A quality control inspector at a textile factory is examining long rolls of fabric for defects. The inspector knows from past experience that, on average, there are 0.5 defects per meter of fabric. What is the probability that the inspector finds 0 defects in any given meter of fabric?
Table of contents
- 1. Introduction to Statistics53m
- 2. Describing Data with Tables and Graphs2h 1m
- 3. Describing Data Numerically2h 8m
- 4. Probability2h 26m
- 5. Binomial Distribution & Discrete Random Variables3h 28m
- 6. Normal Distribution & Continuous Random Variables2h 21m
- 7. Sampling Distributions & Confidence Intervals: Mean3h 37m
- Sampling Distribution of the Sample Mean and Central Limit Theorem19m
- Distribution of Sample Mean - Excel23m
- Introduction to Confidence Intervals22m
- Confidence Intervals for Population Mean1h 26m
- Determining the Minimum Sample Size Required12m
- Finding Probabilities and T Critical Values - Excel28m
- Confidence Intervals for Population Means - Excel25m
- 8. Sampling Distributions & Confidence Intervals: Proportion1h 33m
- 9. Hypothesis Testing for One Sample3h 32m
- 10. Hypothesis Testing for Two Samples4h 49m
- Two Proportions1h 12m
- Two Proportions Hypothesis Test - Excel28m
- Two Means - Unknown, Unequal Variance1h 2m
- 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
- 11. Correlation1h 24m
- 12. Regression1h 59m
- 13. Chi-Square Tests & Goodness of Fit2h 31m
- 14. ANOVA2h 1m
5. Binomial Distribution & Discrete Random Variables
Poisson Distribution
Struggling with Statistics for Business?
Join thousands of students who trust us to help them ace their exams!Watch the first videoMultiple Choice
A student working on a transportation engineering project analyzes traffic flow at an intersection for 20 min. From past data, the average # of cars per minute is 17.6.
(A) What is the expected number of cars in the entire 20 min period?
A
18
B
352
C
360
D
340
Verified step by step guidance1
Step 1: Understand the problem. The problem involves calculating the expected number of cars passing through an intersection over a 20-minute period, given the average number of cars per minute is 17.6.
Step 2: Recall the formula for expected value in this context. The expected number of cars over a given time period can be calculated as: \( \text{Expected Number of Cars} = \text{Average Cars per Minute} \times \text{Total Time in Minutes} \).
Step 3: Substitute the given values into the formula. Here, the average number of cars per minute is 17.6, and the total time is 20 minutes. The formula becomes: \( \text{Expected Number of Cars} = 17.6 \times 20 \).
Step 4: Perform the multiplication to find the expected number of cars. This step involves multiplying 17.6 by 20 to get the result.
Step 5: Interpret the result. The calculated value represents the expected number of cars passing through the intersection during the 20-minute observation period.
Watch next
Master Introduction to the Poisson Distribution with a bite sized video explanation from Patrick
Start learningRelated Videos
Related Practice
Multiple Choice
19
views
Poisson Distribution practice set

