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STATS UNIT 4 vocab
STATS UNIT 2 vocab
| Term | Definition |
|---|---|
| population | entire group of individuals |
| census | collects data from every individual in population |
| sample | subset of individuals in the population |
| sample survey | study that collects data from a sample to learn about the population from which the sample was selected |
| convenience sampling | selects individuals from the population who are easy to reach |
| bias | shows bias if it is very likely to underestimate or very likely to overestimate the value you want to know --> not just bad luck in one sample |
| voluntary response sampling | allows people to choose to be in the sample by responding to a general invitation |
| sampling error | difference between sample result and a true population result --> results from sample chance fluctuation |
| sample chance fluctation | natural |
| non-sampling error | sample data is incorrectly recorded : bias, recorded wrong, faulty instruments |
| random sampling | involves using a chance process to determine which members of a population are included in the sample |
| simple random sample (SRS) | of size n is chosen in such a way that every group of n individuals in the population has an equal chance to be selected as the sample *EVERY SUBSET EQUALLY LIKELY* |
| strata | groups of individuals in a population who share characteristics thought to be associated with the variables being measured in a study |
| stratified random sampling | selects a sample by choosing an SRS from each stratum and combining the SRS, into one overall sample * |
| sampling without replacement | an individual from a population can be selected ONLY ONCE |
| sampling with replacement | an individual from a population can be selected MORE THAN ONCE |
| systematic sampling | selects a sample from an ordered arrangement of the population by randomly selecting one of the first k individuals and choosing every kth individual thereafter |
| cluster sampling | selects a sample by randomly choosing clusters and including each member of selected clusters in sample |
| cluster | a group of individuals in population that are located near eachother |
| how to do a random number generator | math --> prop --> 5: randomInt( --> add low and high and n |
| stratified random sampling is | similar (homo) *MORE PRECISE ANSWERS* |
| clusters are | heterogeneous *NOT AS PRECISE* |
| what can you do to avoid bad surveys | random sampling |
| undercoverage | occurs when some members of the population are less likely to be chosen or cannot be chosen in a sample |
| Nonresponse | occurs when an individual chosen for the sample can't be contacted or refuses to participate |
| response bias | occurs when there is a systematic pattern of inaccurate answers to a survey question |
| Question word bias | manipulate answers by adding specific words to the question |
| observational study | observes individuals and measures variables of interest but does not attempt to influence *ONLY OBSERVE* |
| cross-sectional study | data are observed, measured, and collected at ONE point of time |
| retrospective or Case-control study | data are collected from the PAST by going back in time by examining records, interviews, etc |
| Prospective/longitudinal/cohort study | data is collected in the FUTURE by cohorts (groups) sharing common factors |
| response variable | measures outcome of study; y-axis |
| explanatory variable | explain/predict changes in response variable; x-axis |
| Confounding variable | 2 variables effect the response variable --> cannot be distinguished from eachother |
| experiment | deliberately imposes treatments (conditions) on individuals to measure their responses |
| placebo | treatment with no active ingredient |
| treatment | a specific condition applied to the individuals in an experiment |
| experimental unit | the object to which treatment is randomly assigned |
| human beings | subjects |
| factor | an explanatory variable that is manipulated and may cause a change in the response variable |
| levels | the different values of a factor |
| what happens when you make an experiment double blind | eliminates lurking variables |
| 4 C's 2 R's (Principle of Experimental Design) | random assignment, control, replication, comparison |
| random assignment | experimental units are assigned to treatments using a chance process --> balances the effects among the treatment groups |
| control | keeping other variables CONSTANT for all experimental units --> reduce affect of lurking variables |
| Replication | giving each treatment to enough experimental units so that a difference in the effects of the treatments can be distinguished from chance variation due to random assignment |
| completely randomized design | the experimental units are assigned to the treatments completely at random |
| block | a group of experimental units that are known before the experiment to be SIMILAR in some way that is expected to affect the response to the treatments *NOT FORMED AT RANDOM* |
| randomized block design | the random assignment of experimental units to treatments is carried out separately within each block |
| WHATS THE MORAL OF THE STORY --> how you end experimental designs | the moral of the story is: control what you can, block what you can't control, and randomize to create comparable groups |
| matched pairs design | compares 2 treatments that use a block of size 2. two VERY SIMILAR experimental units are paired and the two treatments are randomly assigned within each pair |
| sampling variability | different random samples of the same size from the same population produce different estimates *LARGER SAMPLE SIZE --> MORE PRECISE ESTIMATE* |
| statistical significance | when the observed results are TOO UNUSUAL to be explained by chance alone *TAMPERED WITH, NOT FAIR* |
Created by:
lilli.spears1