Inference for Paired Data
Über den Vortrag
Der Vortrag „Inference for Paired Data“ von David Spade, PhD ist Bestandteil des Kurses „Statistics Part 2“. Der Vortrag ist dabei in folgende Kapitel unterteilt:
- Inference for paired Data
- The Paired t-Test
- Pitfalls to Avoid
Quiz zum Vortrag
What is meant by the term “paired data"?
- Paired data refers to situations in which two measurements are taken on the same individual and the differences in the measurements are observed.
- Paired data refers to data in which the measurements are taken on different individuals in each group.
- With paired data, the data in each group are independent.
- There is no difference between paired data and the type of data used for the two-sample t-test.
- Paired data must be collected at the same time.
What is not a condition necessary for a paired t-procedure?
- The differences can have any distribution, and the paired t-procedures will still work well regardless of the sample size.
- The data must be paired.
- The differences must be independent.
- Data must be collected from a random sample.
- Treatment groups must be randomly assigned.
Once the differences are computed, what is the difference between the one-sample t-test and the paired t-test?
- There is no difference between the paired t-test and the one-sample t-test after the differences are calculated as the differences can be viewed as a random sample from a single population.
- The standard error is calculated differently for the differences than it is for the individual observations in the one-sample t-test.
- The degrees of freedom for the test statistic are computed differently for the two tests.
- The test statistic is calculated differently for the two tests.
- There are no differences between the paired t-test and the one-sample t-test.
What is an example of a paired-t-test?
- Weighing patients before and after a weight-loss diet
- Weighing patients after a weight-loss diet
- Weighing patients after two weight-loss interventions
- Weighing two groups of patients before their primary care appointment
- Weighing patients on two different scales and comparing the difference
What is not something of which to be cautious for the paired t-procedures?
- It is important to examine side-by-side box plots or histograms for differences when the data are paired.
- It is important to be careful not to use a two-sample t-test with paired data.
- It is important not to use the paired t-procedures when the data are not paired.
- It is important to be cautious of outlying differences when working with paired data.
- It is important to make sure data is randomly sampled.
Dozent des Vortrages Inference for Paired Data
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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