Correlational and Survey Research by 7U2odi

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									Correlational and Survey
        Research
     PSYC301: Week 4
               Today’s Agenda

•   Hand in papers (no sharing, I promise!)
•   Correlations
•   Survey Research
•   Entering Data
           Correlational Data

• How one variable changes in response to
  another.
• Co Relates!
• Covarying, association
   Why Use Coorelational Data?

• When we don’t have much control over the
  data.
• When we can’t possibly assign groups.
  – Impossible to assign…
  – Unethical to assign…
    What Do Correlations Show?

• A relationship between two variables
  occurring in nature.
• How strong that relationship is.
• What the direction of that relationship is.
• But one important thing…
Okay, enough with the animation

  • Correlation ≠ Causation
  • Shows that there is a relationship
  • Does not show that one causes the other.
                 Correlations

• A third variable could be causing them both:
  – As ice cream sales go up, so does deaths relating
    drowning.
  – Is the Good Humor man a murderer?
  The Good Humor Man Cannot Hurt
               You
• Spurious relationship
  – A 3rd variable is somehow affecting the 1st and 2nd
    variables.
  – Heat is related to both high ice cream sales and
    more people to drown.
  – But is heat causing drowning? I don’t think so.
            Mediating Variable

• Something that comes between two things
  that relate.
• Higher heat = more drowning.
  – (We’ll leave the ice cream out of this).
• Fills the logical hole.
• Higher heat = more swimming = more
  drowning.
           Moderating Variable

• A third variable that directs the other two.
• Let’s assume there’s a negative correlation
  between year and school and drinking.
• Freshman drink more than seniors.
  – (Drink milk. Because the other stuff’s illegal).
          Moderating Variable

• But what if we could make this a stronger
  correlation?
• Students who live on campus drink more.
• Living on campus is a moderator.
• Younger students drink more, especially if
  they live on campus.
    Today’s Lecture is Brought to you by
                the letter r
•   How do we measure this stuff?
•   Many ways.
•   Pearson’s correlation.
•   Abbreviated as r.
                     Pearson’s r
• Shows how much two variables correlate.
• Measured from -1.0 to 1.0

                        - 0.43
- and + indicate direction.    The number represents
                               percentage two variables relate.



                    Nothing is 100%!
                      Some Examples
• Visual representation
                Correlation Between GPA and SAT   r = .62
     4
    3.8
    3.6
    3.4
    3.2
     3
    2.8
    2.6
    2.4
          700       900    1100   1300    1500
          Some Examples
          Correlation Between GPA and Average Drinks Per Week


 4                                                               r =- .62
3.8

3.6

3.4

3.2

 3

2.8

2.6

2.4
      0      2         4        6        8        10       12   14
                Some Examples

        Jack Bauer’s Damnits and Donovon McNabb’s
6                  Touchdowns in a Week
5
4
3
2
1
0
    0     50      100      150
            Survey Research

• Correlational
• Helps us answer a question with things that
  already exist
• Say we want to look at general satisfaction
  with George Mason University and overall
  course performance.
      What makes up a survey?

• Predetermined set of questions.
  – Operational definitions!
• Representative sample.
  – Is going to an old folks home going to help with
    our research?
  – Our sample tells the story about the population.
  – So what would be a good sample?
          How do we sample?

• Simple Random Sample
   • Everything has an equal chance of being
     samples.
• Stratified Random Sample
   • Split up into groups.
        Convenience Sampling

• Non-probabilistic
• Participants are involved based on their
  willingness to respond.
• Anyone do Sona-Systems for fun?
                Avoiding Bias

• Polarized responses
  – People who have a strong negative or positive
    feeling are more willing to share than people who
    are so-so.
              Types of Biases

• Selection Bias: using a method of selection
  that won’t fairly select a group that represents
  your whole population.
  – 85% of people disagree with teaching evolution in
    the classroom.
  – But this is your sample:
          Many types of methods

•   Phone
•   Internet
•   Mailing
•   Public Places
      Using Surveys in Research

• How does depression work throughout a
  lifespan?
• Cross Sectional
• Longitudinal
              Cross Sectional

• Many people are given surveys at one time.
• Survey many different ages to assess depression.
               Longitudinal
– One group of people are given surveys over time
– Survey one group of people over a 20-year period.
                    Self-Report

• Potential Problems?
• Ways to assess self-report:
  – Likert-type scale
     • On a scale of 1 to 10…
  – Yes or No
     • Do you like coffee?
  – Multiple Choice?
     • Starbucks, Jazzman’s, etc.
 How do we know it’s a good survey?

• Reliability
• Validity
                   Reliability

• Reliability
   – How consistent your survey is
   – If you gave the survey to the same group of
     people twice, would the answers be the same?
                      Validity

• Validity
  – Does your survey say what you want it to?
  – Operational definition!
• Many Types
  – Construct Validity
     • Does your measure actually measure your construct?
  – Convergent Validity
     • Does it agree with other measures?
   Time to answer some surveys!

• Life Satisfaction Survey
  – Answer the questions honestly
  – Once you finish, add up your total score from
    the 5 questions
• Perceived Stress Survey
  – Answer the 10 questions honestly
  – Once you finish, add up your total score
               Entering Data

• Enter your data on the link you can find at the
  course website

								
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