Chapter 20 - Plain Local Schools
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Transcript Chapter 20 - Plain Local Schools
CHAPTER 20
Psychological Research and Statistics
Objectives
Describe the process of psychological research
Name the different types of psychological
research and some of the methodological
hazards of doing research
Describe descriptive and inferential statistics
Name specific research methods used to
organize data
Gathering Data
How do psychologists collect information
about the topic they’ve chosen to study?
Gathering Data
Validity – verifying that a claim is correct, or
disproving it
A claim cannot be valid until it has been
repeatedly tested and found to be true
Example: Fashion magazine advertisements
(“thicker” hair, no wrinkles, rapid weight loss)
Innocent
until proven guilty – have to be found
guilty in order for your arrest to be valid
Gathering Data
Sample – relatively small group out of the total
population
Population – an entire group as a whole
Sample must be representative of the population
If a sample is not representative, then it is biased
How can researchers avoid bias?
Gathering Data
What does correlation mean?
The degree of relatedness between two sets
of data
Two
types - positive correlation & negative
correlation
Gathering Data
IQ scores and academic success – positive
correlation (direct relationship)
The higher your IQ, the higher your grades
Car speed and time it takes to travel somewhere
– negative correlation (inverse relationship)
- as car speed increases, time it takes to reach
your destination decreases
Correlations
Your turn!
Hours in the sun and chance of sunburn
Positive
correlation
Amount of exercise and % body fat
Negative correlation
Mrs. Bird’s high school GPA and your high school GPA
no correlation
Correlations
A researcher uses statistics to compute their
research findings
Statistics
= field of mathematics that involves the
analysis of numerical data about representative sample
of population
Correlation coefficient =
needs
to be near 1 (-/+), the closer results are to -1 or
+1 the better the relatability between the two
variables
Experiments
Why do researchers choose experimentation over
other research methods?
Researchers
can control the situation.
Can establish cause and effect, only research
method in which you can
The goal of research is to prove or disprove a
...
Hypothesis
Experiments
Variables – conditions and behaviors that are
subject to variation/change
Two types of variables – independent and
dependent
IV – manipulated variable in order to view
its effects
DV – dependent upon the IV – affected by
it, the one the researcher measures
Experiments
Experimental group – consists of subjects who
undergo the experimental treatment –
variables are applied to this group
Control group – consists of subjects who do not
receive experimental treatment
Why is this group necessary?
Experiments in Psych
Avoid Researcher Bias: researcher’s desire to prove
hypothesis affects results
Avoid Self-fulfilling prophecy: researcher’s desire to
prove hypothesis affects results
Could be very subtle or unconscious, but researcher
will treat one group slightly differenty (body
language, tone of voice)
Avoiding Researcher Bias
Use double-blind = neither researcher nor subjects
know what group they are in, helps reduce
researcher influencing results
Confounding variables = factors that cause changes
in the dependent variable that aren’t the
independent variables
Quasi-Experiment (“sort of” experiment)
For example, imagine that we wanted to do a study to compare student
performance. Imagine further that we scheduled two sections of the
course, let students sign up for which one they wanted, and then taught
one using cooperative learning and the other using standard
lecture. Note that this study includes a manipulated independent
variable, but it lacks random assignment of participants to conditions.
The problem with this approach, of course, is that there might be
differences between the two groups of students other than the style of
teaching to which they were exposed. Perhaps the students who signed
up for the earlier section are more “gung ho.” Or perhaps the students
who signed up for the evening section are more likely to be working
adults. Or perhaps the students in the 1:00 p.m. section tend to be
drowsy after lunch. It is possible that differences in the dependent
variable could have been caused by these differences rather than
differences in teaching style.
So what’s the problem
with quasi-experiments?
No random assignment!
= a sort of experiment!
Naturalistic Observations
Naturalistic observation – viewing the subjects
of an experiment in their natural habitat
IMPORTANT: Subjects CANNOT know they
are being watched!
Why is this important??
ACTIVITY TIME!
CASE STUDY
Case study – a scientific biography of a group
or person, very in depth look at a phenomena
Most use long-term research to gather tons
of data in order to generate new hypotheses
Utilize lots of different tests to collect data
ex) facial agnosia, split brain patients
Surveys
Surveys – an interview/questionnaire that
gathers data on the attitudes, beliefs, and
experiences of large numbers of people
Longitudinal Studies
Longitudinal studies – covers a long period of
time, same subjects followed for long time and
questioned at different intervals in time (ex.
Age 20, 25, 30 35)
Psychologists study subjects over regular
intervals for a period of years
Allows for examination of consistencies and
inconsistencies as development occurs
Cross-sectional
Cross-sectional studies – individuals are
organized/studied on the basis of age
Question different groups of people that
represent different stages of development
Avoiding Errors
How can researchers avoid errors while doing research?
self-fulfilling prophecy - Researchers finding what
they want to find, while overlooking contrary
evidence
Example experiment – testing a new medicine
Single Blind – subjects do not know if they have a are
in control group (placebo) or in the experimental
group ( get real IV)
Double Blind – subjects AND experimenter have no
knowledge of who in is experimental or control group
= best option if possible to design
Smile Break
Statistics
A branch of mathematics that enables
researchers to organize and evaluate the
data they collect
Statistics
Descriptive statistics – listing and
summarizing data in a practical and
efficient way
Examples
– graphs, averages
Statistics
Frequency distribution – table that arranges
data in a way that allows us to see how often
a particular score occurs
Histogram – similar to bar graphs – always
vertical & the bars always touch
Frequency polygon – no bars just lines to
visually display data
Frequency Distribution
Histogram
Frequency Polygon
Central Tendency
Central tendency – a number that
describes something about the “average”
score
Used to summarize information into
statistics
Measures
of CT: mean, median mode
Central Tendency
Mean – an “average” score
Most commonly used measure of CT
To find the mean, you add all scores and
divide by the number of scores
Central Tendency
Median – the middle score
The midpoint of a set of scores, so it
divides the frequency distribution into
two halves
Mode
– the most frequent score
Central Tendency
0, 3, 4, 4, 5, 5, 6, 7, 8, 8, 8, 9, 9, 10, 10
Mean – 6.4
Median – 7
Mode - 8
Measures of Variance
Distributions show us not only the
“average” score, but also how “spread
out” these scores are.
Variance – provides an index of how
spread out the scores of a distribution are
Measures of Variance
Range – subtract the lowest score from the
highest score
Standard deviation – a measure of distance,
describing an “average” distance of every
score to the mean
The larger the standard deviation, the more
spread out the scores are
Standard Deviation
Inferential Statistics
Used to determine whether or not the data that
researchers collect supports their hypotheses,
or whether their results are merely due to
chance outcomes, draw conclusions &
interpret data
probability
& chance
If probability that results are due to chance
is less than 5% ( .05), researchers can be
confident in their findings (less than 1 in 20
chance)
Inferential Stats Cont
Meta-Analysis-
Ethical Guidelines
Read page 59