Acceptance Sampling Suppose that you have just received a shipment of 20 modems. Although you don’t know this, 3 of the modems are defective. To determine whether you will accept the shipment, you randomly select 4 modems and test them. If all 4 modems work, you accept the shipment. Otherwise, the shipment is rejected. What is the probability of accepting the shipment?
Table of contents
- 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 8m
- 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 Errors16m
- 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
- 12. Regression3h 33m
- 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
5. Binomial Distribution & Discrete Random Variables
Hypergeometric Distribution
Problem 6.2.11
Textbook Question
In Problems 7–16, determine which of the following probability experiments represents a binomial experiment. If the probability experiment is not a binomial experiment, state why.
Three cards are selected from a standard 52-card deck without replacement. The number of aces selected is recorded.
Verified step by step guidance1
Recall the definition of a binomial experiment: it consists of a fixed number of independent trials, each with only two possible outcomes (success or failure), and the probability of success remains constant across trials.
Identify the trials in the given experiment: selecting three cards from a deck without replacement means there are three trials, each corresponding to selecting one card.
Check if the trials are independent: since cards are drawn without replacement, the outcome of one draw affects the probabilities of the next draws, so the trials are not independent.
Check if the probability of success (drawing an ace) remains constant: because cards are not replaced, the probability of drawing an ace changes after each card is drawn.
Conclude that this experiment is not a binomial experiment because the trials are not independent and the probability of success changes with each draw.
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Key Concepts
Here are the essential concepts you must grasp in order to answer the question correctly.
Binomial Experiment Criteria
A binomial experiment consists of a fixed number of independent trials, each with two possible outcomes (success or failure), and a constant probability of success. Understanding these criteria helps determine if a given experiment fits the binomial model.
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The Binomial Experiment
Independence of Trials
Independence means the outcome of one trial does not affect the outcomes of others. In sampling without replacement, trials are dependent because the composition of the population changes after each draw, affecting probabilities.
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Independence Test
Sampling Without Replacement
Sampling without replacement means items are not returned to the population after selection, altering the probabilities for subsequent draws. This violates the constant probability requirement of binomial experiments.
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Sampling Distribution of Sample Proportion
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