birthday. Understanding basic probability principles, such as the total number of outcomes and favorable outcomes, is essential for solving the problem.
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Introduction to Probability
Combinatorics
Combinatorics is a branch of mathematics dealing with counting, arrangement, and combination of objects. In the birthday problem, it is used to calculate the number of ways to assign unique birthdays to each person in a group. This involves understanding permutations and combinations, which are crucial for determining the total possible arrangements of birthdays.
Complementary Events
Complementary events are pairs of outcomes where one event occurs if and only if the other does not. In this scenario, instead of directly calculating the probability that no two people share a birthday, it can be easier to calculate the probability that at least two people do share a birthday and subtract that from 1. This approach simplifies the calculations and provides a clearer path to the solution.
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Complementary Events
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