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# Unit 3 Stat Vocab

### Various simulation and bias vocabulary

Simulation Using random numbers to generate relative frequencies
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
Survey A study in which the researcher gathers data by asking for responses from subjects.
Obervational study A study in which the researcher observes behaviors of the subjects
Controlled experiment A study in which the researcher imposes (manipulates variables) on subjects.
2 Examples of Invalid Sampling 1) Convenience 2) Voluntary response
Bias A systematic effect that skews all of the data values in a sample, in one direction.
Census Studying ALL subjects of the population of interest
Sample Studying a proper subset of the subjects from the population of interest.
5 valid types of sampling Simple random sampling (SRS), stratified random sampling, cluster, systematic, and two stage.
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.
Stratified Random Sampling Dividing the population into subgroups, then using SRS to select equally from each group
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)
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.
Two Stage Sampling A subset of elements within each selected cluster is randomly selected for inclusion in the sample.
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)
Parameter A number that characterizes some aspect of the population like mean or standard deviation.
Statistic Values calculated for sample data. Used to estimate parameters.
The 3 / 4 requirements for a fair experiment 1)Control 2)Randomization 3)Replication 4)Block (is possible to improve design)
Two Types of Matched Pairs Design One and Two Subject(s)
One Subject matched - pair design One subject receives both treatments and the order in which they are received is random.
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.
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.
What is Statistical Significance When the difference is too large for us to believe it occurred by chance.
Created by: yinyang2424