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Psychological Research Methods

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Title: Psychological Research Methods


1
Psychological Research Methods Statistics
Excavating Human Behaviors
2
Psychology Research Methods
  • A Scientific Attitude is critical
  • Curiosity a passion to explore and understand.
  • Skepticism psychologists, like other
    scientists, approach the world of behavior with
    curious doubt. The are constantly asking two
    questions What does it mean? How do you know?
  • Humility an awareness and acceptance that we
    may have to reject our own ideas or theories (if
    they are proven wrong).
  • Critical Thinking a scientific approach
    prepares/demands us to think smarter ? to
    examine assumptions, evaluate evidence, and
    assess conclusions.

3
Hindsight Bias
  • The tendency to believe, after learning the
    outcome, that you knew it all along.
  • With 20/20 hindsight, everything seems obvious.

After the Chris Brown / Rihanna incident.my
husband said he knew Chris Brown was a violent
kid!!! Did he really?
4
Overconfidence
  • We tend to think we know more than we do.
  • We tend to be more confident than correct!

82 of U.S. drivers consider themselves
to be in the top 30 of their group in terms of
safety 81 of new business owners felt they
had an excellent chance of their businesses
succeeding. When asked about the success of their
peers, the answer was only 39. (Now that's
overconfidence!!!)
5
Exercise Unscramble these Anagrams
  • WREAT
  • ETRYN
  • GRABE

6
Anagram Solutions
  • WREAT --- WATER
  • ETRYN --- ENTRY
  • GRABE --- BARGE

7
The Barnum Effect
Theres a sucker born every minute. P.T. Barnum
  • It is the tendency for people to accept very
    general or vague characterizations of themselves
    and take them to be accurate.
  • Barnum Effect Experiment - Subjects take a bogus
    personality test that produces a set of vague and
    even self-contradictory statements such as "you
    can be outgoing at times but at times you can
    also be shy." When put in the correct context
    people will say that this analysis captures them
    to a "T." 

8
Applied versus Basic Research
  • Applied Research has clear, practical
    applications.
  • YOU CAN USE IT!!!
  • Basic Research explores questions that you may be
    curious about, but not intended to be immediately
    used.

Studying how kissing changes when you get older
is interestingbut thats about it.
Research on therapies for drug addicts has a
clear purpose.
9
Psychological Research Methods
  • Psychology is an experimental science.
  • Assumptions must be supported by evidence.
  • Psychologists use a variety of research methods
    to study behavior and mental processes.
  • Psychologists follow the same general procedure
    when conducting research
  • Asking research questions
  • Forming hypothesis (hypotheses)
  • Testing the hypotheses
  • Analyzing the data (results)
  • And drawing conclusions
  • Eventually, replicating research

10
The Scientific Method
  • Step 1 Forming research questions
  • Beginning with scientific curiosity and interest,
    many research questions come from daily
    experience, psychological theory, or common
    knowledge.
  • Step 2 Forming hypotheses
  • A hypothesis is a predicted answer the question
    (or in other words, an educated guess).

11
The Scientific Method
  • Step 3 Testing hypotheses
  • Once a hypothesis has been formed, it must be
    scientifically tested and proved right or wrong.
  • This part of conducting research is the actual
    experiment.
  • Psychologists use a variety of methods to test
    hypotheses.
  • Step 4 Analyzing Results
  • Data is analyzed using statistics
  • The more data collected,
  • the more complex a task
  • it is to analyze.

12
The Scientific Method
  • Step 5 Drawing Conclusions
  • Once the results have analyzed, a psychologists
    can draw or make conclusions about his/her
    questions and hypotheses.
  • Step 6 Replication
  • Even when a research study carefully follows
    proper procedures, its findings might just
    represent a random occurrence.
  • To confirm the results and conclusions of a
    research study, the study must be replicated.
  • The study must be repeated and it must produce
    the same or similar results as before.
  • If there are different results, then the findings
    of the first study are questioned.

13
Research Methods Terminology
14
Hypothesis
  • Expresses a relationship between two variables.
  • A variable is anything that can vary among
    participants in a study.
  • Participating in class leads to better grades
    than not participating.

15
Independent Variable
  • Whatever is being manipulated in the experiment.
  • Hopefully the independent variable brings about
    change.
  • If there is a drug in an experiment, the drug
    is almost always the independent variable.

16
Dependent Variable
  • Whatever is being measured in the experiment
  • It is dependent on the independent variable.
  • The dependent variable would be the effect of the
    drug.

17
Operational Definitions
  • Explain what you mean in your hypothesis.
  • How will the variables be measured in real life
    terms.
  • How you operationalize the variables will tell us
    if the study is valid and reliable.
  • Lets say your hypothesis is that chocolate
    causes violent behavior.
  • What do you mean by chocolate?
  • What do you mean by violent behavior?

18
Selecting Subjects
  • Population all members of a given
  • group (of study)
  • Sample a subset of the population which is
    representative of the whole population
  • Random Sample a sample in which every member of
    the population has an equal chance of being
    selected
  • Stratified Sample a sample in which each
    subgroup of the population is represented
    proportionally to its size in the population

19
Key Research Terminology
  • Using a random sample that represents the whole
    population, a researcher can generalize findings
    to the entire population.
  • CAUTION Overgeneralization is the making of
    generalizations using unrepresentative cases. It
    is easy to do but typically erroneous.
  • False Consensus Effect the tendency to
    overestimate the extent to which others share our
    beliefs and behaviors

20
Methods of Collecting Data
  • Survey commonly used in both descriptive and
    correlational studies, questionnaire method
    sampling many cases (individuals) in less depth
  • Case Study the study of one or more individuals
    in great depth, to inform about an entire
    population or sample
  • Testing psychological tests are given to
  • measure certain mental processes, such as
    intelligence, aptitude, or personality

The ideal case study is John and Kate. Really
interesting, but what does it tell us about
families in general?
21
The Survey Method
  • Use Interview, mail, phone, internet etc
  • The Good- cheap, anonymous, diverse population,
    and easy to get random sampling (a sampling that
    represents your population you want to study)

22
Survey Method The Bad
  • Low Response Rate
  • People Lie or just misinterpret themselves.
  • Wording Effects

How accurate would a survey be about the
frequency of diarrhea?
23
Naturalistic Observation
  • Observing and recording behaviors of an organism
    in natural environment
  • No control- just an observer (do not manipulate
    the environment)
  • This method does not explain behavior but
    describes it

What are the benefits and detriments of
Naturalistic Observation?
24
Correlational Research
  • Detects relationships between variables
  • Does NOT say that one variable causes another

There is a positive correlation between ice cream
and murder rates. As more ice cream is eaten,
more people are murdered. Does that mean that
ice cream causes murder?
25
Types of Correlation
  • Negative Correlation
  • The variables go in opposite directions.
  • Positive Correlation
  • The variables go in the SAME direction.

Studying and grades hopefully has a positive
correlation.
Heroin use and grades probably has a negative
correlation.
26
Correlation vs. Cause Effect
  • Correlation coefficient is a statistical measure
    of relationship (it reveals how closely related
    two factors are or how closely two factors vary
    together and thus how well either one predicts
    the other).
  • Positive and negative correlations are possible
  • A relationship does not mean causation!!!
  • For example, watching TV violence positively
    correlates with aggressive behavior but does not
    necessarily mean watching violence on TV causes
    aggressive behavior.

27
Correlation Coefficient
  • A number that measures the strength of a
    relationship.
  • Range is from -1 to 1
  • The relationship gets weaker the closer you get
    to zero.
  • Which is a stronger correlation?
  • -.13 or .38
  • -.72 or .59
  • -.91 or .04

28
How to Read a Correlation Coefficient
29
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30
Experimental Method
Smoking causes health issues.
  • Looking to prove causal relationships
  • Cause Effect
  • Laboratory v. Field Experiments

Eating too many bananas causes
Constipation
31
Experimental Research
  • In an experiment, participants receive what is
    called a treatment, such as a change in room
    temperature or a new drug.
  • Then, psychologists carefully observe the
    participants to determine how the treatment
    influences their behavior.

32
Independent and Dependent Variables
  • All research studies measure and observe
    variables (factors), especially experimental
    studies.
  • In an experiment, the independent variable is the
    factor that the researcher manipulates (controls)
    so that they can determine its effect on the
    dependent variable.
  • The dependent variable is the factor that depends
    on the manipulated independent variable(s).

33
Experimental and Control Groups
  • The experimental group is a group of participants
    who receive the treatment or manipulated
    variable.
  • The control group is a group of participants who
    do not receive the manipulated variable (instead
    a placebo of sorts).
  • All other variables/factors are held constant (or
    equal) for both groups (to try to isolate a cause
    and effect relationship between independent
    variable(s) of interest to the research
    psychologist and the dependent variable.
  • If the research psychologist fails to manage the
    other variables (or hold them constant), they
    become confounding variables. Confounding
    variables are baaaaad!!!

34
Beware ofConfounding Variables
  • The object of an experiment is to prove that A
    causes B.
  • A confounding variable is anything that could
    cause change in B, that is not A.
  • If I wanted to prove that smoking causes heart
    issues, what are some confounding variables?

Lifestyle and family history may also effect the
heart.
35
Experimental Method continued
  • Psychologists randomly place participants
    (subjects) into one group or another.
  • EXAMPLE The effect of extracurricular activities
    on students academic success.
  • Once subjects are randomly placed into the
    control and experimental groups, the researcher
    makes sure that all other variables are the same
    for all students regardless of group.
  • Using this grouping method in the experimental
    method is called a controlled experiment.
  • The Placebo Effect
  • In research studies and in our daily lives, our
  • expectations affect what happens to us.
  • Feeling better simply because we expect to
  • feel better and for no other reason is an
  • example of the placebo effect.
  • A placebo is a substance or treatment that
  • has no effect apart from the persons belief
    in it.

36
Experimental Method continued
  • Single-blind vs. Double-blind Studies
  • In a single-blind study, participants do not know
    whether they are receiving the treatment (the
    manipulated independent variable) or not. In
    other words, they do not know if they are in the
    experimental group or in the control group.
  • This process avoids the placebo effect.
  • In a double-blind study, both participants and
    researchers are unaware of who has placed in
    which group.

37
Practice Identifying Independent Variable and
Dependent Variable
  • In addition to finding the I.V and the D.V.,
    identify
  • The experimental group/condition(s)
  • The control group/condition
  • A possible confounding variable
  • Hint The third example has two
  • experimental groups/conditions

38
Descriptive Statistics
  • Just describes sets of data
  • You might create a frequency distribution,
    frequency polygons or histograms
  • Measures of Central Tendency
  • (1) Mean The average of all scores in a
    distribution
  • (2) Median The central score in a
    distribution (middle)
  • (3) Mode The score that appears most
    frequently in a distribution

39
Measure of Central Tendency
  • Mean, Median and Mode.
  • Watch out for extreme scores or outliers.

Lets look at the salaries of the employees at
Dunder Mifflen Paper in Scranton
25,000-Pam 25,000- Kevin 25,000-
Angela 100,000- Andy 100,000- Dwight 200,000-
Jim 300,000- Michael
The median salary looks good at 100,000. The
mean salary also looks good at about
110,000. But the mode salary is only
25,000. Maybe not the best place to work. Then
again living in Scranton is kind of cheap.
40
Normal Distribution
  • In a normal distribution, the mean, median and
    mode are all the same.
  • The mean is the most commonly used measure of
    central tendency, but its accuracy can be
    distorted by extreme scores or outliers.

41
Distributions
  • Outliers skew distributions have a more
    dramatic effect on the mean
  • If group has one high score, the curve has a
    positive skew (contains more low scores)
  • Positively skewed the mean is higher than
    the median
  • If a group has a low outlier, the curve has a
    negative skew (contains more high scores)
  • Negatively skewed the mean is lower than
    the median

42
Other measures of variability
  • Range distance from highest to lowest scores.
  • Standard Deviation the variance of scores around
    the mean.
  • The higher the variance or SD, the more spread
    out the distribution is.
  • Low SD indicates that the data points tend to
    be very close to the mean
  • High SD indicates that data points are spread
    out over a large range of values

Shaq and Kobe may both score 30 ppg (same
mean). But their SDs are very different!
43
Scores
  • A unit that measures the distance of one score
    from the mean.
  • A positive z score means a number above the mean.
  • A negative z score means a number below the mean.

44
Normal Distribution
Decker Story
Approx. 68 of scores in a normal distribution
fall within 1 standard deviation point of the mean
Approx. 95 of scores fall within 2 standard
deviation points of the mean
45
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46
Inferential Statistics
  • The purpose is to discover whether the finding
    can be applied to the larger population from
    which the sample was collected.
  • T-tests, ANOVA or MANOVA
  • P-value .05 for statistical significance.
  • 5 likely the results are due to chance.

47
Statistics Research Methods
  • Null hypothesis (H0) is a hypothesis (scenario)
    set up to be nullified, refuted, or rejected
    ('disproved' statistically) in order to support
    an alternative hypothesis
  • Type I error the error of rejecting a null
    hypothesis when it is actually true
  • Type II error the error of failing to reject a
    null hypothesis when the alternative hypothesis
    is the true state of nature

48
T-test
  • The t-test assesses whether the means of two
    groups are statistically different from each
    other. This analysis is appropriate whenever you
    want to compare the means of two groups
  • www.graphpad.com/quickcalcs/ttest1.cfm
  • X mean of group
  • Var Standard deviation of group
  • N number in sample

49
Research Statistics Assignment 1
  • Gather shoe size data from 10 females and 10
    males, recording the shoe size of each.
  • Then calculate the measures of central tendency
    (mean, mode, median) and graph the data set in a
    frequency histogram or box-plot for both the
    female findings and the male findings.
  • Find and discuss any outliers
  • Explain the gender difference, if one exists.

50
Research Statistics Assignment 2
  • Using the Research Question How many pairs of
    shoes do males and females own? Write a testable
    hypothesis.
  • Next, gather data from 10 females and 10 males,
    recording the number of shoes owned by each.
  • Ask your participants, How many pairs of shoes
    do you own? and (obviously) record their answer
    and gender.
  • Calculate the measures of central tendency and
    standard deviation and test for differences
    between means using a t-test. (use
    www.graphpad.com/quickcalcs/ttest1.cfm to help
    you calculate a t-score)
  • Write a brief conclusion about your results (at
    least 1 paragraph). Make sure you give an
    explanation for the differences between the
    gender.

51
Mr. Q is Definitely an Outlier!
52
APA Ethical Guidelines for Research
  • IRB- Internal Review Board
  • Both for humans and animals

53
Animal Research
  • Clear purpose
  • Treated in a humane way
  • Acquire animals legally
  • Least amount of suffering possible

54
Human Research
  • No Coercion- must be voluntary
  • Informed consent
  • Anonymity
  • No significant risk
  • Must debrief
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