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.
Ch 11: Name the problem with “Convenience Samples”
These samples include individuals who are conveniently available. They often fail to be representative because everyone in the population is not equally convenient to sample.
Ch 11: How does “Undercoverage” bias a sample?
In the sample, a part of the population is given less representation than it has in the population.
Ch 11: “Nonresponse Bias” occurs when…
a large fraction of those sampled fails to respond. Those who do respond are likely to NOT represent the entire population.
Ch 11: Define “Response Bias”
Anything in a survey design that influences responses falls under the heading of response bias. Example: wording of question may suggest a favored response.
Ch 12: What is an “Observational Study”
A study, retrospective or prospective, based on data in which factors were not manipulated. Researchers observe factors.
Ch 12: What are the main features of an “Experiment”
1) manipulates factor levels to create treatments; 2) randomly assigns subjects to treatment levels; 3) compares the responses across treatment levels
Ch 12: Define “Random Assignment”
An experimenter assigns experimental units to treatment groups in a random way (slips of paper, random numbers, etc)
Ch 12: What is a “Factor?”
A variable whose levels are manipulated by the experimenter.
Ch 12: Define “Response”
A variable whose values are compared across different treatments.
Ch 12: What are “Experimental Units?”
Individuals on whom an experiment is performed.
Ch 12: What is the “level” of a factor?
The specific values that the experimenter chooses for a factor.
Ch 12: What is a “Treatment?”
The process, intervention or other controlled circumstance applied to randomly assigned experimental units.
Ch 12: What are the “Principles of Experimental Design?”
1) Control; 2) Randomize; 3) Replicate; 4) Block
Ch 12: What is true about a “Completely Randomized Design?”
All experimental units have an equal chance of receiving any treatment.
Ch 12: What does it mean for an observed difference to be “Statistically Significant?”
The observed difference is too large for us to believe that it is likely to have occurred naturally.
Ch 12: What is assigned to a “Control Group?”
Experimental units assigned to a baseline treatment level.
Ch 12: Describe the concept of “Blinding”
Any individual associated with an experiment who is not aware of how subjects have been allocated to treatment groups is said to be blinded.
Ch 12: What is a “Placebo?”
A treatment known to have no effect, administered to one group so that all groups experience the same conditions.
Ch 12: Describe the “Placebo Effect”
The tendency of many human subjects to show a response even when administered a placebo.
Ch 12: Describe “Blocking”
Grouping similar experimental units. In this way, we reduce the variability in the differences between blocks, and the differences between treatments is better observed.
Ch 12: Describe “Randomized Block Design”
The subjects are randomly assigned to treatments within blocks.
Ch 12: When are factors “Confounded?”
When the levels of one factor are associated with the levels of another factor in such a way that their effects cannot be separated.
