Confidence Intervals for Proportions
Über den Vortrag
Der Vortrag „Confidence Intervals for Proportions“ von David Spade, PhD ist Bestandteil des Kurses „Learn Statistics - Become Data Smart“. Der Vortrag ist dabei in folgende Kapitel unterteilt:
- Confidence Intervals for Proportions
- Constructing the Interval
- Margin of Error
- Assumptions and Conditions
- Pitfalls to Avoid
Quiz zum Vortrag
What is not a benefit of using confidence intervals to summarize a population instead of a single value?
- We know that we have constructed an interval that captures the true population proportion.
- We no longer need to rely on a single value to estimate the population proportion.
- We are guaranteed a certain probability that the interval captures the true value of the population parameter.
- We have more confidence in a range than in a single value as an estimate of the population proportion.
- We are able to adjust confidence and precision to match our needs.
Which interpretation of a 95% confidence interval (a,b) for a population proportion centered at the sample proportion (p) is correct?
- We are 95% confident that the true population proportion is between a and b.
- We know that the true population proportion is between a and b.
- We know that the true population proportion is p.
- We are 95% confident that the true standard deviation is between a and b.
- We are 95% confident that the true population proportion is outside of a and b.
What is true regarding the margin of error?
- A smaller margin of error is associated with a smaller confidence interval.
- A smaller margin of error is associated with a larger confidence interval.
- A larger margin of error is associated with a smaller confidence interval.
- We can change the confidence level using the same sample size without affecting the margin of error.
- The larger the margin of error, the more confidence we have in a result.
What is not a condition that we need in order to use the normal model to construct a confidence interval for a population proportion?
- We need our sample size to be at least 10% of the population.
- We need to observe at least 10 successes.
- We need to observe at least 10 failures.
- We need our sample to be random.
- All trials must be independent of each other.
What is true of the one-proportion z-interval?
- The confidence level can be increased while also decreasing the margin of error by increasing the sample size.
- The interval is based on the sample proportion, so any statements you can make based on the interval should be about the sample proportion.
- 95% confidence means that you are 95% certain that the population proportion lies in your interval.
- Values near the center of the interval are more plausible than values near the edges.
- The confidence level is a fixed, immutable property.
What is the 95% confidence interval for a population proportion if the sample proportion is 0.2 and standard deviation is 0.1?
- 0.4; 0
- 0.5; 0
- 0.3; -1
- 0.2; -1
- 0.5; -1
What is the margin of error if the confidence interval is 0.5; 0?
- 0.25
- 0.5
- 0
- 0.3
- 0.8
Dozent des Vortrages Confidence Intervals for Proportions
David Spade, PhD
Dr. David Spade is an Assistant Professor of Mathematical Sciences and Statistics at the University of Wisconsin-Milwaukee and holds a courtesy appointment as an Assistant Professor of Statistics at the University of Missouri-Kansas City, USA.
He obtained his MS in Statistics in 2010 and then completed his PhD in Statistics from Ohio State University in 2013.
An experienced mathemathics instructor, Dr. Spade has been teaching diverse statistics courses from the introductory to the graduate level since 2007.
Within Lecturio, he teaches courses on Statistics.
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