Methods of Research

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Methods of Research
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Psychology as a Science

• Uses the Scientific Method appropriately
  identifies and frames a researchable event
• Can help identify fallacies in thinking
• Become critical of psychological findings dont
  accept everything

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Good Psychological Science

• Skepticism Dont accept ideas on faith or
  authority.
• Reliance on Empirical Evidence Needs to be
  serious evidence based on careful observation or
  experimentation.
• Precision Research based on a scientific
  hypothesis and testing a specific theory.

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Good Psychological Science

• Openess Willing to tell others where they got
  their ideas, how they were tested, and what the
  results were so that they can be replicated.
• Willingness to make a risky prediction Must
  state ideas in a way that they must be testable.

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Good Research must have

• Hypothesis A statement about the relationship
  between two variables. Must be testable,
  verifiable, and refutable.
• Operational definition the exact
  procedures/description of the concept being
  tested

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Testable, Verifiable, Refutable, Risky?

• If you pick any day of the year, a famous person
  was born on it.

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Experiments

• Experiments are the only research method capable
  of showing cause and effect because experimenter
  can manipulate factors and control others.

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Experiments

• Independent Variable Variable manipulated by
  the experimenter, everything else is held
  constant.
• Dependent Variable Measured variable
  influenced by the independent variable.

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Experiments

• Confounding Variable Any variable besides the
  independent variable that could influence the
  outcome of the experiment. (Unwanted)
• Controls methods placed in the experiment to
  keep confounding variables to a minimum

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Experiments

• Subject the person on whom the experiment is
  being done.
• Experimenter the person conducting the
  research (does not have to be the researcher)
• Confederate a person who acts as a subject but
  is actually helping the experimenter

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Experiments

• Sampling a representative group of a larger
  population
• Random Assignment Selection and assignment of
  participants of subjects to groups through
  random or chance procedure.
• Placebo Drug with no medicinal value, usually
  a sugar pill, need not always be a drug,
  sometimes a situation. (placebo effect)

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Experiments

• Control Group Group that does not take part in
  the critical part of the experiment. Serves as
  a comparison of results from the experimental
  group.
• Experimental Group Group that receives the
  treatment.

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Experiments

• Single-Blind Study The subjects do not know to
  which group they belong.
• Double-Blind Study Neither the experimenter
  nor the subjects know to which group the
  subjects belong.

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Good Research must have

• Theory Organized explanation used to explain
  or predict human behavior after it has been
  tested empirically.
• Useful if it effectively organizes a range of
  observations, and anyone can check.

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Good Research Must Have

• Validity test that measures what it is set
  out to measure.
• Reliability test that yields consistent
  results from one time and place to another.

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Types of Research

• Naturalistic observation watching behavior in a
  natural setting
• Survey methodusing questionnaires to poll
  large groups of people (interviews)

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Types of Research

• Experimental methodinvestigating behavior
  through controlled experimentation, usually in a
  lab setting (psychological testing)

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Types of Experiments

• Clinical methodstudying behavior in clinical
  settings (case study)
• Correlational method measuring behavior to
  discover relationships (testing, longitudinal,
  or cross-sectional)

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Correlational Studies

• Statistical technique used to measure the
  strength and nature of a relationship between
  two variables.
• CORRELATION DOES NOT PROVE CAUSATION

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Correlation does not mean causation!

• Global warming has increased in the last 100
  years. Pirating and the pirate lifestyle has
  significantly decreased in the last 100 years.
• The lack of pirates has obviously caused global
  warming.
• Are you kidding me?!

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Correlation does not mean causation!

• As ice cream sales increase, the rate of
  drownings increase.
• OBVIOUSLY, ice cream causes drowning!
• Are you still buying this?!

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Correlation does not mean causation!

• Compared to citizens of other countries,
  Americans and Brits have significantly more
  heart attacks.
• Americans and Brits drink red wine. Therefore,
  red wine must cause heart attacks.
• Nope, Italians drink more red wine and suffer
  fewer heart attacks.

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Statistics

• Descriptive Statistics Statistics that organize
  and summarize data, frequently use graphs or
  charts.

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Statistics

• Arithmetic Mean the average of a set of scores.
  Add all quantities together and divide by the
  total number of scores. Summarizes a mass of
  data, does not examine variation.
• Outliersextreme scores that change or skew
  the mean

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Statistics central tendency and variability

• Mode The most frequently occurring score in a
  set of data.
• Median The middle number in a collection of
  data.
• Range Differences between the lowest and the
  highest scores in a distribution of scores.

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Measures of Variability

• Normal curvea bell-shaped distribution, with a
  large number of data in the middle tapering to
  lower scores on either side

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Skewnessasymmetry in a distribution of numbers

• Positive skewthe majority of the scores on the
  left side of the mean with the tail trailing to
  the right (the mean is greater than the median
  and mode)
• Negative skewthe majority of the scores appear
  on the right side of the mean with the tail
  trailing to the left (the mean is less than the
  median and mode)

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Inferential Statistics

• Statistics that tell the researcher the
  significance of the data.
• Show how likely the data were to have occurred
  by chance.
• Assist in making a statement about relationship
  in variables.

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Statistical Measure

• Variance How clustered or spread out
  individual scores are around the mean.
• Standard Deviation The average distance of
  scores around the mean.

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Significance Testing

• Significance Testingused to draw conclusions
  about whole populations based upon samples.
• Alternative (Research) hypothesis relationship
  is the result of a real effect.
• Null hypothesisis tested to account for a
  chance states that no relationship exists
  between variables.

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Significance Testing

• Type I Errorseeing a statistical difference
  when none is present. (Rejecting the null
  hypothesis when the null is true.)
• Type II Errorseeing no difference when one does
  exist. (Accepting the null when it is false.)
• PROBLEMS?

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Statistical Measure

• P-Value a number from zero to one that
  represents the probability that an event
  occurred by chance.
• E.g. P0.05, means 95 times out of 100 (or 95)
  the results will be similar from one test to the
  next.
• Statistically Significant A low chance of an
  event occurring by chance Plt0.05.

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Measures of Variability

• Z-scorea number that tells how many standard
  deviations above or below the mean a score is.
• Formula for computation
• Score mean/standard deviation

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Correlational Studies

• Illusory Correlation The perception of a
  relationship where none exists.
• Coefficient of Correlation Perfect positive
  correlation 1.00, perfect negative correlation
  -1.00, no correlation 0.

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Correlational Studies

• Positive Correlation high values for one
  variable are associated with high values for
  the other variable. Highest 1.0.
• Negative Correlation High values for one
  variable are associated with low values for the
  other variable. Highest -1.0.

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Types of Data

• Nominal Numbers that are used to name or
  categorize.
• drivers license
• numbers on sports uniforms
• gender (1 female 2 male)

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Types of Data

• Ordinal Numbers represent serial position
  greater or less than.
• Class rank
• Age
• Baseball standings

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Types of Data

• Interval Scale Consistent units of measurement,
  equal spacing between, allows for mathematical
  operations.
• No true zero point (arbitrary)
• Thermometer, temperature
• Cant say 20 degrees is twice as hot as 10
  degrees ratios dont work!

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Types of Data

• Ratio Scale Same consistent units of
  measurement as in the interval scale but with the
  added property of a true zero point. Compare
  scores in terms of ratios.
• Four pounds is twice as heavy as two.
• Time
• Length

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Graphs

• Frequency Distribution A table that divides an
  entire range of scores into a series of classes
  and then records the number of scores that fall
  into each class (page A-4)

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Graphs

• Pie Graph Circle in which all data is
  represented in the form of percentages

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Graphs

• Frequency Histogram Bar graph with scores on
  the horizontal axis and frequencies on the
  vertical axis. (page A-4)
• Frequency Polygon Line graph that has the same
  horizontal and vertical axis as the histogram.
  Each score marked with a point and then
  connected, can plot multiple data sets. (page
  A-4)

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Some data interpretation

• Find the mean, median, mode, and range for the
  salaries of the Indians, the Yankees, all
  baseball teams, and the Browns.
• What conclusions and/or correlations can you
  draw?