Social Science Reasoning Using Statistics

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Social Science Reasoning Using Statistics

• Psychology 138
• Spring 2005

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Different basic methods

• Experimental versus Observational methods
• Experiments involve manipulation of variables
• Observational methods involve examining things as
  they already are

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Example

• Issue Whats the best way to study for a test?
• Cram the night before
• Spread your studying out over several nights

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Example

• Issue Whats the best way to study for a test?

• Randomly select individuals
• Watch their study habits
• See how they do on a test

• Randomly select individuals
• Randomly assign to groups
• Crammed study group
• Distributed study group
• See how they do on a test

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Different basic methods

• Precise control possible
• Precise measurement possible
• Theory testing possible
• Can make causal claims

• May see patterns of complex behaviors
• Good first step
• May learn about something unexpected

• Artificial situations may restrict
  generalization to real world
• Complex behaviors may be difficult to measure

• Shouldnt make causal claims
• Directionality of the relationship isnt known
• Threats to internal validity due to lack of
  control
• Sometimes the results are not reproducible

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Designing an Experiment

• Generally the process involves a number of steps
  
• identification of your research questions
• identifying your variables
• specify your hypotheses (how are the variables
  related to one another)
• selecting a research design
• collecting your data, analyzing your data
• drawing conclusions from your data about your
  hypotheses.

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Variables

• Independent variables

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Variables

• Independent variables these are the variables
  that are manipulated by the experimenter

• A number of ways to manipulate your IV
• Event/Stimulus manipulations manipulate
  characteristics of the stimuli, context, etc.
• Instructional manipulations different groups
  are given different instructions
• Subject manipulations there are (pre-existing
  mostly) differences between the subjects in the
  different conditions (typically results in
  quasi-experimental designs)

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Variables

• Independent variables

1 IV (factor) study type 2 levels
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Variables

• Independent variables
• Dependent variables

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Variables

• Dependent variables these are the variables
  that are measured by the experimenter, they are
  dependent on the independent variables

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Variables

• Independent variables
• Dependent variables
• Extraneous variables

• Control variables
• Random variables
• Confound variables

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Variables

• Control variables
• Holding things constant - Controls for excessive
  random variability

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Variables

• Control variables

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Variables

• Random variables
• may freely vary, to spread variability equally
  across all experimental conditions

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Variables

• Random variables

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Variables

• Confound variables
• Other variables, that havent been accounted for
  (manipulated, measured, randomized, controlled)
  that can impact changes in the dependent
  variable(s)

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Variables
Studied vocabulary and practice problems
Studied only vocabulary

• Confound variables

Or is it due to what was studied?
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Colors and words

• Divide into two groups
• left side of room
• right side of room
• Instructions Read aloud the COLOR that the
  words are presented in. When done raise your
  hand.
• Left side first. Right side people please close
  your eyes.
• Okay ready?

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List 1
Blue Green Red Purple Yellow Green Purple Blue Red
Yellow Blue Red Green
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• Okay, now it is the right sides turn.
• Remember the instructions Read aloud the COLOR
  that the words are presented in. When done raise
  your hand.
• Okay ready?

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List 2
Blue Green Red Purple Yellow Green Purple Blue Red
Yellow Blue Red Green
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Our results

• So why the difference between the results for the
  people on the right side of the room versus the
  left side of the room?
• Is this support for a theory that proposes
• good color identifiers usually sit on the left
  side of a room
• Why or why not? Lets look at the two lists.

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List 2Right side
List 1Left side
Blue Green Red Purple Yellow Green Purple Blue Red
Yellow Blue Red Green
Blue Green Red Purple Yellow Green Purple Blue Red
Yellow Blue Red Green
Matched
Mis-Matched
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Confound

• What resulted in the perfomance difference?
• Our manipulated independent variable
• The other variable match/mis-match?
• Because the two variables are perfectly
  correlated we cant tell
• This is the problem with confounds

Blue Green Red Purple Yellow Green Purple Blue Red
Yellow Blue Red Green
Blue Green Red Purple Yellow Green Purple Blue Red
Yellow Blue Red Green
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Basic Designs

• All experiments must have some sort of
  comparison.
• So the simplest design is to compare two groups.
  This would be an example of a 1 factor with 2
  levels experiment.
• The experiments that we discussed today use a
  1-factor with 2 levels
• e.g., distributed vs crammed study.
• The design that you chose will determine what
  statistical test you perform.
• 1 Factor, 2 groups use a t-test
• One of the purposes of todays lab is to
  introduce you to a statistical test decision tree
  that we will use throughout the course

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Statistical test decision tree