Module 1

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Introduction and Experimental Design Concepts

16 Terms

1
What are the types of Variables in data?
Categorical and Quantitive
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2
What is the definition of a Categorical variable
Divides the cases into groups/ categories
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3
What is the definition of a Quantitative variable
measure a numerical quantity for each cases
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4
What is the subcategories for Categorical
Nominal and Ordinal
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5
What are the subcategories of quantitative data?
Discrete and Continuous
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6
Define Census
information collected from whole (finite) population
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7
Define Sample Survey
Information collected from a subset of the \n population

\
\*\*\*Often use the approach to sampling (and data collection) to distinguish between options...
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8
Why do we want to use Sample Statistics?
to make inferences back about Population Parameters allowing for RANDOMNESS
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9
How do you describe the population
by measuring relationships between variables at a point-in-time (correlations)
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10
What matters most in samples and why?
RANDOM SELECTION! without it, we get biased
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11
What are the variables when it’s a design for an experiment
Treatment variable and outcome variable
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12
What are the \*\*other\*\* variables when it’s a design for an experiment and define it
__**EXPLANATORY VARIABLES**__

attributes we can measure that explain variation in the Outcome

e.g: The Treatment variable is just a ‘special case’ of an \n explanatory variable

\
\
__**CONFOUNDING VARIABLES**__

attributes we cannot measure that explain variation in the Outcome

e.g: With COVID-19 this might be attitudes to social distancing, approach to hygiene and isolation, or your job situation

\
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13
What are cons in observational studies (rather than experiments)
  • Can have SEVERE BIAS due to background effects

  • Correlations are not Causation

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14
What are observational studies useful for?
  • guiding the development of hypotheses for later experiments

    • We look for evidence of a response in a group getting the treatment BEFORE implementing a large expensive double-blind randomised controlled experiment

  • Observational studies are useful for reinforcing the results of double-blind randomised controlled experiments

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15
Define Single-Blind Trials
the participant does not know if they are \n Treatment or Control
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16
Define Double-Blind Trials
neither the administrator of the experiment or the participant knows if they are Treatment or Control
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