Psychological Disorders by ewghwehws

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									Psychological Research
 Methods & Statistics




Excavating Human Behaviors
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.
            Hindsight Bias
 The tendency to
  believe, after learning
  the outcome, that you
  knew it all along.
 With 20/20
  hindsight, everything
  seems obvious.
               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!!!)
Exercise: Unscramble these Anagrams

    WREAT
    ETRYN
    GRABE
    Anagram Solutions

WREAT --- WATER
ETRYN --- ENTRY
GRABE --- BARGE
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:
     1.   Asking research questions
     2.   Forming hypothesis (hypotheses)
     3.   Testing the hypotheses
     4.   Analyzing the data (results)
     5.   And drawing conclusions
     6.   Eventually, replicating research
    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”).
          The Scientific Method
 Step 3: Testing hypotheses –
     1. Once a hypothesis has been formed, it must be scientifically
        tested and proved right or wrong.
     2. This part of conducting research is the “actual” experiment.
     3. Psychologists use a variety of methods to test hypotheses.
 Step 4: Analyzing Results –
     1. Data is analyzed using statistics
     2. The more data collected,
        the more complex a task
        it is to analyze.
       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 –
     1. Even when a research study carefully follows proper
        procedures, its findings might just represent a random
        occurrence.
     2. To confirm the results and conclusions of a research study,
        the study must be replicated.
     3. The study must be repeated and it must produce the same
        or similar results as before.
     4. If there are different results, then the findings of the first
        study are questioned.
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
    change of being selected
   Stratified Sample – a sample in which each
    subgroup of the population is represented
    proportionally to its size in the population
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
      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 Survey Method

 Used  in both descriptional and
  correlational research.
 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)
     Survey Method: The Bad

 Low  Response
  Rate
 People Lie or
  just
  misinterpret
  themselves.
 Wording         How accurate would a
  Effects         survey be about the
                  frequency of diarrhea?
      Naturalistic Observation
 Observing and recording
  behaviors of an organism
  in natural environment
 No control- just an
  observer
 This method does not
  explain behavior but
  describes it
    What are the benefits and detriments of
    Naturalistic Observation?
     Methods of Collecting Data
   Laboratory Observation – this research method
    involves watching and recording behaviors of
    organisms NOT in their natural environment BUT
    in a laboratory setting.

    Cross-sectional Studies – uses participants (subjects)
    of different ages to compare how certain variables
    may change over the life span.
    Longitudinal Studies – use one group of participants
    over a long period of time. This method of study
    tracks the change over time of the participants.
   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. Does that mean
            that ice cream causes
            murder?
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.
How to Read a Correlation
       Coefficient
       Experimental Research

   Explores cause and effect relationships
                                 Constipation
Eating too many bananas causes
    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.
      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).
    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!!!
Experimental Method                                           continued
   Psychologists randomly place participants (subjects) into
    one group or another.
            – EXAMPLE: The effect of extracurricular activities on student’s
              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 person’s belief in it.
     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.
           Statistics & Research Methods

   Describing (Quantifying) Data
       Scaling – assigning numbers to observed events
        (responses, etc.)
       Categorical Scale (Nominal) – a number/score is
        assigned to individuals so as to group responses into
        categories (example: gender)
       Ordinal Scale – assigning numbers to convey relative
        meaning among responses (example: making a list from
        “most” to “least”
       Interval Scale – assigning numbers/scores in which
        equal differences can be treated as equal units
        (example: reaction time)
       Ratio Scale – relative scores assigned by way of
        multiples and includes a true zero point (example: 15 is
        3 times greater than 5)
        Statistics & Research Methods
   Frequency Distribution – a set of data that tells you how many…
Descriptive Statistics
Measures of Central Tendency
 Mark the center of a distribution  Mean, Median, Mode
 Mean – is average of all the scores in a distribution
 Median – is the central score in a distribution
 Mode – is the score that appears most frequently
 The mean is the most commonly used measure of central tendency, but its accuracy
   can be distorted by extreme scores or outliers.

Measures of Variability
 Range – is the distance between the highest and lowest scores in a distribution.
 Variance – is the amount of difference/variability between scores in a distribution.
 Standard deviation – is simply the square root of the variance (Both variance and
   standard deviation relate the average distance of any score in the distribution from the
   mean).
 Z-scores – measure the distance of a score from the mean in units of standard
   deviation (to compare scores from different distributions).

   Normal Distribution or Normal Curve or Bell-shaped Curve – approx. 68% of
    scores in a normal distribution fall within one standard deviation of the mean and
    approx. 95% of scores fall within two standard deviation of the mean.
    Statistics & Research Methods
Inferential Statistics
   While descriptive statistics provide a way to summarize
    information about a sample studied, the purpose of inferential
    statistics is to determine whether or not findings can be
    applied to the larger population from which the sample was
    selected.
   The extent to which the sample differs from the population is
    known as sampling error.
   A few inferential statistical tests exist such as t-tests,
    ANOVAs, and MANOVAs.
   These tests take into account both the magnitude of the
    difference found and the size of the sample.
   All these tests yield a p value. The smaller the p value, the
    more significant the results.
   P value of .05 is the cutoff for statistically significant results.
    (p value of .05 means that a 5% chance exists that the results
    occurred by chance.
   P value of .01 is sometimes sought for greater certainty of
    significant results.
   P value can never equal 0 because one can never be 100%
    certain that results did not happen randomly by chance.
   Replication allows for greater certainty of results.
    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
                           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
    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 and box-plot.
   Find and discuss any outliers
   Explain the gender difference, if one exists.
    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.

								
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