Data Collection Flashcards

1
Q

Survey

A

Method used for observing data that cannot easily be observed. Sample of the population.

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2
Q

Cross-Sectional Survey

A

At a single point in time

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3
Q

Longitudinal Survey

A

Over a period of time

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4
Q

Written Survey

A

Good for broad audience, less than 20% response rate.

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5
Q

Group Survey

A

Specific target population, small sample size, quick response rate.

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6
Q

Drop-Off Survey

A

Smaller sample size, lower response rate, expensive.

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7
Q

Oral Survey

A

1) Phone - good for yes/no questions and follow up. 2) In-person.

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8
Q

Online Survey

A

Inexpensive, quick response time.

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9
Q

Sample

A

Part of a population.

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10
Q

Probability Sample

A

Used for direct correlation between a sample and the larger population - can draw direct conclusions from this type.

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11
Q

Random

A

(Probability) Everyone has equal chance of being selected for survey.

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12
Q

Stratified

A

(Probability) Population is divided and then sampled.

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13
Q

Cluster

A

(Probability) Specific target group sampled from.

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14
Q

Non-Probability

A

No precise connection between sample and population

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15
Q

Volunteer

A

(Non-Probability) Self-selected respondents

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16
Q

Convenience

A

(Non-Probability) Individuals readily available

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17
Q

Snowball

A

(Non-Probability) Interviewee suggests others to be other potential respondents

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18
Q

VGI

A

(Non-Probability) Respondents enter information on web map

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19
Q

Nominal Data

A

Categories. Mutually exclusive groups (have no bearing on each other)

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20
Q

Ordinal Data

A

Ranked. Order matters but not the difference between the values (scales)

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21
Q

Interval Data

A

Continuous. Order matters and so does the difference between the vaules (temperature)

22
Q

Ratio

A

Absolute and relative differences have meaning (distance)

23
Q

Variables: continuous v. discrete

A

Continuous: infinite (can be + or -)
Discrete: finite (+ or binary)

24
Q

Population

A

Totality of some entity

25
Sample
Subset of population
26
Descriptive satistics
Applying mean, median, range, mode to describe a population
27
Inferential statistics
Using probability to determine characteristics
28
Distribution
Shape of the data
29
Gaussian Distribution
Bell curve - 95% of data is within 2 standard deviations of the mean
30
Systemic Distribution
Equal number above and below the mean
31
Skewed Distribution
More below or above the mean
32
Central Tendency
Representative value for distribution (mean, median, mode)
33
Z-Score
Standard deviation units.
34
Inter-Quartile Range
Value between the 25th percentile and 75th
35
T-Test
Difference between the means of two data sets.
36
ANOVA
Analysis of variance - testing equality by classifying groups
37
Chi Square Test
Goodness of fit. Tests sample and hypothesized distribution - determine if one variable is related to another
38
Bivariate
Correlation is not causation - linear relationship
39
Population Estimate: Linear
Change in population over time
40
Population Estimate: Exponential & Modified Exponential
Percentage change extrapolated into the future - curved line
41
Population Estimate: Symptomatic
Uses data indirectly related to population (i.e. drivers licenses, housing)
42
Population Estimate: Step-Down Ratio
Uses population at known point in time as compared to larger city/county
43
Population Estimate: Distributed Housing Unit
Uses housing units multiplied by occupancy rate
44
Population Estimate: Cohort Survival
Current population plus natural increases (birth/migration)
45
Economic Base
Basic + non-basic activities Basic = exported Non-basic = local
46
Location Quotient
Industry's share of local employment divided by share of the nation (>1 means exporting economy)
47
Shift Share
``` Employment growth by sector. National (share) Industry (mix) Regional Competitiveness (shift) - = lagging sector; + = leading sector ```
48
Input-Output
Based on suppliers & purchasers
49
Gompertz Curve
Growth is slowest at the beginning and end.
50
Satisfice
Making a decision when all of the information is not available.