Download chapter 2 review with answers

Chapter 2 Review
A) Experimental Methods : involves a
control group, and an
experimental group. Only
considered scientific if conclusions
can be verified or refuted
1. Testable Hypothesis
- to be testable, a hypothesis
must be formulate
precisely.
- The variable under study must
be clearly defined. Researchers
achieve these clear
formulations by providing
operational definitions of the
relevant variables.
2. Independent variable
- Variable that experimenter
manipulates
3. Dependent variable
- Variable that is measured
by the experimenter
4. Control group
- Group that does not receive
the treatment
5. Experimental group
- group that receives the
treatment
6. Operational definitions
- Description of your
variables. Example:
dependent variable may be
academic performance. You
would need to define how
you will measure academic
performance
7. Participants
-
Subjects who are
participating in your study
8. Steps in designing an
experiment (See slide in power
point)
9. Extraneous
- Undesired variables that
affect the results of an
experiment
10. Confounding variable
- Inconsistencies between
the experimental & control
group that skew the results.
- Because of confounding
variable you are now
unsure on what affected the
results…was in the
confounding or
independent variable?
11. Random sample
- You must insure that your
group of participants
represents your larger
population
12. Random assignment
- Randomly assign
participants to control
group and experimental
group
13. Random selection
- Ensures everyone an equal
opportunity in being
selected for an experiment
14. Strengths and weaknesses
- Strengths: See all strengths
for each research method in
power point
-
B)
1.
2.
3.
Weakness: See all
weaknesses for each
research method in power
point
Description/Correlational
Methods
Naturalistic observation
- Observing subjects in their
natural habitats/no
interaction b/w researcher
and subjects
Case study
- An in depth study of one
person, thing, event or topic
- Strength: can provide
valuable insight on an
issue/condition
- Weakness: findings can
rarely be generalized to a
population
Surveys
- Used to research the selfported attitudes of behavior
of people
- Questionnaire/survey/inte
rview]
- Strength: can be
generalized to a larger
population (if sample is
random)
- Weaknesses: Social
desirability bias
- Individuals tend to answer
questions in a way that is
socially acceptable.
- Example: How many hours
of TV do you watch? You
answer 5 per week when
-
you really watch 30 hrs
worth but you don’t want to
seem like a couch potato
Another weakness:
Response set: the tendency
to exhibit a particular pattern
of response independent of
the question being asked.
Example: Christmas tree the
answers
-
-
4.
5.
6.
7.
When you answer all the
questions without actually
reading the questions
Example: answer all of the
questions with a 5 if you
were asked to rank from 11
to 5. Or Christmas treeing
the answers
Statistics: descriptive & inferential
- Descriptive: organizing and
summarizing data
- Inferential: interpreting
data and drawing
conclusions – use of
probability
Measures of central tendency
a. Mean: average
b. Median: number in the middle
c. Mode: number that is seen the
most
Standard deviation
- measure that is most
commonly used to describe
variability in data
distributions
Positive correlation
- Variables both go in the
same direction.
-
The closer to +1 the
stronger the correlation
- Example: attendance
increases…GPA increases
8. Negative correlation
- Variables go in opposite
direction
- The closer to -1 the
stronger the correlation
Example: exercise
increases…weight decrease
9. Statistical significance
- If the results from the
experiment are minimal but
are NOT by chance! They are
STATISTICALLY SIGNIFICANT
C) Miscellaneous
1. Sampling bias
- Must have a sample that
represents the population
that you are conducting
research on
2. Placebo effects
3. Scatter plots
- Used to graph the
correlation between two
measures obtained on a
group of individuals
- The more the data forms a
line, the stronger the
correlation
- The slope of the line
suggests a positive
correlation
4. Experimenter bias
- Can be avoided with
double-blind
5. frequency polygon
a line figure used to present
data from a frequency
distribution
6. histogram
- a bar graph that represents
data from a frequency
distribution
- used to summarize
statistical data
7. Double blind
- Both the experimenter and
the participants are
unaware of the testable
hypothesis or what is being
tested
8. Quasi-experiment
- An experiment without one
of the factors involved in an
actual experiment
9. Single blind experiment
- When the participants are
unaware of what is being
tested
10. Ethics
- Must let the participants
know what they are signing
up for
- Must debrief participants
- Must have participants
provide written consent to
share results if you want to
share them
- suggested rules for acting
responsibly and morally
when conducting research
or in clinical practice
- guidelines by the APA
prevent unnecessary
deception to humans and
animals, and to protect
confidentiality
11. Cross sectional study
-
Investigate participants
from various ages and
compare them
12. Longitudinal study
- Investigate participants
over a long period of time
- Cohort-effect: occur when
differences b/w ages occur
b/c they group up @
different times
-