TOPIC 2: PSYCHOLOGY AND RESEARCH

Question 1

THEORY, HYPOTHESIS, AND RESEARCH

Answer 1

goal is to create a useful theory: an organized set of principles.

• helps simplify facts about an aspect of the world.
• serves as coherent explanation.
• should allow testable predictions

Question 2

scientific theories

Answer 2

are well substantiated, well-supported, well documented explanations for our observations.

theories are not absolute, they are open to change if better evidence is found.

Question 3

scientific laws

Answer 3

can describe, but only theories can explain.

Question 4

the scientific method

Answer 4

1. ask questions, make observations, describe the phenomenon
2. develop an explanation (theory)
3. generate a hypothesis: testable prediction derived from a theory
4. design research study
5. collect relevant information

6 analyze and interpret the info; compare results with hypothesis

7. solicit peer reviews and report findings.

Question 5

what is a hypothesis

Answer 5

a prediction which is testable and is originally derived from a theory .

Question 6

case study

Answer 6

an in-depth study of an individual, group, m or event by observation. in person meeting, structured psychological tests, recording of physiological activity, on performance on certain tasks, or from archival records.

Question 7

pros and cons of case study

Answer 7

PROS:
-can be revealing and detailed

CONS:
-cannot determine cause of behaviour.

-atypical subject precludes generalization.

Question 8

survey

Answer 8

peoples self-reports to a questionnaire or interview

Question 9

pros and cons to surveys

Answer 9

PROS :
- reveals patterns in large numbers of people.

• easy to administer and score

CONS:
- effects of extremes are mediated

• demand characteristic : response can be influence by the questions itself
  (how wording effects)

Question 10

naturalistic observation

Answer 10

recording behaviour in organisms natural environment

Question 11

pros and cons to naturalistic observations

Answer 11

PROS:
- subjects unaffected by presence of researches

• describes behaviour in natural contexts; wide applicability

CONS:
- cannot determine cause of behaviour

• loss of experimental control

Question 12

correlation

Answer 12

two different variables are measured form individuals, and statistically analyzed for a relationship

Question 13

positive correlation

Answer 13

direct relationship between two variables, when one is effected so does the other.

Question 14

negative correlation

Answer 14

inverse relationship between two variables, when one is effected a certain way, the other variables is affected I the opposite direction.

Question 15

zero correlation

Answer 15

no relationship, the variables have no effect on on one another,

Question 16

pros and cons for correlation

Answer 16

PROS:
- may reveal relationship between variables

• can guide future by generating hypotheses

CONS:
- correlation does not mean that one variable causes the other (correlation does not imply causation)

Question 17

components of an experimentation

Answer 17

• indépendant variable
• dependant variable
• experimental group
• control group

Question 18

independent variable

Answer 18

factor of interest manipulated by experimentor

Question 19

dependant variable

Answer 19

factor measured by experimenter (“effect”)

• all extraneous factors are controlled or held constant

Question 20

experimental group

Answer 20

receive manipulated level of independent variable

Question 21

control group

Answer 21

receive normal level independent variable

Question 22

pros and cons to experimentation

Answer 22

PROS:
- allows cause and effect conclusions

CONS:
- unexpected variables

• some variables cannot be manipulated

Question 23

why are experiments conducted ??

Answer 23

• we learn cause and effect explanations

- thus, we control factors in an experiment

Question 24

why are experiments valid ??

Answer 24

• experiments provide support for a theory
• theory explains universe principles of behaviour
• these occur in a lab, as well as in real life.

Question 25

hindsight bias

Answer 25

• events aren’t obvious beforehand, but they seem very predictable after they occur.

Question 26

over confindence

Answer 26

false image of how confidence means correctness when it doesn’t.

Question 27

confirmation bias

Answer 27

seeking evidence confirming your beliefs–even to the exclusion of contradictory information

SOLUTION: replication of observation by others

Question 28

sampling bias

Answer 28

sample is not representative of the population.

SOLUTION: random selection.

Question 29

experimenter bias

Answer 29

researcher expectations influence change in dependant variable

SOLUTION: double-blind procedure, neither participant nor experimenter knows which treatment the participant is receiving.

Question 30

MODE

Answer 30

most common score, typically the highest score.

Question 31

MEDIAN

Answer 31

model score (50th percentile)

Question 32

MEAN

Answer 32

arithmetic average ( sum of scores divided by the numbers obscures)

Question 33

RANGE

Answer 33

difference between the highest score and lowest score

Question 34

standard deviation

Answer 34

average distance of the scores from the mean; indicates spread of scores around the mean

Question 35

normal curve

Answer 35

regular pattern of variability of human characteristics In the population

Question 36

correlation coefficient

Answer 36

• index of degree and directions of relationship between two variables
• positive / negative sign indicates relationship
• (0.00-1.00) indicates strength of relationship

Question 37

inferential statistics

Answer 37

allows interpretation of sample data; generalization

Question 38

statistically significant

Answer 38

if the probability is unlikely

<0.05

Question 39

Null hypothesis (H0)

Answer 39

in an experiment, the null hypothesis typically states that there is no difference between the experimental groups and control groups

Question 40

complications of inferential statistics

Answer 40

• larger samples are better (closer match to population)
• less variability is preferable ( can be more confident in stable results)
• there is no such thing as an average person.