Ch.2: research methods

Question 1

empiricism

Answer 1

The belief that accurate knowledge can be acquired through observation

Question 2

theories

Answer 2

hypothetical explanations of natural phenomena; ideas about how something works

Question 3

hypothesis

Answer 3

a falsifiable prediction based on a theory

Question 4

what are the methods (2) used to study human behaviour?

Answer 4

1. methods of observation (determine what people do)

2. methods of explanation (why people do what they do)

Question 5

operational defintions

Answer 5

a description of a property/variable in measurable terms

ie: for example, we might operationally define happiness as “a person’s self-assessment” or “the amount of dopamine in a person’s brain” or “the number of times a person smiles in an hour.”

Question 6

construct validity

Answer 6

the extent to which one adequately characterizes the property/variable; how well a study conceptualizes it variables

ie: measuring smiles per hour to measure emotions per day over measuring their IQ

Question 7

power

Answer 7

the ability to detect the presence of differences or changes in the magnitude of a property

Question 8

empirical method

Answer 8

set of rules and techniques for observation

Question 9

the scientific method

Answer 9

a procedure for using empirical evidence to establish facts.

Question 10

naturalistic observation

Answer 10

gathering data by observing behaviour in an ordinary setting, without researcher interference

Question 11

what are a case study/method and some of its disadvantages

Answer 11

• the deep study of an individual or small group in hopes of revealing universal principles
• research usually on unusual phenomena
• DESCRIBES behaviour (experimentation explains it) what cant always be studied in a lab

disadvantage: large time commitment, the small number group is NOT representative of the population as a whole (experimentation can be used to apply what learned to the larger population(

Question 12

correlational research

Answer 12

requires at least two variables to be measured so that one variable can be used to predict the other
- NO variable manipulation by researcher

Question 13

disadvantages of experimentation

Answer 13

some variables cant be manipulated without violating ethical standards:
- informed consent
safety
- privacy of data
benefit to society
- a benefit to participants

Question 14

demand characteristics

Answer 14

settings that cause subjects to behave as they think someone else (eg. experimenter) wants or expects

Question 15

how to avoid demand characteristics?

Answer 15

1. naturalistic observation
2. if you cant do naturalistic observation:

privacy and control

• gathering info privately or anonymously
• measuring behaviour that people are unable or unlikely to control (such as dilation of pupils to tell whether or not you’re lying)

unawareness
- make sure ppl are unaware of the true purpose of the observation

Question 16

how can you avoid observer/experimenter bias

Answer 16

double-blind design: neither the researcher not the participant knows how the participants are expected to behave
- avoids the placebo effect

Question 17

normal distribution

Answer 17

where the most measurements of a frequency distribution are concentrated in the middle
mean = median =mode

Question 18

what are the descriptive stats of central tendency?

Answer 18

mode: the value of the most frequently observed measurement.
mean: the avg value of all the measurements.
median: the value in the middle

Question 19

descriptive stats:

Answer 19

s calculated from a distribution of scores, indicating the central tendency (avg) and the variability; brief summary statements aBOUT ESSENTIAL INFORMATION FROM A frequency DISTRIBUTION

• indicated whether or not experimental treatment changed performance

Question 20

third-variable (confounding variable)?

Answer 20

correlation between two variables cannot be taken as evidence of a causal relationship between them because a third variable might be causing them both

Question 21

the third-variable (confounding variable) problem?

Answer 21

correlation between two variables cannot be taken as evidence of a causal relationship between them because a third variable might be causing them both

***why correlation DOES NOT = causation

Question 22

what’s a solution to the third-variable problem?

Answer 22

1. experimentation: eliminating or controlling other possible causes, thus creating a a set of conditions that differ in ONLY ONE WAY. Experimentation finds causal relationships
   - via manipulation: a technique for determining the causal power of a variable by actively changing its value
2. randomization

Question 23

a good detector has ____ and _____

Answer 23

power and reliability

If a person smiles a bit more often on Tuesday than on Wednesday, a powerful smile-detector will detect different amounts of smiling on those two days. If a person smiles exactly as much on Wednesday as she did on Tuesday, then a reliable smile-detector will detect identical amounts of smiling on those two days. A good detector detects differences or changes in the magnitude of a property when they do exist (power), but not when they don’t (reliability).

Question 24

negatively skewed data leans to the….

Answer 24

right

Question 25

positively skewed data leans to the

Answer 25

left

Question 26

standard deviation

Answer 26

how each of the measurements in a frequency distribution differs from the mean; involves finding the distance between each individual score and the mean, and then computing the average of these distances. - indicate how many exceptions there are. - when the standard deviation gets larger = the more the two groups overlap and the smaller (weaker) the effect size and vice versa (smaller SD = less overlap = stronger effect size)

Question 27

if the distribution has extreme scores that pull the mean in their direction, researchers prefer to use the:

Answer 27

median

Question 28

What's a limitation of naturalistic observation?

Answer 28

** describes behaviours but cannot explain why they occur which is why we need experimentation

Question 29

frequency distribution

Answer 29

a graphic representation showing the numner of times in which the measurement of a property takes on each of its possible values

Question 30

sample

Answer 30

a partial collection of people or animals or things drawn from a population (n); representative of the population

Question 31

population

Answer 31

a complete collection of people (N)

Question 32

correlation

Answer 32

when variations in the values of one variable are synchronized with variations in the value of the other

Question 33

what is direction (r) in a correlation?

Answer 33

the direction of the correlation = positive or negative; - positive = "more is more"; ppl have a lot of one variable also have a lot of the other; r=1 ie: more health is associsated with more wealth - negative = "more is less"; r= -1 ie: more health is associated with less poverty *the sign associated wit r

Question 34

variability

Answer 34

the extent to which the measurements differ from each other (range, standard deviation, etc)

Question 35

correlation coefficient (r) + scale

Answer 35

mathematical measure that shows both strength and direction of a correlation (how much of an impact the variables have on one another ie: 0.75 or -0.75 = strong correlation vs -.05 or -0.10) scale: weak = 0.10, medium = 0.30, strong > or = 0.50

Question 36

what is strength (r) in a correlation?

Answer 36

the absolute value of r, thus tells you the amount of exceptions to the correlation/rule

Question 37

r= 1

Answer 37

perfect positive correlation (positive direction) every time the value of a variable increases (decreases) by a certain amount, the value of the second variable (decreases) increases by a certain amount.

Question 38

r= - 1

Answer 38

perfect negative correlation every time the value of a variable increases by a certain amount, the value of the second variable decreases by a certain amount.

Question 39

r = 0

Answer 39

no correlation every time the value of a variable increases by a certain amount, the value of the second variable NEITHER increases nor decreases by a certain amount.

Question 40

imperfect positive correlation

Answer 40

most common in the real world. there are always exceptions which means r will be somewhere between 0-1 and 0- -1 - few exceptions=r is closer to 1, more exceptions = r is closer to -1

Question 41

imperfect positive correlation

Answer 41

most common in the real world. there are always exceptions which means r will be somewhere between 0-1 and 0- -1 - few exceptions=r is closer to 1 (stronger correlation), more exceptions = r is closer to -1 (weaker correlation)

Question 42

natural correlations

Answer 42

correlations we observe in the world around us | ie: height and weight, sleep and memory, etc

Question 43

techniques used in experimentation?

Answer 43

manipulation: a technique for determining the causal power of a variable by actively changing its value random assignment: avoids bias towards a specific type of person

Question 44

steps of the experimentation technique

Answer 44

1. MANIPULATE: manipulate the independant variable - creates at least 2 conditions 2. MEASURE: measure the dependant variable ("depends "on the participants) 3. COMPARE: compare the variable of the variable in one condition and the value of the variable in the other condition - if values differ on avg, then the independent CAUSED changes to the DEPENDANT

Question 45

self-selection

Answer 45

problem that occurs when anything about a participant determines whether they will be included in the experiment or control group; a type of bias that can arise when study participants choose their own treatment conditions, rather than being randomly assigned

Question 46

random assignment

Answer 46

a procedure that allows chance (ie coin flipping) to assign participants to the experimental/control group **used in experimental/causation studies

Question 47

can random assignment fail? is so, how?

Answer 47

yes. assortment of participants into group appears biased/not 50/50 split of each "type" of participant in each condition. - calculate the STATISTICAL SIGNIFICANCE of the data. if p>5%, the results are NOT statistically significant and random assignment failed, p<5%, then results are statistically significant

Question 48

statistical significane

Answer 48

calculates how likely is it that the sample’s result came from a population in which there is no relationship (if the null hypothesis were true); determined by calculating the probabilities that random assignment has failed, there inferential statistics - assess the probability that the effect size calculated from one just one sample came from a larger population with certain characteristics - statistically significant results: p<0.05 * ** a result can be statistically significant but not necessarily important

Question 49

internal validity

Answer 49

an attribute of an experiment that allows it to establish causal relationships; everything INSIDE the experiment is working exactly as it should - how well it can rule out alternative explanations * *conclusions drawn are restricted to the

Question 50

external validity

Answer 50

when the variables in an experiment have been defined in a normal, typical, or realistic way (variables are representative of the real world); how well the results can generalize to a population of interest.

Question 51

type I error

Answer 51

error that occurs when researchers conclude that there is a causal relationship between two variables when in fact there is not (a false positive conclusion)

Question 52

type II error

Answer 52

error that occurs when researchers conclude that there is not a causal relationship between variables when in fact there is (a false negative conclusion)

Question 53

cross-sectional study

Answer 53

a study in which people of different ages are compared with one another at the same time - get a snapshot of people at the same time - more feasible alternative to longitudinal study

Question 54

longitudinal study

Answer 54

research in which the same people are restudied and retested over a long period of time - useful for developmental psychology (how behaviours, personality, etc change over time)

Question 55

disadvantages to longitudinal research

Answer 55

takes alot of money and time | difficult to retain research participants (some move away, pass away, etc)

Question 56

disadvantages of the cross-sectional studies

Answer 56

cohort effect: the way ppl are affected by their coming from a particular time in history (50year old in 1950s vs 2010)

Question 57

central tendency

Answer 57

the typical, or representative score in a distribution, often referred to as the "average"

Question 58

inferential statistics

Answer 58

use sample results to infer what is true about the broader population; #s that are calculated from a distribution of scores to provide evidence supporting or opposing a hypothesis (indicates the level of confidence in results)

Question 59

experimental group

Answer 59

participants in an experiment who receive the treatment level of the independent variable

Question 60

control group

Answer 60

participants in an experiment who do not receive the treatment

Question 61

null hypothesis significance testing (NHST)

Answer 61

an approach to evaluating research results that compared the observed outcome to what would be expected if the null hypothesis is true = p>0.05 or p<0.05 when the sample’s result (or one more extreme) would happen less than 5 percent of the time if the null hypothesis is true = reject null and say the research is statistically significant

Question 62

null hypothesis

Answer 62

no difference between the variables in a population | ie, no difference between the experimental group and the control group

Question 63

effect size ("d")

Answer 63

the magnitude of the relationship between manipulated or measured variables. - the absolute value of the size of r captures the effect size = r of 0.30 = medium effect size, r of 0.80 = strong effect size. a calculated number that indicates the size of a difference between two values; not affected by the sample size "d" is used to represent the statistical calculation of the effect size

Question 64

confidence interval

Answer 64

a range of scores calculated such that there is a specific probability (usually 0.95) that the value of interest (such as the estimated mean of the population) actually falls within that range - if the confidence intervals don't overlap = indicates that differences between the two groups are reliably different

Question 65

p-level

Answer 65

probability of finding a difference that is equal to or greater than what was actually measured, assuming the null hypothesis is true the probability/odds that the results would have occurred if the random assignment had failed

Question 66

reliability

Answer 66

ability to detect the absence of differences or changes in the magnitude of a property - findings can be consistently repeated

Question 67

3 criteria for causation (making casual claims)

Answer 67

1. must show correlation between the variables 2. establish the temporal precedence of the causal variable (one variable must come before the other) 3. rule out alternative explanations (third-variable) temporal precedence: establishing that the cause (i.e., independent variable) occurs before the effect (i.e., outcome)

Question 68

convenience vs random sampling

Answer 68

Random: ie. random sampling because it used a random-digit dialer to select who was going to be in the study sample. Convenience: - there was no manipulated variable in the study, so there was no random assignment. - a convenient group/choice given the study's circumstances ( ie. psyc class in uni vs random ample of another population) - whoever is there for observers to observe at that time

Question 69

note

Answer 69

Each method has its own strengths and weaknesses, so each one is better for answering some questions than others.

Question 70

experimental research

Answer 70

- testing whether one variable causes another; establishes causal relationship between variables - independent (manipulated); dependant (control group) - ONE OF THE VARIABLES MUST BE MANIPULATED - uses random assignment - determines causation

Question 71

descriptive research

Answer 71

about a single variable and not about a relationship - Most descriptive studies try to provide concise summaries of one variable at a time. - often based on self reports - usually expressed as percentages or frequencies

Question 72

what happens when you add a data point lower than the mean

Answer 72

, the mean decreases but the standard deviation increases.

Question 73

what happens when you add a data point higher than the mean

Answer 73

both the mean and the standard deviation increase

Question 74

how are mean and standard deviation similar?

Answer 74

both examples of descriptive statistics; Both means and standard deviations summarize participants’ different responses.

Question 75

how are the r and d statistic similar?

Answer 75

Both r (strength) and d (effect size) indicate the strength of the relationship between two variables.

Question 76

TRUE OR FALSE: a low p-value means the hypothesis is true

Answer 76

FALSE it just means the data are unlikely to occur under the null hypothesis - significant result

Question 77

TRUE OR FALSE: a high p-value means that the hypothesis is false/should be abandoned

Answer 77

FALSE it just means that the data are likely to occur under the null hypothesis - non-significant result

Question 78

meta-analysis

Answer 78

- provides a quantitative estimate of the effect size in the previous body of research - demonstrate research replication

Question 79

Saying that a finding is “statistically significant” means that it

Answer 79

is unlikely to have happened by chance if the null hypothesis were true

Question 80

TRUE or FALSE: every study must have a strong external validity, or the results will not be considered reliable

Answer 80

Many studies sacrifice external validity for internal validity; studies that make this sacrifice are sure not to make extensive claims about their generalizability.

Question 81

TRUE or FALSE: every study has to reflect the global population

Answer 81

Not every study has to reflect the global population; rather, the participants used in a study should be parallel to the specific types of people that the study aims to analyze.

Question 82

idea

Answer 82

unorganized principles or thoughts about social behaviour

Question 83

what's a variable?

Answer 83

event, situation, behaviour, or characteristics that take on more than one value

Question 84

conceptual variable definition:

Answer 84

concept or meaning of a variable (what is it)? ie: age is conceptual, operationalized to be days since birth (for example) exercise (conceptual), operationalized (ie: miles run per month)

Question 85

predictions

Answer 85

- more specific than the hypothesis | - -- >uses operational definitions of variable

Question 86

placebo

Answer 86

A placebo is a sham substance or treatment which is designed to have no therapeutic value.