Thinking Critically With Psychological Science Slide 2 2
Psychological Science 1.How can we differentiate between uniformed
opinions and examined conclusions? 2.The science of psychology
helps make these examined conclusions, which leads to our
understanding of how people feel, think, and act as they do! Slide
3 3 Thinking Critically with Psychological Science The Need for
Psychological Science The limits of Intuition and Common Sense The
Scientific Attitude The Scientific Method Slide 4 4 Thinking
Critically Description The Case Study The Survey Naturalistic
Observation Slide 5 5 Thinking Critically Correlation Correlation
and Causation Illusory Correlation Perceiving Order in Random
Events Slide 6 6 Thinking Critically Experimentation Exploring
Cause and Effect Evaluating Therapies Independent and Dependent
Variables Slide 7 7 Thinking Critically Statistical Reasoning
Describing Data Making Inferences FAQs About Psychology Slide 8
What About Intuition & Common Sense? Many people believe that
intuition and common sense are enough to bring forth answers
regarding human nature. Intuition and common sense may aid queries,
but they are not free of error. Slide 9 9 Limits of Intuition
Personal interviewers may rely too much on their gut feelings when
meeting with job applicants. Taxi/ Getty Images Slide 10
Overconfidence We tend to think we know more than we do. 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!!!) Slide 11 Overconfidence Sometimes we
think we know more than we actually know. Anagram BARGEGRABE
ENTRYETYRN WATERWREAT How long do you think it would take to
unscramble these anagrams? People said it would take about 10
seconds, yet on average they took about 3 minutes (Goranson, 1978).
Slide 12 12 The Scientific Attitude The scientific attitude is
composed of curiosity (passion for exploration), skepticism
(doubting and questioning) and humility (ability to accept
responsibility when wrong). Slide 13 13 Critical Thinking Critical
thinking does not accept arguments and conclusions blindly. It
examines assumptions, discerns hidden values, evaluates evidence
and assesses conclusions. The Amazing Randi Courtesy of the James
Randi Education Foundation Slide 14 14 Scientific Method
Psychologists, like all scientists, use the scientific method to
construct theories that organize, summarize and simplify
observations. Slide 15 How Do Psychologists Ask & Answer
Questions? Psychologists, like all scientists, use the scientific
method to construct theories that organize, summarize and simplify
observations. Slide 16 A theory is an explanation that integrates
principles and organizes and predicts behavior or events. For
example, low self-esteem contributes to depression. Theory Slide 17
A hypothesis is a testable prediction, often prompted by a theory,
to enable us to accept, reject or revise the theory. People with
low self-esteem are apt to feel more depressed. Hypothesis Slide 18
Research would require us to administer tests of self-esteem and
depression. Individuals who score low on a self-esteem test and
high on a depression test would confirm our hypothesis. Research
Observations Slide 19 Research Process Slide 20 Case Studies A
detailed picture of one or a few subjects. Tells us a great
storybut is just descriptive research. Does not even give us
correlation data. The ideal case study is John and Kate. Really
interesting, but what does it tell us about families in general?
Slide 21 Survey Method Most common type of study in psychology
Measures correlation Cheap and fast Need a good random sample
Low-response rate Slide 22 Survey Random Sampling If each member of
a population has an equal chance of inclusion into a sample, it is
called a random sample (unbiased). If the survey sample is biased,
its results are not valid. The fastest way to know about the marble
color ratio is to blindly transfer a few into a smaller jar and
count them. Slide 23 Sampling Identify the population you want to
study. The sample must be representative of the population you want
to study. GET A RANDOM SAMPLE. Stratified Sampling Slide 24
Naturalistic Observation Watch subjects in their natural
environment. Do not manipulate the environment. The good is that
there is no Hawthorne effect. The bad is that we can never really
show cause and effect. Slide 25 Correlational Method Correlation
expresses a relationship between two variable. Does not show
causation. As more ice cream is eaten, more people are murdered.
Does ice cream cause murder, or murder cause people to eat ice
cream? Slide 26 Types of Correlation Positive Correlation The
variables go in the SAME direction. Negative Correlation The
variables go in opposite directions. Studying and grades hopefully
has a positive correlation. Heroin use and grades probably has a
negative correlation. Slide 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
Slide 28 Perfect positive correlation (+1.00) Scatterplot is a
graph comprised of points that are generated by values of two
variables. The slope of the points depicts the direction, while the
amount of scatter depicts the strength of the relationship.
Scatterplots Slide 29 No relationship (0.00) Perfect negative
correlation (-1.00) The Scatterplot on the left shows a negative
correlation, while the one on the right shows no relationship
between the two variables. Scatterplots Slide 30 Data Data showing
height and temperament in people. Slide 31 Scatterplot The
Scatterplot below shows the relationship between height and
temperament in people. There is a moderate positive correlation of
+0.63. Slide 32 Example As the graph below (taken from the Church
of the Flying Spaghetti Monster website) shows, two things have
happened since the early 19th-century: one is that the number of
pirates has declined, the other is that global average temperatures
have risen.Church of the Flying Spaghetti Monster If correlation
implied causation, we would be able to infer a connection between
these two events. It is not the case, however, that global warming
is an effect of the decline in piracy. Neither is the decline in
piracy the result of increasing temperatures. Mere correlation does
not imply a causal connection. Slide 33 Correlation = not Causation
Real-World Example Nestle, the makers of the breakfast cereal
Shredded Wheat, once ran an advertising campaign in which the key
phrase was this: People who eat Shredded Wheat tend to have healthy
hearts. This is very carefully phrased. It does not explicitly
state that there is any causal connection between eating Shredded
Wheat and having a healthy heart, but it invites viewers of the
advertisements to make the connection; the implication is there.
Whether or not there is any such connection, the mere fact that the
two things are correlated does not prove that there is such a
connection. Slide 34 or Correlation and Causation Correlation does
not mean causation! Slide 35 Illusory Correlation The perception of
a relationship where no relationship actually exists. Parents
conceive children after adoption. Confirming evidence Disconfirming
evidence Do not adopt Disconfirming evidence Confirming evidence
Adopt Do not conceive Conceive Michael Newman Jr./ Photo Edit Slide
36 Given random data, we look for order and meaningful patterns.
Order in Random Events Your chances of being dealt either of these
hands is precisely the same: 1 in 2,598,960. Slide 37 Order in
Random Events Given large numbers of random outcomes, a few are
likely to express order. Angelo and Maria Gallina won two
California lottery games on the same day. Jerry Telfer/ San
Francisco Chronicle Slide 38 Experimentation Like other sciences,
experimentation is the backbone of psychological research.
Experiments isolate causes and their effects. Exploring Cause and
Effect Slide 39 Many factors influence our behavior. Experiments
(1) manipulate factors that interest us, while other factors are
kept under (2) control. Effects generated by manipulated factors
isolate cause and effect relationships. Exploring Cause &
Effect Slide 40 Experimental Method Looking to prove causal
relationships. Cause = Effect Laboratory v. Field Experiments
Smoking causes health issues. Slide 41 Experimental vs. Control
Groups Experimental Group The group exposed to manipulation of the
independent variable E.g. receives the DROW-Zs Control Group Group
NOT exposed to manipulation of the independent variable; used for
COMPARISON E.g. does NOT receive DROW-Zs May instead receive a
PLACEBO Random assignment to groups All subjects have an equal
chance of being in either the control group or experimental group!
Slide 42 Operational Definitions, Etc. Operational Definitions What
are we measuring and how? How are we defining VARIABLES (IV/DV)?
Allows experiment to be replicated by others E.g. what is a better
nights sleep? Sample Size: the bigger the better! What is the
difference between groups? Replication? Slide 43 In evaluating drug
therapies, patients and experimenters assistants should remain
unaware of which patients had the real treatment and which patients
had the placebo treatment. Evaluating Therapies Double-blind
Procedure Slide 44 Random Assignment Once you have a random sample,
randomly assigning them into two groups helps control for
confounding variables. Experimental Group v. Control Group. Group
Matching Slide 45 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. Slide 46 Dependent
Variable The dependent variable would be the effect of the drug.
Whatever is being measured in the experiment. It is dependent on
the independent variable. Slide 47 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? Slide 48
Beware of Confounding Variables If I wanted to prove that smoking
causes heart issues, what are some confounding 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.
Lifestyle and family history may also effect the heart. Slide 49
Hawthorne Effect But even the control group may experience changes.
Just the fact that you know you are in an experiment can cause
change. Whether the lights were brighter or dimmer, production went
up in the Hawthorne electric plant. Slide 50 Experimenter Bias
Another confounding variable. Not a conscious act. use Double-Blind
Procedure to counter this Slide 51 Statistics Recording the results
from our studies. Must use a common language so we all know what we
are talking about. Slide 52 Descriptive Statistics Just describes
sets of data. You might create a frequency distribution. Frequency
polygons or histograms. Slide 53 Measures of Central Tendency Mode:
The most frequently occurring score in a distribution. Mean: The
arithmetic average of scores in a distribution obtained by adding
the scores and then dividing by the number of scores that were
added together. Median: The middle score in a rank-ordered
distribution. Slide 54 Central Tendency Mean, Median and Mode.
Watch out for extreme scores or outliers. $25,000-Pam $25,000-
Kevin $25,000- Angela $100,000- Andy $100,000- Dwight $200,000- Jim
$300,000- Michael Lets look at the salaries of the employees at
Dunder Mifflen Paper in Scranton: 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.
Slide 55 Normal Distribution In a normal distribution, the mean,
median of the central tendency are equal! i.e. Sample Data Set: 1,
1, 2, 2, 2, 3, 3, 3, 3, 4, 4, 4, 5, 5 Slide 56 Measures of Central
Tendency A Skewed Distribution Slide 57 Distributions Outliers skew
distributions. If group has one high score, the curve has a
positive skew (contains more low scores) If a group has a low
outlier, the curve has a negative skew (contains more high scores)
Slide 58 Measures of Variation Range: The difference between the
highest and lowest scores in a distribution. Standard Deviation: A
computed measure of how much scores vary around the mean. Slide 59
Descriptive Statistics: Measures of Variation Range the difference
between the highest and lowest score in a distribution What does it
tell you? What DOESNT it tell you? Standard Deviation how much do
scores vary from the mean in a distribution? (see table 1.4 in text
p. 36) 1.Calculate mean 2.Calculate each scores deviates from the
mean 3.Square that difference 4.Add the sum of the squares 5.Divide
by the number of scores in the distribution 6.Take square root of
this 7.The number is equal to the value of ONE standard deviation
Slide 60 Standard Deviation Slide 61 Descriptive Statistics:
Measures of Variation So what? In a normal curve, this number
reveals the percentage of scores that falls within a particular
range 68% fall within one standard deviation from the mean 96% fall
within two standard deviations from the mean 99% fall within three
standard deviations from the mean What must the standard deviation
be for this distribution of IQ scores? Slide 62 Comparison Below is
a comparison of different research methods. Slide 63 Illusion of
Control 1.Illusory Correlation: the perception of a relationship
where no relationship actually exists. 2.Regression Toward the
Mean: the tendency for extremes of unusual scores or events to
regress toward the average. That chance events are subject to
personal control is an illusion of control fed by: Slide 64 Making
Inferences A statistical statement of how frequently an obtained
result occurred by experimental manipulation or by chance. Slide 65
Making Inferences 1.Representative samples are better than biased
samples. 2.The less variation in the data, the more reliable (if
variability is high in a distribution, the mean becomes less
meaningful) 3.More cases are better than fewer cases. (ask 2
friends how they like the class vs. asking 25) When is an Observed
Difference Reliable? Slide 66 Making Inferences When sample
averages are reliable and the difference between them is relatively
large, we say the difference has statistical significance. It is
probably not due to chance variation. For psychologists this
difference is measured through alpha level set at 5 percent. If
possibility of chance is above 5%, then study loses value. When is
a Difference Significant? Slide 67 Significant Difference? What is
the difference between the experiences of the control and the
experimental groups? What is the chance that the difference
happened due to chance? If it IS a significant difference, how
important is that difference (e.g. difference between IQ scores of
first- and later-born children is significant, but due to its very
small value, it is not important. Slide 68 Normal Distribution
Slide 69 Statistical Significance p =.05 p = The probability that
the results of the experiment were due to chance variations in the
sample groups Findings which have a p value above 5% dont find
those results valuable. p =.01 is more statistically significant
than p =.03 Slide 70 Frequently Asked Questions About Psychology
Q1. Can laboratory experiments illuminate everyday life? Ans:
Artificial laboratory conditions are created to study behavior in
simplistic terms. The goal is to find underlying principles that
govern behavior. Slide 71 FAQ Q2. Does behavior depend on ones
culture and gender? Ans: Even when specific attitudes and behaviors
vary across cultures, as they often do, the underlying processes
are much the same. Biology determines our sex, and culture further
bends the genders. However, in many ways woman and man are
similarly human. Ami Vitale/ Getty Images Slide 72 FAQ Q3. Why do
psychologists study animals, and is it ethical to experiment on
animals? Ans: Studying animals gives us the understanding of many
behaviors that may have common biology across animals and humans.
From animal studies, we have gained insights to devastating and
fatal diseases. All researchers who deal with animal research are
required to follow ethical guidelines in caring for these animals.
D. Shapiro, Wildlife Conservation Society Slide 73 FAQ Q4. Is it
ethical to experiment on people? Ans: Yes. Experiments that do not
involve any kind of physical or psychological harm beyond normal
levels encountered in daily life may be carried out. Slide 74 FAQ
Q5. Is psychology free of value judgments? Ans: No. Psychology
emerges from people who subscribe to a set of values and judgments.
Roger Shepard Slide 75 FAQ Q6. Is psychology potentially dangerous?
Ans: It can be, but is not when practiced responsibly. The purpose
of psychology is to help humanity with problems such as war,
hunger, prejudice, crime, family dysfunction, etc.
