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Research Methods
Research Methods, AICP Nov 2022 Test
| Term | Definition |
|---|---|
| Three steps of the statistical process | quantitative |
| Nominal Data | Classified into mutually exclusive groups or categories and lack intrinsic order. A zoning classification, social security number, and sex are examples of nominal data. (qualitative variable) |
| Ordinal Data | ordered categories implying a ranking of the observations. Examples of ordinal data are letter grades, suitability for development, and response scales on a survey (e.g., 1 through 5). (qualitative data) |
| Interval Data | Data that has an ordered relationship where the difference between the scales has a meaningful interpretation. The typical example of interval data is temperature |
| Ratio Data | gold standard of measurement, where both absolute and relative differences have a meaning. The classic example of ratio data is a distance measure |
| Quantitative Variables | Household income, level of pollution in a river. Represent interval data |
| Qualitative variables | Zoning classification. Represent nominal or ordinal data |
| Continuous variables | Can take an infinite number of values, both positive and negative, and with as fine a degree of precision as desired. Most measurements in the physical sciences yield continuous variables. |
| Discrete variables | can only take on a finite number of distinct values. An example is the count of the number of events, such as the number of accidents per month - cannot be negative |
| Binary/dichotomous variables | can only take on two values, typically coded as 0 and 1. |
| Population | totality of some entity ex # of planners preparing for AICP test |
| Sample | subset of the population |
| Descriptive Statistics | describe the characteristics of the distribution of values in a population or in a sample |
| Inferential Statistics | Use probability theory to determine characteristics of a population based on observations made on a sample from that population. We infer things about the population based on what is observed in the sample. |
| Distribution | overall shape of all observed data. It can be listed as an ordered table, or graphically represented by a histogram or density plot. |
| Central tendency | a typical or representative value for distribution of observed values. (mean, median, mode) |
| Dispersion | How distribution values are spread around the central tendency |
| Symmetry | is an attribute used to describe the shape of a data distribution. |
| Skewness | If the skewness of S is zero then the distribution represented by S is perfectly symmetric. If the skewness is negative, then the distribution is skewed to the left, while if the skew is positive then the distribution is skewed to the right |
| Kurtosis | provides a measurement about the extremities (i.e. tails) of the distribution of data, and therefore provides an indication of the presence of outliers. |
| Normal/Gaussian Distribution (Bell Curve) | this distribution is symmetric and has the additional property that the spread around the mean can be related to the proportion of observations. 95% of the observations that follow a normal distribution are within 2 standard deviations from the mean |
| Variance (stats) | a measure of how spread out a distribution is. It is computed as the average squared deviation of each number from its mean. |
| Standard Deviation | square root of the variance. |
| Coefficient of Variation | measures the relative dispersion from the mean by taking the standard deviation and dividing by the mean |
| Z-Score | the number of standard deviations from the mean a data point is. But more technically it's a measure of how many standard deviations below or above the population mean a raw score is |
| Inter-quarterly Range | is a measure of variability, based on dividing a data set into quartiles. Quartiles divide a rank-ordered data set into four equal parts. |
| hypothesis test | distinguish between the null hypothesis (H0), i.e., the point of departure or reference, and the alternative hypothesis (H1), or the research hypothesis one wants to find support for by rejecting the null hypothesis |
| Linear Method | uses the change in population (increase or decline) over a period of time and extrapolates this change to the future, in a linear fashion (i.e. grows by 1,000 people every year) |
| Exponential and Modified 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 - percent change extrapolated into the future. Modified = assumes at some point growth stops |
| Symptomatic Method | uses any available data indirectly related the population size, such as housing starts, or new drivers licenses. |
| Step-Down Ratio 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. |
| Distributed Housing Unit Method | uses the Census Bureau data for the number of housing units, which is then multiplied by the occupancy rate and persons per household. |
| Cohort Survival Method | uses the current population plus natural increase (births less deaths) and net migration (in-migration less out-migration) to calculate a future population. The population is calculated for men and women in specific age groups. |
| Input-Output Analysis | a quantitative method that links suppliers and purchasers to determine the economic output of a region, identifies primary suppliers, intermediate suppliers, intermediate purchasers, and final purchasers |
| Location Quotient | defines base sector of study area, or the concentration of a given industry in a given place in comparison to the nation – used to tell the amount of export employment in an industry - >1 = exporting basic <1 = importing local |
| Economic Base Theory | divide regional industries into two groups: Basic (export) and Non-basic (local sectors) |
| Shift Share Analysis | a descriptive technique for analyzing sources of change in the regional economy by looking at national share, industry mix, and regional shift |
| National growth share | what part of local job growth is due to growth in the national economy |
| Industry mix | the effect of industry trends on local employment |
| Regional shift | unique local factors relating to local employment growth or decline |
| North American Industry Classification System (NAICS) | Used by Federal statistical agencies in classifying business establishments for the purpose of collecting, analyzing, and publishing statistical data about the U.S. economy, 6 digit code distinguishes industries |
| Areas under the normal distribution curve | • 68 % is within one standard deviation of the mean. • 95% is within two standard deviations. • 99% is within three standard deviations." |
| TIGER | he 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. |
| Digital Aerial Photography | Digital aerial photography has allowed for increased accuracy to the 0.5-foot resolution |
| Digital Elevation Models (DEMs) | how digital data about the elevation of the earth's surface as it varies across communities allows planners to analyze and map it. |
| Light Detection and Ranging (LIDAR) | new technology using a laser, instead of radio waves, that is mounted in an airplane to provide detailed topographic information. |
| UrbanSim | simulation software program that models planning and urban development. |
| CommunityViz | is an ESRI software environment that allows agencies to analyze land use scenarios and create 3D images. - |
| Urban Footprint | developed by Peter Calthorpe and Associates, uses a library of place types, block types, and building types to support interactive scenario building. |
| US Geological Survey Scale | 1 inch equals :24,000 lf |
| Slope | 0-0.5% = no drainage, not suited for dev; 0.5-1% no problems. ideal for all types of deve; 1-3% slight problems for large commercial areas; acceptable for residential; 3-5% major problems for commercial/industrial/large scale residential |
| Zip code | Zone Improvement Plan Code |
| 1 acre | 43560 square feet |
| 1 mile | 5280 feet |
| 1 hectacre | 2.47 acres |
| 1 square mile | 640 acres |
Created by:
cristinemshoff
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