Final Exam Flashcards
(115 cards)
1
Q
Tenacity
A
- Superstition/habit
- Info may not be accurate/No method for correcting
2
Q
Authority
A
- Find answers by seeking out an authority on the subject
- Quickest/easiest way to obtain answers
- (doctors, parents, lawyers)
- not all “experts” are experts, personal opinion/biases
3
Q
Rationalism
A
- Logical reasoning
- Begin with set of known facts/assumptions
- Even if logic is sound, the conclusion may not be true
4
Q
Empiricism
A
- Direct observation or personal experience
- Too much confidence in observations
- Perceptions can drastically alter by prior knowledge, expectations, feelings, or beliefs
5
Q
Inductive vs. deductive logic
A
- Inductive: small set of specific observations used for forming a general statement about a larger set of possible events.
- Deductive: General statement or set of statements as the basis for reaching a conclusion about specific examples
6
Q
Steps in the research process
A
- Observe
- General Hypothesis
- Research Hypothesis
- Evaluate
- Support, refute, or refine
7
Q
Applied research
A
Research studies that are intended to answer practical questions or solve practical problems.
8
Q
Basic research
A
Research studies that are intended to answer theoretical questions or gather knowledge simply for the sake of new knowledge.
9
Q
Testable hypothesis
A
- possible to observe and measure all variables involved
10
Q
Refutable hypothesis
A
- contrary results must be possible
- in other words, the hypothesis must be falsifiable
11
Q
Informed consent
A
The ethical principle requiring the investigator to provide all available information about a study so that a participant can make a rational, informed decision regarding whether to participate in the study.
12
Q
Active deception
A
- misleading participants about the specific purpose of the study.
13
Q
Passive deception
A
- information is withheld from a participant.
14
Q
Anonymity
A
the condition of being anonymous.
15
Q
Confidentiality
A
the state of keeping or being kept secret or private.
16
Q
Concurrent validity
A
The type of validity demonstrated when scores obtained from a new measure are directly related to scores obtained from more established measure of the same variable.
17
Q
Divergent validity
A
- Two different methods to measure two different constructs.
- Convergent validity must be shown for each of the two constructs.
- There should be little to no relationship between the scores obtained for the two different constructs when they are measured by the same method.
18
Q
Convergent validity
A
- Strong relationship between the scores obtained from two different methods of measuring the same construct.
19
Q
Ratio
A
- The scale must have a true 0 point and ratios must be calculable
- E.g., height, weight, reaction time
20
Q
Interval
A
- Scale must have equally-spaced units (distance along intervals equal)
- Zero is just a point on the scale (not absence of the construct)
- E.g., temperature, clock hour, psychological sclaes
- 1(strongly disagree) - 7(strongly agree)
21
Q
Predictive validity
A
- Does my measure accurately predict behaviour?
22
Q
Operational definitions
A
- A procedure for indirectly measuring and defining a variable that cannot be observed or measured directly.
- Specifies a measurement procedure (a set of operations) for measuring an external, observable behaviour and uses the resulting measurements as a definition and a measurement of the hypothetical construct.
23
Q
Mean
A
A measure of central tendency obtained by adding the individual scores, then dividing the sum of the number of scores. The mean is the arithmetic average.
24
Q
Test-retest
A
Successive measurements
25
Inter-rater
Simultaneous measurements
26
Split-half
Internal consistency
27
Developmental research design (Non-experimental & Quasi-experimental)
- Cross-sectional developmental
| - Longitudinal developmental research design
28
Question types
- Open-ended
| - Rating scale
29
Ordinal
- Order of cases important
- Data arranged in a rank position
- Can determine direction, but not magnitude, of differences; distances b/w ranks NOT equal
- Ex; Sales rep position (junior, middle, senior)
30
Nominal
- Not really a "scale" at all
- Categories of people, things; anything that can be grouped, and groups have no rank order
- No one can exist "between categories" (they are mutually exclusive)
- E.g., place of birth, occupation (when no status difference), colour preference, favourite TV show, Teams A vs. B vs. C etc.
31
Sample
relatively smaller group of individuals who participate in the study
32
Simple random sampling (Random)
- Randomly select participants from list containing total population
- Each individual has equal and independent chance of selection
33
Systematic sampling (Random)
- Select every nth participant from list containing total population after random start
34
Stratified random sampling (Random)
- Divide population into subgroups and randomly select equal numbers from each subgroup
35
Proportionate stratified random sampling (Random)
- Divide population into subgroups and randomly select from each subgroup so proportions in sample correspond to proportions in population
36
Cluster sampling (Random)
- Randomly select clusters from a list of all the clusters in the population
37
Convenience sampling (Nonrandom)
- Select individual participants who are easy to get
38
Quota sampling (Nonrandom)
- Identify subgroups to be included, then establish quotas for individuals to be selected through convenience
39
Range
Range = maximum value - minimum value
40
Standard deviation
- Used whenever mean is used as measure of central tendency
- Measures distance between each score and the mean
- To calculate, you need to first calculate the variance.
41
Variance
- Average squared distance from the mean.
42
Quasi-experimental (Strategies)
- Attempts to answer cause-effect questions about relationship between two variables, but answers tend to be ambiguous.
43
What is a z-score?
- A z-score is the number of standard deviations a score is from the mean.
- Any raw score can be turned into a z-score.
- When ALL of your raw scores are turned into z-scores, the mean of those scores will be 0, and the SD will equal 1.
- Two uses of the z-score:
1. Assessing the relative position of a score in a distribution
2. Assessing the probability of attaining a score or mean at or below, or higher, than that score or mean in the population.
44
Experimenter bias (Threats to validity)
- the findings of the of a study are influenced by the experimenter's expectations or personal beliefs about the study's outcome.
45
Reactivity (Threats to validity)
- participants modify their natural behaviour in response to the fact that they are aware they are being studied
- behaviour can change by being overly cooperative or defensive/uncooperative.
46
Confounding variable (Threats to validity)
- extraneous variable (usually unmonitored)
- changes systematically along with the two variables being studied.
- alternative explanation for observed relationships between the two variables.
47
Assignment bias (Threats to validity)
Occurs when the process used to assign different participants to different treatments produces groups of individuals with noticeably different characteristics
48
Selection bias (Threats to validity)
- Sampling procedure favours the selection of some individuals over others.
- If the sample doesn't accurately represent the population, the results will not generalize to the population
49
External validity
- The extent to which the results obtained in a research study can hold true outside that specific study.
50
Internal validity
- Changes in one variable are followed by changes in another variable and no other variable provides an alternative explanation for the results.
51
Manipulation
Manipulate one variable to create two different treatment conditions.
52
Measure
Measure a second variable to obtain a set of scores in each treatment condition
53
Comparison
Compare the scores in treatment A with the scores in treatment B
54
Control
- The second distinguishing characteristic of an experiment is control of extraneous variables
- Ensure observed relationship is not contaminated by the influence of other variables.
55
Threats to validity (experimental)
- Assignment bias (different participants to different treatment groups with noticeably different characteristics)
56
Mitigating threats to validity (experimental)
Holding variables constant:
- making variables the same for every observation
- environmental variables: standardize the environment and procedures
- individual differences variables: hold demographic variables constant
Matching:
- balance variables in each treatment condition
Random assignment:
- passive control technique
- disrupting systematic relation
- unpredictable and unbiased procedure to distribute different values of each extraneous variable across the treatment conditions
57
Manipulation check
- included in the study to measure whether the independent variable had the intended effect on the participant
58
Placebo effect
Believed to be psychosomatic: the mind (psyche) has an effect on the body (somatic)
- the individual thinking/believing it's effective, causes a response to the medication
59
What is a between subjects design?
- obtain each of the different groups of scores from a separate group of participants
- comparing different groups of individuals
- individual scores
60
Between subjects design advantages
- Each individual score is independent from the other scores
| - Can be used for a wide variety of research questions
61
Between subjects design disadvantages
- Require a relatively large number of participants
| - Individual differences
62
Specific threats to validity (Between subjects design)
- Differential attrition
- Communication
- Differential attrition: when participants withdrawal from a study before it's completed
- Communication: when participants from different conditions talk to each other...
(Diffusion) - treatment effect spread between groups
(Compensatory equalization) - untreated groups demand equal treatment
(Compensatory rivalry) - untreated group works hard to show they can perform just as good
(Resentful demoralization) - untreated group becomes less productive and motivated
63
What does the t-statistic represent? (Between subjects design)
measures the size of the difference relative to the variation in your sample data
64
What is a within-subjects design?
- uses a single group of participants and tests or observes each individual in each treatment group
65
Order effects/testing effects (Within-subjects design)
Factors related to experience within the research study.
66
Carryover effects (Within-subjects design)
Changes in a participant that can be attributed directly to lingering aftereffects of earlier treatments.
- Drug that lingers in system
- Skills that can't be forgotten
67
Progressive error (Within-subjects design)
Changes in participant that can be attributed to general experience rather than specific treatment.
- Practice effects (improvement in performance)
- Fatigue effects (decline in performance)
68
History (Within-subjects design)
Environmental events that change outside the study.
69
Maturation (Within-subjects design)
Physiological or psychological characteristics in participants
70
Instrumentation (Within-subjects design)
Measurement instrument may change (terms may be obsolete)
71
Regression toward the mean (Within-subjects design)
Extreme scores become less extreme due to statistical regression.
72
Counterbalancing (Within-subjects design)
The process of matching treatment with respect to time.
73
Matched-subjects design (Within-subjects design)
An experiment in which different groups of people are exposed to the different manipulations of the IV, but within the separate groups, people are matched and compared with a partner who is very similar on an important participant variable.
- An ideal "matched pair" would be identical twins.
74
Basic assumptions (Dependent samples t-test)
- Dependent samples
- The dependent variable involves an interval or ratio scale.
- The samples come from populations with normal distributions.
- Homogeneity of variance (variances of samples approx. equal)
- Compare 2 treatment conditions.
75
State the null & alternative hypothesis (Dependent samples t-test)
- Null: The IV has no effect on the DV
| - Alternative: The IV has an effect on the DV
76
Degrees of freedom (Dependent samples t-test)
(df) number of pairs minus 1
77
Question types (Correlational/Descriptive Research Strategy)
Open-ended:
- Introduce a topic to participants and let them answer in their own words. (Describe your ideal date?)
Rating scale:
- participants respond by selecting numerical value on a predetermined scale (Likert scale)
Restricted:
- multiple choice
78
Correlational research strategy
| - Strengths/Weaknesses
- to examine/describe the associations and relationships between variables.
- data consists of two or more measurements, one for each of the variables being examined.
- high external validity, low internal validity
79
Debriefing
A post-experimental explanation of the purpose of the study. A debriefing is given after a participant completes a study, especially if deception was used.
80
Fraud
The explicit efforts of a researcher to falsify and misrepresent data. Fraud is unethical.
81
Plagiarism
Presenting someone else's ideas or words as one's own. Plagiarism is unethical.
82
Face Validity
An unscientific form of validity that concerns whether a measure superficially appears to measure what it claims to measure.
83
Measurement sensitivity
an absolute quantity, the smallest absolute amount of change that can be detected by a measurement.
84
Floor effect
when measurements of the dependent variable result in very low scores on the measurement scale.
85
Ceiling effect
- when a variable is no longer measured or estimated at a certain point. (65 and over)
- the level at which an independent variable no longer has an effect on a dependent variable
86
How to calculate a z-score
- A z-score is the number of standard deviations a score is from the mean
Uses: 1. Assessing the relative position of a score in a distribution. 2. Assessing the probability of attaining a score or mean at or below, or higher, than that score or mean in the population
87
Target population
defined by researcher's specific interests
88
Accessible population
Portion of population who are accessible to be recruited for the study
89
Descriptive (Research strategies)
Intended to answer questions about the current state of individual variables for a specific group of individuals. (Describe specific characteristics of a specific group of individuals)
90
Experimental (Research strategies)
- Intended to answer cause-effect questions about the relationship between variables
- rigorous control to help ensure an unambiguous demonstration of the cause-effect relationship
91
Quasi-experimental (Research strategies)
- Attempts to answer cause-effect questions about relationship between two variables, but answers tend to be ambiguous.
92
Non-experimental (Research strategies)
- Demonstrates relationship between variables without explaining relationship.
- Does not use rigour and control or produce cause-effect explanations.
93
State the null hypothesis & alternative hypothesis (Independent samples t-test)
- There is no effect, no change, no relationship
- Any differences between the sample and the population occurred due to chance
vs.
- The hypothesis of our predicted effect (Corresponds to Research Hypothesis)
94
Positive Relationship (Correlational/Descriptive Research Strategy)
Variables change in the same direction
95
Negative relationship (Correlational/Descriptive Research Strategy)
Variables change in opposite directions
96
Third variable
A type of confounding in which a third variable leads to a mistaken causal relationship between two others.
97
Directionality
- the word "directionality" refers to directionality of inference. The program can either have a forward or backward direction.
98
Control group
The group in an experiment or study that does not receive treatment by the researchers and is then used as a benchmark to measure how the other tested subjects do.
99
Placebo control group
A separate control group receives a sham "placebo" treatment which is specifically designed to have no real effect.
100
Basic assumptions (Independent samples t-test)
- 2 groups
- Populations from which samples are drawn are normally distributed
- Observations within each sample must be independent.
- Ratio or interval measurement for DV
- Homogeneity of variance (variances of samples approximately equal)
101
Differential research design
- Sometimes, individual differences are the primary interest (gender, age, IQ, race, etc)
- Researcher creates separate groups of participants based on individual difference of interest, then compares these groups.
- No manipulation of an independent variable and no control over the assignment of participants to groups - not a true experiment.
102
Degrees of freedom (Independent samples t-test)
df = (n - 1) + (n-1)
103
Critical-T (Independent samples t-test)
- Compares the means of two independent groups in order to determine whether there is statistical evidence that the associated population means are significantly different.
104
- Longitudinal developmental research design
An observational research method in which data is gathered for the same subjects repeatedly over a period of time.
105
Critical T (Dependent samples t-test)
- Used to compare two means for situations in which every participant is in both samples
106
Response sets (Correlational/Descriptive Research Strategy)
- Whenever questions in a series have the same choices for responding, participants tend to use the same choices for responding.
- To deal with this, include positive and negative statements, including alternate phrasing of same item.
107
Pretest-posttest non-equivalent control group design
- Stronger version of nonequivalent control group design
1. Observe/measure both groups.
2. Apply treatment to one group.
3. Observe/measure both groups again.
- Adding the pretest measure allows researchers to address assignment bias.
- O X O (treatment group)
- O O (non-equivalent control group)
108
One-group pretest-posttest design
- The simplest version of the pre-post design consists of one observation for each participant made before the treatment or event and one observation made after it.
- Non-experimental - cannot make any conclusions about cause-and-effect.
- O X O
109
Time-series
- A series of observations for each participant before and after a treatment or event.
- The intervening treatment may or may not be manipulated by the researcher.
- O O O X O O O
110
Developmental research Design
- Non-experimental designs that can be used to study changes in behaviour that relate to age.
- Cross-sectional
- Longitudinal
111
- Cross-sectional developmental research design
- Used to examine changes in similar groups at different ages.
- Between-subjects design that uses separate group of participants for each of the ages being compared.
- Dependent variable is measured for the individuals in each group and the groups are compared to determine whether there are age differences.
112
- Longitudinal developmental research design
- An observational research method in which data is gathered for the same subjects repeatedly over a period of time.
- Within-subjects nonexperimental design - a one-group pretest-posttest design.
113
Predictor variable (Correlational/Descriptive Research Strategy)
Comparable to an independent variable and is used to predict an outcome (the criterion variable)
114
Criterion variable (Correlational/Descriptive Research Strategy)
Another name for a dependent variable only used in non-experimental situations.
115
Non-response bias (Correlational/Descriptive Research Strategy)
Nonresponse bias is the bias that results when respondents differ in meaningful ways from nonrespondents.
