2.1 Flashcards

1
Q

format for thesis questions

A

what is the relationship between xyz, how is xyz affected by abc

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2
Q

analyzing thesis question

A

what are main variables, statistically measurable, enough accessible data, social relevance

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3
Q

population

A

group being studied

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4
Q

sample

A

selection of individuals from population

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5
Q

inference

A

prediction about population based on sample

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6
Q

cross sectional study

A

different groups at same time, specific timeframe, wide range of individuals

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7
Q

longitudinal study

A

small group over a long period of time

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8
Q

time series data

A

data accumulated over a long period of time

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9
Q

qualitative data

A

not measurable numerically, categorical, multiple choice answers

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10
Q

qualitative data

A

bar graph circle graph pictographs

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11
Q

quantitative data

A

numerical, discrete or continuous

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12
Q

quantitative discrete

A

bar, histogram (over long range)

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13
Q

quantitative continuous

A

box and whisker, histogram

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14
Q

simple random sampling

A

fast/easy, may not be representative of pop, e.g. pick names out of hat

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15
Q

systematic random sampling

A

random starting point, then select every nth object, n is sample interval = pop size/sample size, population spread

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16
Q

stratified random sampling

A

pop broken up into groups, then random proportional sample from each

17
Q

cluster random sampling

A

population broken up into groups, then random sample of groups (all objects)

18
Q

multi stage random sampling

A

population broken up into groups, then random sample of groups (random sample of objects)

19
Q

destructive random sampling

A

samples used up by testing process, usually for quality control

20
Q

factors that affect reliability

A

variability of pop, sampling method, degree of precision

21
Q

non random sampling

A

convenience sampling, volunteers

22
Q

types of questions

A

open, closed

23
Q

open questions

A

opinion/list, sometimes difficult to interpret

24
Q

closed

A

information, checklist, ranking, rating

25
good questions
simple, relevant, specific, readable
26
bad questions
jargon, abbreviations, negatives, leading respondents, insensitive
27
types of data
primary, secondary, administrative
28
types of bias
sampling, non-response, household, response
29
sampling bias
sample doesn't represent population, inappropriate sampling technique or sample size not large enough
30
non-response bias
results are influenced because surveys are not returned
31
household bias
type of respondent is over represented because diff sized groups polled equally
32
response bias
factors in sampling method that influence the result, poor design of questionnaire, leading questions