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AP Psychology: Chapter 1: Thinking Critically With Psychological Science

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Title: AP Psychology: Chapter 1: Thinking Critically With Psychological Science


1
AP Psychology Chapter 1 Thinking Critically
With Psychological Science
2
Solve ME
  • A man is traveling from work and wants to go
    home. He will not go home because there is
    another man in a mask waiting there for him.
    What does the first man do for a living?
  • The man is a runner at third base and he is
    trying to score a run

3
Solve ME
  • A man is found shot to death in a room with a
    table, four chairs, and 53 bicycles. Why was he
    murdered?
  • There are 52 Bicycle playing cards in a normal
    deck. He was playing with an extra ace.

4
  • What is critical thinking?
  • How does it relate to psychology and this course?

5
Lets Make A Deal!
  • One Volunteer is Needed for A chance to win
    1,334,499 Turkish dollars!

6
Lets Make A Deal Shows Us That
  • Human Intuition is highly limited.
  • Critically thinking rarely comes easily to us!
  • Critical Thinking thinking that does not blindly
    accept arguments and conclusions
  • examines assumptions
  • discerns hidden values
  • evaluates evidence
  • An awareness to our own vulnerability

7
Lack of Intuition
  • Hindsight Bias tendency to believe, after
    learning an outcome, that one would have foreseen
    it.
  • the I-knew-it-all-along phenomenon

8
Lack Of Intuition
  • Overconfidence we tend to think we know more
    than we do.
  • We can't always trust our common sense or
    intuition we need research

9
Research Strategies
  • Theory
  • an explanation using an integrated set of
    principles that organizes and predicts
    observations
  • Low self esteem contributes to depression
  • Hypothesis
  • a testable prediction
  • often implied by a theory
  • Allows us to test and reject or revise the theory
  • People with low self esteem score higher on a
    depression scale

10
Scientific Method
lead to
11
How to check our bias
  • Operational Definition
  • a statement of procedures (operations) used to
    define research variables
  • You want to be clear enough so that the test and
    observations can be replicated
  • To give the study more credibility it is usually
    done with different subjects in different
    situations
  • Make sure studies are valid and reliable

12
Research Strategies
  • 1. Descriptive- making observations that describe
    behavior
  • 2. Correlational- detecting correlations that
    help predict behavior
  • 3. Experimental-doing studies that help explain
    behavior

13
Research Methods- Descriptive
  • Case Study
  • an observation technique in which one person is
    studied in depth in the hope of revealing
    universal principles
  • Longitudinal
  • Cross Sectional
  • Drawbacks of case study individuals can be
    atypical and lead to false findings.
  • Anecdotal Stories

14
Research Methods- Descriptive and Correlation
  • Survey
  • technique for ascertaining the self-reported
    attitudes or behaviors of people
  • usually by questioning a representative, random
    sample of them

15
Components of Survey
  • Population all the individuals you are
    interested in knowing something about.
  • Sample the individuals you actually question.
  • Sampling should always be taken randomly from the
    population so that it is representative, meaning
    each individual in the population had an equal
    chance of being selected.

16
Drawbacks of Surveys
  • 1.) Improper Sampling
  • 2.) Question Wording Can Effect the results of a
    survey.
  • Ex Should cigarette ads or pornography be
    allowed on television?
  • Ex. Mississippi River- Is the Mississippi River
    longer or shorter than 500 miles? How long is the
    Mississippi River?
  • Is the Mississippi River longer or shorter than
    3000 miles?How long is the Mississippi River?

17
Importance of Proper Sampling
  • False Consensus Effect tendency to overestimate
    the extent to which others share our beliefs and
    behaviors.
  • Overgeneralizing extreme examples can lead you to
    false conclusions!

18
Types of Research-Descriptive
  • Naturalistic Observation observing and
    recording behavior in naturally occurring
    situations without trying to manipulate and
    control the situation
  • Drawbacks hard to identify any type of
    causation since there is no controls.

19
Correlation Research
  • Correlation Research research that looks at a
    relationship between two things. How well does
    one factor predict the other?
  • Ex Consumption of Ice Cream and Drowning.

20
Types of Correlations
  • Positive Correlation a relationship in which
    increases in one variable leads to increases in
    the other.
  • Ex Amount of fat burned is positively
    correlated with amount of sit-ups completed
  • Negative Correlation a relationship in which
    increases in one variable leads to decreases in
    the other.
  • Ex As tooth brushing goes up, tooth decay goes
    down

21
Some More Correlation Examples
  • Married people tend to have higher measures of
    happiness.
  • Children who watch high amounts of television are
    more aggressive.
  • People with low self-esteem are more likely to be
    depressed.
  • What meanings can we make of these examples?

22
Correlations Continued
  • Correlation Coefficient the statistical measure
    of the extent to which two factors vary together
    and thus how well either factor predicts the
    other. (number that measures strength of the
    correlation).
  • STRONGEST CORRELATIONS are 1 and 1. 1 is a
    perfect positive correlation while 1 is a
    perfect negative correlation.
  • Correlations are always between 1 and 1. A
    correlation of Zero means there is no
    relationship.

23
Correlation Scatterplots
24
Indicates direction of relationship (positive or
negative)
Correlation coefficient
r .37
  • Indicates strength
  • of relationship
  • (0.00 to 1.00)

25
  • R.37
  • R-1.00
  • R.17
  • R -.08

26
Correlation Measures
  • Scatterplot
  • a graphed cluster of dots, each of which
    represents the values of two variables
  • the slope of the points suggests the direction of
    the relationship
  • the amount of scatter suggests the strength of
    the correlation
  • little scatter indicates high correlation
  • also called a scattergram or scatter diagram

27
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29
Correlation and Causation
  • Correlation does not prove causation
  • Ex- negative correlation between self-esteem and
    depression
  • Heredity and brain chemistry might play a role
  • Among men, length of marriage correlates
    positively with hair loss- because both are
    associated with a third factor.
  • Age
  • Correlation indicates the possibility of a cause
    and effect relationship, but DOES NOT prove
    causation

30
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31
Intuition Limit 976
  • Illusory Correlation the perception of a
    relationship where none exists.
  • Sugar makes kids more hyperactive
  • Wet hair and cold hair cause a cold
  • Dont overgeneralize extreme cases GET THE DATA!!

32
One last check..
  • You need to make sure your study is reliable and
    valid.
  • Reliability-if your study was replicated would
    you get the same results?
  • Validity- Does the study or experiment test what
    it is designed to test.

33
Summing Up Surveys, Naturalistic Observation,
Case Studies, and Correlation Research
  • All of these methods look to describe the
    behavior not to explain it!
  • Experimental Designed research is the only
    research that gets at causationNEXT TIME!

34
Random Sequences
  • Your chances of being dealt either of these hands
    is precisely the same 1 in 2,598,960.

35
Warm Up
  • For the following research methods list one
    positive and one negative
  • 1. Corelational Study
  • 2. Case Study
  • 3. Naturalistic Study
  • 4. Survey
  • 5. Experiment

36
  • Experimentation
  • and
  • Statistics

37
Experiments

38
Experimentation
  • Experiments are the best way to isolate cause and
    effect
  • the investigator manipulates one or more factors
    (independent variables) to observe their effect
    on some behavior or mental process (the dependent
    variable) while controlling other relevant
    factors by random assignment of subjects
  • by random assignment of participants the
    experiment controls other relevant factors.
  • Breast Milk Example

39
Experimentation
  • Research Strategies
  • Double-blind Procedure
  • both the subject and the research staff are
    ignorant (blind) about whether the subject has
    received the treatment or a placebo
  • commonly used in drug-evaluation studies
  • Placebo
  • an inert substance or condition that may be
    administered instead of a presumed active agent,
    such as a drug, to see if it triggers the effects
    believed to characterize the active agent
  • Placebo Effect- the effect of positive thought
    and willpower on an experiment

40
Experimentation
  • Research Strategies
  • Experimental Condition
  • The group that is exposed to the treatment, that
    is, to one version of the independent variable (
    real drug)
  • Control Condition
  • The group that contrasts with the experimental
    treatment . Get the placebo, or possible nothing
  • serves as a comparison for evaluating the effect
    of the treatment
  • Example- Viagra

41
Experimentation
  • Research Strategies
  • Random Assignment
  • assigning subjects to experimental and control
    conditions by chance
  • minimizes pre-existing differences between those
    assigned to the different groups
  • Want similar age, attitudes.

42
Experimentation
  • Research Strategies
  • Independent Variable
  • the experimental factor that is manipulated
  • the variable whose effect is being studied
  • Dependent Variable
  • the experimental factor that may change in
    response to manipulations of the independent
    variable
  • in psychology it is usually a behavior or mental
    process
  • It can vary depending on what happens during the
    experiment
  • Cause/effect If/Then

43
Experimentation
  • Confounding Variables-
  • Variables that cause changes in the DV besides
    the IV
  • Breast Feeding Example
  • Operational Definitions
  • Example Viagra
  • IV- Viagra or placebo- time, amount
  • DV- Sex- ..

44
Experimentation
  • Problems-
  • Sometimes not feasible or ethical
  • 1. Obtain consent
  • 2. Protect from harm
  • 3. Confidential
  • 4. Fully explain research after the exp.
  • Animals?
  • Results may not overgeneralize to other contexts

45
  • Statistics

46
Describing Data
  • Researchers first need to organize their data
  • Pie Chart, Bar graph
  • Descriptive Statistics- describe the data, but
    dont focus or the relationship

47
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49
Measure of Central Tendency
  • 3 measures of Central Tendency- Mode , Mean and
    Median
  • Mode- the most frequently occurring score
  • Mean- average
  • Median- the middle score, when you arrange the
    score in order from the highest to lowest
  • Be Careful- can a few extreme score through off
    any one of the central tendencies?
  • What's wrong with- income for 62 is below average

50
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51
Measures of Variation
  • Need to know the variation in the data, how
    diverse or similar the scores are
  • Range the gap between the highest and lowest
    score
  • Remember extremes scores can skew the data
  • 475,000 and 710,000

52
Measures of Variation
  • The more useful measure is Standard Deviation
  • It gauges if scores are packed together or
    dispersed
  • Uses info from each score
  • Smaller Standard Deviation for more similar
    populations
  • Higher Standard Deviation for more diverse
    populations

53
When is an Observed Difference Reliable?
  • 1. Representative samples are better than biased
    samples
  • 2. Less variable observations are more reliable
    than those that are more variable
  • Consistency
  • 3. More Cases Are better than few

54
When is Difference Significant?
  • statistical significance (p) is a measure of the
    likelihood that the difference between groups
    results from a real difference between the 2
    groups rather than from chance
  • If statistically significant ..the differences
    are probably not due to chance
  • Statistical significance indicates the likelihood
    that a result will happen by chance. It does not
    indicate the importance of the result
  • The lower the P value, the less likely the
    results are due to chance (Plt.o1)

55
  • Ethics
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