Various simulation and bias vocabulary
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Simulation | Using random numbers to generate relative frequencies
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In order to perform a simulation, one must: | 1) Identify component 2) Explain how you model outcome 3) Explain simulation of trial 4) State y variable 5) Run sev. trials 6) Analyze y variable 7) State conclusion
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Survey | A study in which the researcher gathers data by asking for responses from subjects.
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Obervational study | A study in which the researcher observes behaviors of the subjects
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Controlled experiment | A study in which the researcher imposes (manipulates variables) on subjects.
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2 Examples of Invalid Sampling | 1) Convenience 2) Voluntary response
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Bias | A systematic effect that skews all of the data values in a sample, in one direction.
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Census | Studying ALL subjects of the population of interest
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Sample | Studying a proper subset of the subjects from the population of interest.
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5 valid types of sampling | Simple random sampling (SRS), stratified random sampling, cluster, systematic, and two stage.
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Simple Random Sampling (SRS) | Label every subject with a number starting with 0 or 00, then use a random number generator to identify which numbers are needed to fulfill the quota.
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Stratified Random Sampling | Dividing the population into subgroups, then using SRS to select equally from each group
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Systematic Random Sampling | Separate subjects into random groups and randomly choose one subject from each group (this can really help with achieving more variety in the sampling)
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Cluster / One Stage Sampling | Divide the population into subgroups, and label each group with an overall number, then use a random number generator. The number(s) selected will identify the groups that will be studied / tested.
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Two Stage Sampling | A subset of elements within each selected cluster is randomly selected for inclusion in the sample.
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4 main types of bias | 1) Voluntary response bias 2) Non - responsive bias 3) Response bias (involves an incentive) 4) Under coverage bias (focusing on one specific category, rather than randomizing the subjects)
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Parameter | A number that characterizes some aspect of the population like mean or standard deviation.
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Statistic | Values calculated for sample data. Used to estimate parameters.
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The 3 / 4 requirements for a fair experiment | 1)Control 2)Randomization 3)Replication 4)Block (is possible to improve design)
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Two Types of Matched Pairs Design | One and Two Subject(s)
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One Subject matched - pair design | One subject receives both treatments and the order in which they are received is random.
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Two Subject matched - pair design | Two subject paired based upon similar characteristics, and one subject from the pair is randomly assigned one treatment while the other receives the other treatment. Then, the y variable is the difference in response of each pair.
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2 Types of Blind Studies and Definitions | 1) Single blind: Subject of the experiment do not know which treatment they are receiving 2) Double - Blind: When neither the subject nor the evaluators know which treatment is assigned to which group.
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What is Statistical Significance | When the difference is too large for us to believe it occurred by chance.
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