Experiments and Observational Studies von David Spade, PhD

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Über den Vortrag

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

  • Experiments and observational studies
  • Why do Observational Studies?
  • Designing an Experiment
  • Principles of Experimental Design
  • Diagramming an Experiment
  • Experiments and Surveys
  • Placebos and their Uses
  • Randomized Block Designs

Quiz zum Vortrag

  1. We have conducted a retrospective study.
  2. We have conducted a survey.
  3. We have conducted a prospective study.
  4. The information provided in this question is not sufficient to determine what kind of study has been conducted.
  5. We have conducted a cohort study.
  1. Observational studies allow us to examine the relationship between two variables.
  2. Observational studies allow us to establish cause and effect relationships between two variables.
  3. Observational studies allow us to determine whether we have found the explanatory variables that have the largest effect on the response.
  4. Observational studies allow us to evaluate the placebo effect.
  5. Observational studies are useful to determine the maximum safe dose of a drug.
  1. In an experiment, the researcher assigns treatments, while in an observational study, treatments are not assigned.
  2. In an observational study, the researcher assigns treatments, while in an experiment, treatments are not assigned.
  3. Experiments can be used to study relationships between two variables, while observational studies cannot be used in this way.
  4. An observational study allows us to infer cause and effect relationships, while experiments do not.
  5. Only observational studies regularly look at toxicity outcomes.
  1. We say that these variables are confounded.
  2. We say that these are lurking variables.
  3. We say that these variables are factors.
  4. We say that these variables are treatments.
  5. We say these variables are atypical.
  1. Non-human individuals on whom experiments are performed
  2. Numbers involved in experiments
  3. The one who conducts the experiments
  4. The one who pays for the experiments
  5. The one who create hurdles in the experiment
  1. Individuals on whom experiments are performed
  2. Numbers involved in experiments
  3. The one who conducts the experiments
  4. The one who pays for the experiments
  5. The one who creates hurdles in the experiment
  1. A control treatment is a baseline measurement used to help decide whether a treatment has an effect on the response.
  2. A control treatment is a complex tool used to help decide whether a treatment has an effect on the independent variable.
  3. A control treatment is a false replication of the original treatment.
  4. A control treatment is a method of removing outliers.
  5. A control treatment is one that has no effect on the response.
  1. Single-blind
  2. One-blind
  3. Triple -blind
  4. No-blind
  5. Single-bind
  1. Double-blind
  2. Both-blind
  3. One-blind
  4. Triple-blind
  5. Double-bind

Dozent des Vortrages Experiments and Observational Studies

 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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