Quantitative Methods Chapter 1

data
facts and statistics collected together for reference or analysis

statistics
the science of data. It involves collecting, classifying, summarizing, organizing, analyzing, and interpreting numerical and categorical information

descriptive statistics
utilizes numerical and graphical methods to explore data, i.e., to look for patterns in a data set, to summarize the information revealed in a data set, and to present the information in a convenient form

inferential statistics
utilizes sample data to make estimates, decisions, predictions, or other generalizations about a larger set of data

inference
estimate of the characteristics or properties of a population derived from the analysis of a sample drawn from it

experimental/observational unit
is an object usually a person, thing, transaction, or event upon which we collect data

a population
is a set of units sometimes people, objects, transactions, or events that we are interested in studying.

variable
is a characteristic or property of an individual experimental or observational unit

measurement
is the process we use to assign numbers to variables of individual population units

Census
the measure of a variable for every experimental unit of a population

sample
is a subset of the units of a population

statistical inference
is an estimate of prediction or some other generalization about a population based on information contained in a sample

reliability
how good an inference is

measure of reliability
is a statement usually quantified about the degree of uncertainty associated with a statistical inference

four elements of descriptive statistical problems
-the population or sample of interest
-one or more variables that are to be investigated
-tables, graphs, or numerical summary tools
-identification of patterns in the data

five elements of inferential statistical problems
-the population of interest
-one or more variables that are to be investigated
-the sample of population units
-the inference about the population based on information contained in the sample
-a measure of reliability for the inference

a process
is a series of actions or operations that transforms inputs to outputs, a process produces or generates output overtime

black box
a process whose operations or actions or unknown or unspecified

sample (produced by a process)
Any set of output object or numbers (produced by a process)

quantitative data
are measurements that are recorded on a naturally occurring numerical scale

qualitative data
are measurements that cannot be measured on a natural numerical scale; they can only be classified into one group of categorties

3 ways to obtain data
data from a published source
data from a designed experiment
data from an observational study example survey

published source
book, journal, newspaper, or web site,

designed experiment
a method in which the collection of data involves conducting a designed experiment, in which the researcher exerts strict control over the units people, objects, or events, in the study

observational study
the researcher observes the experimental units in their natural setting and records the variables of interest

survey
the most common type of observational study, researcher samples a small group of people, asks one or more questions and records responses

representative sample
exhibits characteristics typical of those possessed by the population of interest

simple random sample
a simple random sample of N experimental units is a sample selected from a population in such a way that every different sample of size N has an equal chance of selection

random number generator
Random number generators are available in table form, online, and in most statistical software packages

complex random sampling designs
stratified random sampling, cluster sampling, systematic sampling, and randomized response sampling

selection bias
results when a subset of experimental units in the population has little or no chance of being selected for the sample

nonresponsive bias
is a type of selection bias that results when data on all experimental units in a sample are not obtained

measurement error
refers to inaccuracies in the values of the data collected. In surveys, the error may be due ambiguous or leading questions and the interviewers effect on the respondent

quantitative literacy
the ability to evaluate data intelligently

statistical thinking
involves applying rational thought and the science of statistics to critically assess data and inferences. Fundamental to the thought process is that variation exists in populations and process data

unethical statistical practice
the selection bias in the sample is chosen intentionally, with the sole purpose to mislead the public