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2015AICPPlanMak/Impl
Plan & Vision, Survey, Data Collection, Site and Econ Analysis, Statistics
| Term | Definition |
|---|---|
| Plan Making Process Inlcudes | 1. Goals and visions; 2. Analysis of current problems; and 3. Creation and evaluation of alternatives. |
| Strategic Planning | Short Term, 5 or fewer years. Sets goals, objectives and policies for reaching set objectives and funding for e/ objective. Sometimes done instead of comprehensive planning |
| Visioning | 20-30 year timeframe. Process for citizens to create a vision statement by a series of meetings. Focus is on what community wants, not existing conditions. |
| Tribal Comprehensive Plans | Engages tribal government leads, residents and businesses in preparing plans and administering planning processes in support of a tribal community. |
| Survey | Research method to collect data on a topic that cannot be directly observed Used to gather attitudes and characteristics.Takes a sample of the population |
| Cross-Sectional Survey | Gathers info about a population at a single point in time. Ex. How parents feel about the quality of recreational facilities |
| Longitudinal Survey | Gathers info about a population over a period of time. Ex.Citizen service satisfaction survey over a few years |
| Written Survey | Good for info gathering of a broad audience. Mailed, printed or administered in a group setting. Low Cost but low 20% response rate. Reading and writing is required; not good for illiterate |
| Group-administered Survey | Good for targeting specific audience, small sample size. High and quick response rate. Problem is getting people together to complete survey |
| Drop-off Survey | Survey dropped off at someone's residence or business, small sample, completed at their convenience. Higher response rates than mail bc of personal contact. Expensive. |
| Phone Survey | Good for yes/no answers. Allows a follow up. Expensive. Can be biased. Not good for long questions and multiple answers |
| Online Survey | Administered on website, email or text message. Inexpensive method for a quick responses. Higher response rather than written/interview surveys. Will not reach people without internet |
| When Designing a survey | Make all questions clear; only ask about one issue per question, avoid negative items, avoid biased items and terms, consistent response method such as 1 to 7 or yes/no; order from general to specific; define terms |
| Convenience Sample | Uses individuals that are readily available for a survey |
| Random Sample | Everyone has a chance to be selected to participate in survey |
| Stratified Sample | Divides population into groups where sample is drawn in survey |
| Scale | Small scale = large land area with little detail Large scale = limited land area with great detail |
| USGS Scale | 1:24,000 scale means 1" = 2,000 lf and .3787 miles (divide by 5,280) |
| Slope | 0-0.5% = no drainage, not suited for development; 0.5-1% = no prob, ideal for all types of development; 1-3% = slight prob for large commercial areas; acceptable for residential; 3-5% = major prob for commercial/industrial/large scale res; |
| Slope Calculated | Rise (change in y coordinate) / Run (change in x coordinate) |
| Floor area ratio (FAR) | Gross floor area of a building/ Ground area. Used to determine building density on a site. 20,000 sf has FAR limit of .5 = site may not exceed 10,000 sf |
| Population | Total number of some entity. The total number of planners preparing for the 2011 AICP exam. |
| Sample | Subset of the population. For example, 25 candidates out of the total number of planners preparing for the 2011 AICP exam. |
| Descriptive Statistics | Describe the characteristics of a population. 25% of AICP test takers passed exam. |
| Inferential Statistics | Determine characteristics of a population based on observations made on a sample from that population |
| Central tendency | Typical or representative value of a dataset. Mean, median and mode |
| Mean | Average of a distribution. [2, 3, 4, 5] is 3.5 |
| Median | Middle number of a ranked distribution. [2, 3, 4, 6, 7] is 4 |
| Mode | Most frequent number in a distribution.[1, 2, 3, 3, 5, 6, 7, 7] are 3 and 7. |
| Nominal data, MO | Classified into mutually exclusive groups that lack intrinsic order. Race, social security number, and sex are examples of nominal data. Mode is used |
| Ordinal data, MO, MED | Values ranked so inferences can be made regarding the magnitude but data has no fixed interval between values. Educational attainment or a letter grade on a test are examples of ordinal data. Mode and median are used |
| Interval data , MEA | Ordered relationship with a magnitude. For temperature, 30 degrees is not twice as cold as 60 degrees. Mean is used |
| Ratio data, ALL | Ordered relationship and equal intervals. Distance is an example of ratio data. 3.2 miles is twice as long as 1.6 miles. Any form of central tendency can be used |
| Qualitative Variables Quantitative Variables | nominal or ordinal interval or ratio |
| Continuous Variables | Can have an infinite number of values, such as 1.1111 |
| Dichotomous Variables | Can only have two possible values, such as unemployed or employed which are symbolized as 0 and 1. |
| Hypothesis Test | Allows for a determination of possible outcomes and the interrelationship between variables. |
| Null Hypothesis | Shown as H0 is a statement that there are no differences. For example, a Null Hypothesis could be that Traffic Calming has no impact on traffic speed |
| Alternate Hypothesis | Designated as H1, proposes the relationship - Traffic Calming reduces traffic speed. |
| Normal Distribution | Data Distribution symmetrical around the mean. This is a bell curve. Right skew = higher numbers (large home values) Left skew = low numbers (people walk out of AICP test) |
| Range | Simplest measure of dispersion. The range is the difference between the highest and lowest scores in a distribution. Survey goes to 18-64 yr olds. Range = 44 |
| Variance | Average squared difference of scores from the mean score of a distribution. Variance is a descriptor of a probability distribution, how far the numbers lie from the mean. Calculated by squaring each number and sum it. |
| Standard Deviation | Square root of the variance. If we want to know the difference in wages among three employees at a planning department, we need to calculate mean, variance and standard deviation. |
| Coefficient of Variation | Measures the relative dispersion from the mean and is measured by taking the standard deviation and dividing by the mean |
| Standard Error | Standard deviation of a sampling distribution. Standard errors indicate the degree of sampling fluctuation. The larger the sample size the smaller the standard error. |
| Confidence Interval | Gives an estimated range of values which is likely to include an unknown population parameter. Large width of confidence interval = need more data before making a definitive answer. +/-3%as seen in polls |
| Chi Square | Provides a measure of the amount of difference between two frequency distributions to test the goodness of fit of an observed distribution to a theoretical one |
| z-score | Measure of the distance, in standard deviation units, from the mean. This allows one to determine the likelihood, or probability that something would happen |
| t-test | Allows the comparisons of the means of two groups to determine how likely the difference between the two means occurred by chance. needs to know the number of subjects, the difference between the means, and the standard deviation |
| ANOVA | Analysis of variance. It studies the relationship between two Variables, the first variable must be nominal and the second is interval. |
| Correlation tests Correlation Coefficient | Strength of the relationship between variables. Indicates the type and strength of the relationship between variables, ranging from -1 to 1. The closer to 1 = stronger relationship. AICP Test Passers = strong relationship to hours studied |
| Regression | test of the effect of independent variables on a dependent variable. A regression analysis explores the relationship between variables AICP Exam Passers= hours studies, years of experience, etc |
| Population Estimate: Linear Method | Uses the rate of growth (or decline) in population over a period of time to estimate the current or future population Plannersville has grown an average of 1000 people per year over the last 20 years = this same rate of growth in the future |
| Population Estimate: Exponential Method | uses the rate of growth (or decline) in population over a period of time to estimate the current or future population For example, growing 2% per year for 20 years. Two percent of 2,000 people is larger than 2% of 1,000 people. |
| Population Method: Symptomatic Method | Uses available data to estimate the current population. If the average household size is 2.5 and 100 new single-family building permits are issued this year, approximately 250 new people will be added to the community |
| Population Method: Step-Down Ratio Method | Used to estimate or project population. This method uses the ratio of the population in a city and a county at a known point in time. Ex. City is 20% of County pop in 2000. In 2005 we can estimate city pop is 4,000 (20%) |
| Population Method: Distributed Housing Unit Method | Number of housing units multiplied by the occupancy rate and persons per household. This method is reliable for slow growth or stable communities, but is less reliable in communities that are changing more quickly. |
| Population Method: Cohort Survival Method | Uses the current population plus natural increase and net migration to calculate a future population. The population is calculated for men and women in specific age groups |
| Natural increase | difference between the number of children born and the number of people who die during one time interval |
| Death rate | number of deaths per 1,000 people |
| General Fertility Rate | number of babies born per 1,000 females of childbearing age |
| Net Migration | difference between the number of people moving in and the number of people moving out |
| Economic Analysis: Economic Base Analysis | basic (exports - manufacturing) and non-basic (locally oriented) economic activities. The exporting industries make up the economic base of a region |
| Economic Analysis: Location Quotient | Type of Economic Base Analysis. The ratio of an industry's share of local employment/ share of the nation (or other level of government). <1 = import. >1 = export |
| Economic Analysis: Shift-share analysis | Analyzes a local economy in comparison with a larger economy. Method uses employment information by sector for two points in time.Ex. Compare Employment by Industry between 1990 to 2000. |
| Economic Analysis: Input-Output Analysis | Quantitative method that identifies primary suppliers, intermediate suppliers, intermediate purchasers, and final purchasers. Produces multipliers. Ex. the construction of a major league football stadium in the City of Industry, CA. |
| North American Industry Classification System (NAICS) | Developed by Office of Management and Budget in 1997. 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. Replaced SIC |
Created by:
cristinrae21
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