Unit 1 Chapters 10-12 Flashcards
Ch 10: Define “Random”
An outcome is random if we know the possible values it can have, but not which particular value it takes.
Ch 10: What is a “Simulation”
A simulation mimics a real-life event by using random numbers to represent the outcomes of real events.
Ch 10: What is a “Simulation Component?”
A component uses equally likely random digits to model simple random occurrences whose outcomes may not be equally likely.
Ch 10: What is a “Trial”
The sequence of several components representing events that we are “pretending” will take place.
Ch 10: Define “Response Variable”
Values of the response variable record the results of each trial with respect to what we were interested in.
Ch 11: Define “Population”
The entire group of individuals or instances about whom we hope to learn.
Ch 11: Define “Sample”
A subset of a population, examined in hope of learning about the population
Ch 11: What is a “Sample Survey?”
A study that asks questions of a sample drawn from some population in hope of learning something about the entire population.
Ch 11: Name four types of “Bias” in a survey.
1) relying on voluntary response; 2) undercoverage of the population; 3) nonresponse bias; 4) response bias
Ch 11: What minimizes the risk of bias in a survey?
Randomization. Each individual is give a fair, random chance of selection.
Ch 11: What is “Sample Size?”
The number of individuals in a sample.
Ch 11: What is a “Census?”
A sample that consists of the entire population.
Ch 11: Define the term “Population Parameter”
A numerically valued attribute (mean, standard deviation, proportion, correlation, regression coefficient) of a model for a population.
Ch 11; What is a “Sample Statistic?”
Values calculated from sample data (mean, standard deviation, proportion, correlation, regression coefficient), used to estimate a population parameter
Ch 11: When is a sample “representative?”
A sample is representative if the statistics computed from it accurately reflect the population parameters.
Ch 11: “SRS”
A “Simple Random Sample” of sample size n is a sample in which each set of n elements in the population has an equal chance of selection.
Ch 11: What is the “Sampling Frame?”
The list of individuals from whom the sample is drawn. Individuals who may be in the population of interest, but not in the sample frame may NOT be included in the sample.
Ch 11: Define Sampling Variability
The natural tendency of randomly drawn samples to differ from one another.
Ch 11: What is a “Stratified Random Sample?”
A sampling design in which the population is divided into several subpopulations, or strata. Random samples are then drawn from each stratum.
Ch 11: What is a “Cluster Sample?”
A sampling design in which entire groups, or clusters, are chosen at random. Cluster sampling is usually selected as a matter of convenience, practicality, or cost.
Ch 11: Define “Multistage Sampling”
Sampling schemes that combine several sampling methods.
Ch 11: What is “Systematic Sampling?”
A sample drawn by systemically selecting individuals from a sampling frame (ie: select a random starting point, then choose every 5th name from a list)
Ch 11: What is a “Pilot Study?”
A small trial run of a survey to check whether questions are clear.
Ch 11: What is “Voluntary Response Bias?”
Bias introduced to a sample when individuals can choose on their own whether to participate in the sample.
