Randomness and Survey Sampling von David Spade, PhD

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Über den Vortrag

Der Vortrag „Randomness and Survey Sampling“ von David Spade, PhD ist Bestandteil des Kurses „Statistics Part 1“. Der Vortrag ist dabei in folgende Kapitel unterteilt:

  • Randomness and Survey Sampling
  • Random Sampling
  • Selecting a Representative Sample
  • Stratified Sampling
  • Systematic Sampling
  • Types of Bias

Quiz zum Vortrag

  1. Any random sample will be representative of the population about which it is used to make inferences
  2. By randomly sampling, we ensure that separate outcomes do not affect each other
  3. No one can guess the outcomes before they happen
  4. Several software packages exist that will do the sampling for you
  1. A census is not representative of the population
  2. A census can be extremely expensive to carry out
  3. A census may not give information about the population that is as accurate as what is obtained from a random sample
  4. A census can be very complex
  1. This list is known as the sampling frame
  2. This list is known as the population
  3. This list is known as the sample
  4. This list is known as a census
  1. We have used a convenience sampling scheme
  2. We have used a voluntary response sampling scheme
  3. We have used a cluster sampling scheme
  4. We have used a stratified sampling scheme
  1. This survey will likely suffer from response bias
  2. This survey should not suffer from any bias because the respondents were selected randomly
  3. This survey will likely suffer from nonresponse bias
  4. This survey will likely suffer from undercoverage
  1. To learn about the population
  2. To learn about the sample
  3. To learn about hypothesis
  4. To learn about unknown things
  5. To learn about regressions
  1. 500
  2. 100
  3. 200
  4. 300
  5. 400
  1. Benefits = 200 ; Costs = 100
  2. Benefits = 100 ; Costs = 100
  3. Benefits = 200 ; Costs = 200
  4. Benefits = 150 ; Costs = 130
  5. Benefits = 10 ; Costs = 0
  1. Cluster sampling and Stratified sampling techniques are the same
  2. Random sampling implies that the sample is representative of the population
  3. Higher sample size is more accurate than small sample size
  4. Sample is always smaller than population
  5. The sampling strategy with the highest net benefit is chosen

Dozent des Vortrages Randomness and Survey Sampling

 David Spade, PhD

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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