Relational Research

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Relational Research
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Contingency Tables

• Contingency tables combine categorical data from
  two variables, allowing us to see relationships

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Contingency Tables

• Advertiser Education
• High School Some College College Grad
• Male 28 69 32
• Female 17 64 46

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Correlational Research

• Quantifies the strength of a relationship between
  two variables
• How does the value of one variable change when
  the value of another variable changes?

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Correlational Research

• Steps
• Develop hypothesis
• How will you measure the variables of interest?
• Obtain data, perform analyses
• Interpret results

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Correlational Research

• Many types of correlations
• Pearson product-moment correlation
• Spearman rank-order correlation
• Advanced techniques
• Multiple correlation
• Path analysis
• Partial correlation
• Point-biserial correlation

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Pearson product-moment correlation

• Represented by a mathematical score
• Ranges from 1.0 to -1.0
• Absolute value signifies strength of relationship
• Sign signifies nature of the relationship

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Pearson product-moment correlation

• Strength of a relationship is represented by a
  mathematical score
• 1.0 Perfect positive correlation

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Pearson product-moment correlation

• Strength of a relationship is represented by a
  mathematical score
• 1.0 Perfect positive correlation
• -1.0 Perfect negative correlation

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Pearson product-moment correlation

• Strength of a relationship is represented by a
  mathematical score
• 1.0 Perfect positive correlation
• -1.0 Perfect negative correlation
• 0.0 No correlation No relationship!

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Pearson product-moment correlation

• Which is stronger?

-.35 -.41
.75 -.81
1.00 -1.00
.58 .47
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Interpreting Correlations

• What does strength of a correlation mean?
• Rule of thumb

• .8 to 1.0
• .6 to .8
• .4 to .6
• .2 to .4
• .0 to .2

• Very strong relationship
• Strong relationship
• Moderate relationship
• Weak relationship
• Weak or No relationship

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Interpreting Correlations

• Large-scale study of contraceptive use in Taiwan
  found that people with more electrical appliances
  were more likely to use birth control.

Does this mean that toasters cause people to use
birth control?
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Interpreting Correlations

• When we find a relationship between two variables
  (A and B), there are three possible explanations
• Changes in A cause changes in B
• Changes in B cause changes in A
• Changes in a third variable C cause changes in
  both A and B

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Interpreting Correlations

• The more psychology courses students take during
  their college years, the higher scores they get
  on a measure of interpersonal sensitivity.

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Interpreting Correlations

• In a study of suburban communities, it was
  noticed that communities that sex-related crimes
  was highest in the communities that had the
  largest number of X-rated adult book stores.

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Interpreting Correlations

• A college professor notices that the farther
  students sit toward the back of the room, the
  worse their grades in the course seem to be.

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Interpreting Correlations

• A survey of adolescents being treated for eating
  disorders noted that those who watched the most
  TV during the week tended to get the lowest
  ratings on a measure of general health.

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Interpreting Correlations

• Correlations allow us to describe relationships
• Correlations allow us to predict

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Interpreting Correlations
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Correlation Coefficient

• Reflects the amount of variability that is shared
  between variables
• Beware the problem of restricted range
• Correlations are lower because available
  variation is restricted

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Interpreting Correlations

• Coefficient of Determination
• Percentage of variance in one variable that is
  accounted for by variance in the other variable
• Computed by squaring the correlation coefficient