RESEARCH AND ASSESSMENT METHODS Flashcards

1
Q

Linear Method

A

The linear method uses the change in population (increase or decline) over a period of time and extrapolates that change into the future, in a linear fashion. For example, if the population of Plannersville has grown an average of 1,000 people per year over the last 20 years, it would be assumed to grow by 1,000 people annually in the future.

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2
Q

Exponential Method

A

CURVE
The exponential method uses the rate of growth (or decline), i.e., the percentage change in population over a period of time to estimate the current or future population. In the same Plannersville example, the population has been increasing by 2% per year for the last 20 years. This percentage change is extrapolated into the future. Two percent of 2,000 people is larger than 2% of 1,000 people. The result is a curved line.

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3
Q

Modified Exponential Method

A

S SHAPED CURVE

A modified exponential projection assumes there is a cap to the change and that at some point the growth will slow or stop, resulting in an S-shaped curved line. The Gompertz Projection is a further modification of the modified exponential, where the growth is slowest at the beginning and speeds up over time.

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4
Q

Symptomatic Method

A

The symptomatic method uses any available data indirectly related to population size, such as housing starts, or new drivers licenses. It then estimates the population using a ratio, such as the average household size (from the U.S. Census). For instance, with the average household size at 2.5, data on 100 new single-family building permits that are issued this year, would yield an estimate of 250 new people will be added to the community.

Other sources of data for estimating population can include water taps, phone lines, voter registration, and utility connections.

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5
Q

Step Down Ratio Method

A

The step-down ratio method is a relatively simple way to estimate or project population. This method uses the ratio of the population in a city and a county (or a larger geographical unit) at a known point in time, such as the decennial Census.

This ratio is used to project the current or future population. For example, the population of Plannersville is 20% of the county population in 2000. If we know that the county population is 20,000 in 2005, we can then estimate the population of Plannersville as 4,000 (20%).

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6
Q

Distributed Housing Unit Method

A

This method multiplies Census Bureau data for the number of housing units by the occupancy rate and persons per household. This method is reliable for slow growth or stable communities but is less reliable in quickly changing communities.

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7
Q

Cohort Survival Method

A

Calculated for Men and Women in specific age groups
current population plus natural increases (births, deaths, Migration)

Population pyramid (elders on top)
age cohorts, with same year intervals, to keep consistency as cohorts age.

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8
Q

The general fertility rate

A

number of babies born per 1,000 females

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9
Q

Death Rate

A

death rate per 1000 people

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10
Q

Net Migration

A

Number of people moving in minus people moving out

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11
Q

what is the most accurate population projection method

A

Cohort Survival Method

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12
Q

Qualitative research

A

An approach for understanding the meaning individuals and groups ascribe to a human or social problem
Emerging questions
Flexible written report
Analysis building from particular data to general themes (inductive)

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13
Q

Quantitative Research

A

An approach for testing objective theories by examining the relationships among variables (deductive)
Numbered data which can be analyzed using statistical procedures
Structured written report

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14
Q

Mixed Methods Research

A

Collection of both qualitative and quantitative data
Integrating the two forms of data
May involve both philosophical assumptions and theoretical frameworks
Assumes a more complete understanding of a research problem than using one of the approaches alone

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15
Q

Case Study Method

A

A research method focusing on the study of a single case. Usually it is not designed to compare one individual or group to another, although sometimes a case study may be included in comparative analysis as a key or illustrative example.

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16
Q

Discourse Analysis

A

A study of the way versions or the world, society, events, and psyche are produced in the use of language and discourse. It is often concerned with the construction of subjects within various forms of knowledge/power. Semiotics, deconstruction, and narrative analysis are forms of discourse analysis.

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17
Q

Comparative Analysis

A

Analysis where data from different settings or groups at the same point in time or from the same settings or groups over a period of time are analyzed to identify similarities and differences.

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18
Q

e-research

A

Also known as e-Science or e-Social Science, e-Research is the harnessing of any digital technology to undertake and promote social research. This includes treating the digital sphere as a site of research by examining social interaction in the e-infrastructure.

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19
Q

Ethnography

A

A multi-method qualitative (participant observation, interviews, discourse analyses of natural language and personal documents) approach that studies people in their “…naturally occuring settings or ‘fields’ by means of methods which capture their social meanings and ordinary activities, involving the researcher participating directly in the setting…”

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20
Q

Field Research

A

a researcher goes to observe an everyday event in the environment where it occurs

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21
Q

Grounded Theory

A

An inductive form of qualitative research where data collection and analysis are conducted together. Theories remain grounded in the observations rather than generated in the abstract. Grounded theory is an approach that develops the theory from the data collected, rather than applying a theory to the data.

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22
Q

Narrative Analysis

A

Narrative analysis is a form of discourse analysis that seeks to study the textual devices at work in the constructions of process or sequence within a text.

In narrative research, the respondent gives a detailed account of themselves and is encouraged to tell their story rather than answer a predetermined list of questions. This method is more successful when people are discussing a life changing event.

Analysis of the narrative tells the researcher about the person’s understanding of the meaning of events in their lives.

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23
Q

Nominal Data

A

Nominal data are classified into mutually exclusive groups or categories and lack intrinsic order. A zoning classification, social security number, and sex are examples of nominal data. The label of the categories does not matter and should not imply any order. So, even if one category might be labeled as 1 and the other as 2, those labels can be switched.

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24
Q

Ordinal Data

A

Ordinal data are ordered categories implying a ranking of the observations. Even though ordinal data may be given numerical values, such as 1, 2, 3, and 4, the values themselves are meaningless. ONLY THE RANK COUNTS. It would be incorrect to infer, for example, that 4 is twice 2, despite the temptation. Examples of ordinal data include letter grades, suitability for development, and response scales on a survey (e.g., 1 through 5).

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25
Q

Interval Data

A

Interval data has an ordered relationship where the difference between the scales has a meaningful interpretation. The typical example of interval data is temperature, where the difference between 40 and 30 degrees is the same as between 30 and 20 degrees, but 20 degrees is not twice as cold as 40 degrees.

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26
Q

What kind of data are letter grades, and response scales 1-5

A

Ordinal Data

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27
Q
A
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28
Q

What kind of data are zoning classification, SSN, gender

A

Nominal

29
Q

What kind of data is temperature

A

Interval Data

30
Q

Ratio Data

A

Ratio data is the gold standard of measurement, where both absolute and relative differences have a meaning. The classic example of ratio data is a distance measure, where the difference between 40 and 30 miles is the same as the difference between 30 and 20 miles, and in addition, 40 miles is twice as far as 20 miles.

31
Q

What type of measurement is used for Quantitative variables?

A

interval and ratio measurement

32
Q

What type of measurement for Qualitative variables

A

Ordinal and nominal measurement

33
Q

Binary/Dichotomous Variable

A

can only take two values, i.e. 1 or 0

34
Q

Kurtosis

A

the presence of thick tails in a distribution curve, i.e. higher likelihood of extreme values

35
Q

What percentage of observation fall within 2 sTDs

A

95%

36
Q

What percentage of observations fall within 1 STD

A

68%

37
Q

What percentage of observations falls within 3 STDs

A

99.7%

38
Q

what is the median of [2,3,4,5]

A

3.5 (the average of 3 and 4 since there is no middle number because even amount.

39
Q

what is statistical variance and the equation?

A

The average of the squared differences from the mean

Divide by n if the population mean is known
divide by n-1 if mean is of a SAMPLE

(degree of freedom correction, n-1)

40
Q

what is the standard deviation

A

the square root of the variance

41
Q

coefficient of vatriation

A

= Standard Deviation/ Mean

42
Q

What is the standard deviation equation

A
43
Q

Z score equation

A
44
Q

What is the interquartile range

A

the range between Q1 and Q3

45
Q

Outlier calculation

A
46
Q

Statistical evidence can ONLY ______ the null hypothesis, but never…

A

The statistical evidence only provides support to reject the null hypothesis, NEVER ACCEPT THE ALTERNATIVE HYPOTHESIS (i.e., the alternative is only used as a means to help in rejecting the null). An alternative hypothesis can be two-sided (differences in both directions are considered) or one-sided (only differences in one direction are considered, i.e., only larger than or smaller than, but not both).

47
Q

difference between a standard error and standard deviation

A

A possible source of confusion is the difference between the standard deviation and the standard error. They are essentially the same concept (and are computed in the same way), but the standard error pertains to the distribution of a STATISTIC that is computed from a sample. For example, the sample average has a standard error, which is the same as the standard deviation of its sampling distribution.

*STANDARD DEVIATION quantifies the variation within ONE SET of measurements.

STANDARD ERROR quantifies the variation in the means of multiple sets of measurements.

48
Q

P -Value/Type 1 Error

A

The probability that we reject the null hypothesis when in fact it is correct.

Typical significance benchmarks are 5% or 1%

49
Q

sample error

A

sample mean minus population mean

50
Q

statistic

A

mean gathered from a sample

51
Q

parameter

A

mean gathered from a population

52
Q

ANOVA

A

ANOVA or analysis of variance is a more complex form of testing the equality of means between groups. The typical application is in a so-called treatment effects analysis where the outcome of a variable is compared between a treatment group and a control group(in medical experiments, this would be the placebo group). For example, we would compare the average speed of cars on a street before (control) and after a street calming infrastructure was put in place (treatment). It is thus similar to the case considered in a t-test, but it allows more complex categorization of the groups. Typically, one classifies the sample into several groups according to categorical variables and compares the mean outcome on a continuous outcome variable. An F-test is a simple case of ANOVA, a slight generalization of the t-test (allowing different variances in two groups).

53
Q

T Test

A

A t-test (also known as Student’s t-test) is typically used to compare the means of two populations based on their sample averages. This is a so-called two-sample t-test (a one sample t-test compares the sample average to a hypothesized value for the mean). So, the null hypothesis is that the two population means are equal. However, since we do not observe the actual means, but only the sample averages, we can only make a probabilistic statement about the equality. Each of the sample averages has its only sampling distribution. By comparing the two sampling distributions, we can make statements about the null hypothesis. Under the null hypothesis, the test statistic follows the Student’s t distribution (similar to the normal distribution, but with thicker tails).

The implementation of the t-test is slightly different between the one sample case, and for the two-sample case, between assumptions of equal variance or unequal variance.

54
Q

Chi Square Test

A

Hypothesis test used when you want to determine if there is a relationship between two CATEGORICAL VARIABLES.

i.e. male/female, preferred newspaper, education level

A Chi Square test is a measure of fit. It is a test that assesses the difference between a sample distribution and a hypothesized distribution. A Chi Square test is often used to test the null hypothesis of independence in a contingency table, i.e. when the observations are grouped according to two categorical variables. The observed proportions are compared to the proportions we would expect if the two classifications were independent. The Chi Square distribution is a skewed distribution that is obtained by taking the square of a standard normal variable (so, it only takes positive values). Under the null, the Chi Square test follows a Chi Square distribution.

55
Q

correlation coefficient (r)

A

between -1 and 1
greater than zero is a positive correlation
negative is a negative correlation

56
Q

r squared

A

is between 0 and 1, and is a percentage.

57
Q

dependent variable

A

left side of the equation, Y

58
Q

explanatory variables

A

right hand of the equation

59
Q

linear population estimation

A

i.e. 1000 people per year

60
Q

exponential population estimation

A

i.e. 2% per year (curved growth) because it is a rate

61
Q

Economic Base Analysis

A

looks at basic and non basic economic activities

62
Q

Basic Economic Activity

A

those that can be exported

63
Q

non-basic

A

those that are locally oriented

64
Q

Input output analysis

A

links suppliers and purchasers to determine the economic output of a region.

  • requires large quantity of data, costly
  • Can determine the employment effect a certain project has on a local economy
  • identifies: primary suppliers, intermediate suppliers, intermediate purchasers, final purchasers.
65
Q

An input output analysis is composed of three tables:

A

transactions
direct requirements
total requirements

66
Q

North American Industry Classification System (NAICS)

A

is the standard used by Federal statistical agencies in classifying business establishments for the purpose of collecting, analyzing, and publishing statistical data about the U.S. economy

67
Q

What was the North American Industry Classification System replaced with in 1997?

A

Standard Industrial Classification (SIC) System

68
Q

TIGER

A

is the acronym for Topographically Integrated Geographical Encoding and Referencing map, which is used for Census data. A TIGER map includes streets, railroads, zip codes, and landmarks. TIGER maps are used by the U.S. Census Bureau and can be downloaded into a GIS system, where they are often used as base layers upon which local information is added.