Plan Making and Implementation Flashcards
Comprehensive Plan
“Scope = Entire Community
Time frime = Long Term
Goal= Describe how development might be best accomodated now and in the future.
Implementation = 1. Regulation (zoning, subdivisions, housing ordinances, signs, building codes, taxation)
2. Acquisition (fee simple purchase, dedications, developer agreements, conservation easments, eminent domain)”
Strategic Plan
“Scope = more focused
Time frame = short-term
Goal = Direct resources to accomplish stated purpose
Implementation = 1. Taxation tools (property and sales tax, tax abatement, CID, Tax Increment Financing (TIF)
2. Expenditures (capital improvements, operating expenditures, retiring bond debt)”
Visioning
Used to develop a vision statement, a preferred image of the community. Public participation important step. Used at BEGINNING of process. Does not look at existing constraints.
Goal
Value based statement, not necessarily measureable. Should include purpose, scope, and context
Objective
More specific than goal, measureable statement of desired end, should include location, character, and timing
Policy
Rule or course of action that indicates how the goals and objectives should be realized. Should include principles, agreements, resolutions, and guidance for implementation
Program
series of related, mission-oriented activites aimed at carrying out a particular goal or policy. Should include initiatives, costs, milestones, responsibilites
Nominal Measure
“Descriptive, label, non-numerical
example - gender, race, colors”
Ordinal Measure
“Order of values are important, but the differences is not well known
example- very happy, happy, ok, sad, very sad”
Interval Measure
“Numberic scale in wher we know the order and the difference between values.
Example - 10 degrees, 20 degrees, 30 degrees”
Ratio Measure
“Numeric order and EXACT difference known between values and have an absolute zero value.
Example - amount of apples purchased: 0, 1, 2”
Qualitative Variable
relating to, measuring, or measured by the quality of something rather than its quantity.
Quantitative Variable
relating to, measuring, or measured by the quantity of something rather than its quality.
Discrete Variable
Discrete variablesare countable in a finite amount of time. For example, you can count the change in your pocket. You can count the money in your bank account. You could also count the amount of money ineveryone’sbank account. It might take you a long time to count that last item, but the point is — it’s still countable.
Continuous Variable
Acontinuous variableis one which can take on infinitely many,uncountablevalues.
Dichotomous Variable
Dichotomous variables are nominal variables which have only two categories or levels. For example, if we were looking at gender, we would most probably categorize somebody as either “male” or “female”.
Dependent Variable
“The dependent variable is what is being studied and measured in the experiment.It’s what changes as a result of the changes to the independent variable.An example of a dependent variable is how tall you are at different ages. The dependent variable (height) depends on the independent variable (age).
(Y)”
Independent Variable
“The independent variable is the variable whose change isn’t affected by any other variable in the experiment.Either the scientist has to change the independent variable herself or it changes on its own; nothing else in the experiment affects or changes it.(X)
Example - time or age”
Mode
“The most frequently occurring number found in a set of numbers. The mode is found by collecting and organizing data in order to count the frequency of each result. The result with the highest number of occurrences is the mode of the set.
A measure of Central Tendency”
Mean
“The sum of the values in the data set and then divide by the number of values that you added.
A measure of Central Tendency”
Median
Median”The median is the value separating the higher half from the lower half of a data sample (a population or a probability distribution). For a data set, it may be thought of as the ““middle”” value. For example, in the data set {1, 3, 3, 6, 7, 8, 9}, the median is 6, the fourth largest, and also the fourth smallest, number in the sample.
A measure of Central Tendency”
Normal Distribution
“Anormal distribution, sometimes called thebell curve, is a distribution that occurs naturally in many situations. For example, thebell curveis seen in tests like the SAT and GRE. The bulk of students will score theaverage(C), while smaller numbers of students will score a B or D. An even smaller percentage of students score an F or an A. This creates a distribution that resembles a bell (hence the nickname). Thebell curveis symmetrical. Half of the data will fall to the left of themean; half will fall to the right.
mean = median = mode”
Skewed Distribution
“If one tail is longer than another, the distribution is skewed. These distributions are sometimes called asymmetric or asymmetrical distributions as they don’t show any kind of symmetry.
A left-skewed distribution has a long left tail. Left-skewed distributions are also called negatively-skewed distributions. That’s because there is a long tail in the negative direction on the number line. The mean is also to the left of the peak.
A right-skewed distribution has a long right tail. Right-skewed distributions are also called positive-skew distributions. That’s because there is a long tail in the positive direction on the number line. The mean is also to the right of the peak.”
Range
“Range (statistics) The difference between the lowest and highest values. In {4, 6, 9, 3, 7} the lowest value is 3, and the highest is 9, so the range is 9 − 3 = 6. Range can also mean all the output values of a function.
A measure of Variability”
Variance
“the expectation of the squared deviation of a random variable from its mean. Informally, it measures how far a set of (random) numbers are spread out from their average value.
A measure of Variability”
Standard Deviation
“a measure that is used to quantify the amount of variation or dispersion of a set of data values.[1] A low standard deviation indicates that the data points tend to be close to the mean (also called the expected value) of the set, while a high standard deviation indicates that the data points are spread out over a wider range of values.
A measure of Variability”
Frequency Analysis
Frequencyis the number of occurrences of a repeating event per unit of time. It is also referred to as temporalfrequency, which emphasizes the contrast to spatialfrequencyand angularfrequency. The period is the duration of time of one cycle in a repeating event, so the period is the reciprocal of thefrequency.
Hypothesis Testing
“Hypothesis testing is the use of statistics to determine the probability that a given hypothesis is true. The usual process of hypothesis testing consists of four steps.
- Formulate the null hypothesis H_0 (commonly, that the observations are the result of pure chance) and the alternative hypothesis H_a (commonly, that the observations show a real effect combined with a component of chance variation).
- Identify a test statistic that can be used to assess the truth of the null hypothesis.
- Compute the P-value, which is the probability that a test statistic at least as significant as the one observed would be obtained assuming that the null hypothesis were true. The smaller the P-value, the stronger the evidence against the null hypothesis.
- Compare the p-value to an acceptable significance value alpha (sometimes called an alpha value). If p<=alpha, that the observed effect is statistically significant, the null hypothesis is ruled out, and the alternative hypothesis is valid.”
Regression Analysis
Instatistical modeling,regression analysisis a set of statistical processes forestimatingthe relationships among variables. It includes many techniques for modeling and analyzing several variables, when the focus is on the relationship between adependent variableand one or moreindependent variables(or ‘predictors’). More specifically, regression analysis helps one understand how the typical value of the dependent variable (or ‘criterion variable’) changes when any one of the independent variables is varied, while the other independent variables are held fixed.
Qualitative Data
Qualitative datais information about qualities; information that can’t actually be measured. Some examples ofqualitative dataare the softness of your skin, the grace with which you run, and the color of your eyes.
Descriptive Data
tools, data, and methods to describe the population within an area
Trends (demographic)
how demographic data has changed over a period of time
Projections
Estimates of future population and population structure
Crude Death Rate
deaths / 1000 pop
Crude Birth Rate
births / 1000 pop
General Fertility Rate
births / 1000 women aged 15-49
Age-Specific Fertility Rate
births per 1000 women in specific age group
Fecundity
physiological capacity of a woman to produce a child
Fertility
acutal reproductive perdomance of an individual
Total Fertility Rate
“number of children women are having
Example - US birth rate is 2.1 births per woman”
Replacement Rate
“Country’s survival rates
Example: 2.06 per woman”