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PYSC*2360 (stats) > Unit 4 Measurement & Sampling > Flashcards

Unit 4 Measurement & Sampling Flashcards

(62 cards)

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1
Q

Research

A

investigation and study of materials and sources in order to establish facts and reach new conclusions

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2
Q

Role of quantitative methods

A

applying: numbers, equations, formulas, mathematical techniques, and graphical analyses

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3
Q

what is the purpose of quantitive methods

A

they provide a objective approach

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4
Q

what are the 4 stages of a research study

A

1) research question (theory)
2) research design (hypotheses)
3) findings/ answers (observations)
4) share/ publish findings (empirical generalizations)

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5
Q

difference between population and sample

A

population: entire group of individuals to which a law of nature applies

sample: a smaller subset of a population that is intended to represent the population

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6
Q

what are examples of a population?

A
  • all university students in Canada
  • all Canadian’s over the age of 65
  • all Canadians suffering from arthritis
    -all people with cardiovascular disease
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7
Q

define “parameters”

A

numbers that characterize the population

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8
Q

what does this symbol represent “μ” mean

A

mean

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9
Q

what does this symbol represent “σ” or “s” mean

A

standard deviation

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10
Q

what does this symbol represent “ρ” mean

A

correlation coheficont

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11
Q

define “statistics”

A

numbers that characterize the sample

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12
Q

random sample

A

individuals that the sample are randomly selected from the population (theory)

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13
Q

what is the issue with random sampling

A

may not produce a representative sample [it is difficult to randomly select people to study]

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14
Q

data

A

scores on variables (or info expressed) - quantitatively

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15
Q

variables

A

traits that can change values from case to case (gender, age, religion)

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16
Q

cases

A

entities from which data are gathered (people, business, cities, countries)
- ex) university students studied would be a case

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17
Q

what are the 2 general approaches to stats application?

A

DESCRIPTIVE + INFERENTIAL

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18
Q

descriptive application

A

describing basic characteristics of a person or a group

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19
Q

what are the terms for…
1) summarize 1 variable
2) summarize relationship between 2 variables
3) summarize relationship between 3+

A

1) univariate
2) bivariate
3) multivariate

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20
Q

inferential application

A

“inferring” the results of an analysis to a larger population (hypothesis testing)

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21
Q

what makes inferential application different than descriptive?

A

inferential establishes a cause and effect relationship

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22
Q

discrete variables

A

measured in units that cannot be divided (contain gaps)
- ex) number of people per house [no 1.5]

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23
Q

continuous variables

A

measured in a unit that can be subdivided infinitely
-ex) age 2.5

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24
Q

dichotomous

A

only 2 possible outcomes (male, female)

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25
dependent variable
measuring an outcome
26
what are (3) examples of a dependent variable
- results of a federal election -number of SARs infections in Ontario -median household income
27
independent variable
a factor influencing an outcome (dependent variable)
28
what are (3) examples of a independent variable
- political fundraising -residential location (SARS) - level of education (income)
29
precision
the exactness of a measure ex) measuring heart rate ex) surveys / questionnaires
30
nominal scale
identification scores - does not measure amount or value
31
examples of nominal scale
- yes or no question - sex at birth (female) (male) - gender
32
what is the criteria for a nominal scale (3)
1) mutually exclusive (cant pick more than 1 category) 2) exhaustive- category must exist for every possible score 3) homogenous - should include cases that are comparable
33
ordinal scale
categorical scale with a natural order (possible between items)
34
example of ordinal scale
opinion surveys (agree, strongly agree, etc) LIKERT scale
35
interval scale
describes an actual quantity (numerical values) - NO TRUE ZERO
36
example of interval scale
temperature (0 does not mean no temp)
37
ratio scale (highest level)
scores represent the true "amount" of the variable that is present (true zero)
38
example of ratio scale
employee salaries OR age
39
difference between parameter and statistic
parameter (assumed) POPU statistic (calcuated) SAMPLE
40
what does this symbol represent "σ^2" or "s^2" mean
variance
41
simple random samping
conceptually, represents the population
42
table of random numbers
all digits have an equal chance to occur
43
sampling with replacement
After 1 unit is selected, it has the equal chance of being selected again [marble kept in bag]
44
Sampling without replacement
After 1 unit is selected, it has no further chance of being selected [marble taken out of bag]
45
stratified random sampling
Separates the population into different categories and randomly selects a sample from each category. (sub groups)
46
disproportional sampling
To over-sample or under-sample certain strata to achieve specific research objectives, even if they don't reflect their proportions in the population.
47
what are the 3 steps to... cluster sampling
1) Divide the population into groups based on certain characteristics. 2) Randomly choose a set number of groups (clusters). 3) Randomly pick a set number of people from each chosen group.
48
conveience sample
Participants chosen based on availability - BIAS of self-selection
49
quota sampling
stopping the selection once an adequate number is achieved (meeting quota)
50
purposive sampling
researcher "hand-picks" participants - BIAS
51
snowball sampling
gaining participants from "chain-referral"
52
self-reports
researcher participants provide info directly - ex) surveys
53
what are ADVANTAGES and DISADVANTAGES of self-reports
ADVANTAGE: first-hand experience for participants (convenient) DISADVANTAGE: Social desirability concerns: The tendency for respondents to provide answers that make them look good. - PERCEPTION BIAS
54
Potential demand characteristics
a cue that makes participants potentially aware of what the experimenter expects / wants them to say - PARTICPANT BIAS
55
Possible retrospective bias
when participants view / interpret past events in an inaccurate way
56
how do you deal with bias?
always address how reliability and validity may have been affected (will never be perfect)
57
behavioural trace
a measure that relies on evidence left behind by a participant who is no longer present (ex- journal)
58
behavioural observation
measure that relies on directly seeing or observer behaviour
59
behavioural choice
measure in which participants purposefully select from several options
60
Participant reactivity
participants act differently or unnaturally because they know someone is watching them
61
unobtrusive measure's
strategies that allow for observations and assessment without the participants awareness (Requires ethics approval)
62
ceiling effect
in which participants would tend to provide responses at the top end of the scale (or floor- vice versa)

PYSC*2360 (stats) (4 decks)

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