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Stats Chap 1.3
Terms from 1.3
| Term | Definition |
|---|---|
| Observational Study | A researcher observes and measures characteristics of interest or part of a population, but does not change existing conditions. (Part of Data collection) |
| Experiment | A treatment is applied to part of a population, called the treatment group, and responses are observed. (Part of Data collection) |
| Simulation | Uses a mathematical or physical model to reproduce the conditions of a situation or process. This often involves computers, saves time and money, and allows the study of situations that can be impractical or dangerous to create irl |
| Survey | Carried out on people by asking them questions. Important that questions are worded in unbiased way. (Part of Data collection) |
| 3 Key Elements of a Well Designed Experiment | Control, Randomization, & Replication |
| Designing a Statistical Study | 1)Identify variables of interest&population of study. 2)Develop detailed plan for collecting data. 3)Collect the data. 4)Describe data using descriptive stats techniques 5)Interpret data & make decisions using inferential stats. 6)Identify possible errors |
| Placebo | A harmless fake treatment that is made to look like the real treatment. |
| Confounding Variables | Occurs when an experimenter can't tell the difference between the effects of different factors of a variable. (Part of Experimental Design) |
| Blinding | A technique where the subject does not know whether they are receiving a treatment or a placebo. (Part of Experimental Design) |
| Double-Blind | Neither the subject nor the experimenter know if the subject is receiving a treatment or a placebo. (Part of Experimental Design) |
| Randomization | A process of randomly assigning subjects to different treatment groups. (Part of Experimental Design) |
| Completely Randomized Design | Subjects are assigned to different treatment groups through random selection. |
| Randomized Block Design | Divide subjects w/ similar characteristics into blocks, and then w/n each block, randomly asking subjects to treatment groups. |
| Matched-Pairs Design | Subjects are paired up according to similarity. One subject of the pair is randomly selected to receive on treatment while the other subject receives a different treatment. (Part of Experimental Design) |
| Sample Size | The # of subjects in a study is very important to experimental design. (Part of Experimental Design) |
| Replication | The repetition of an experiment using a large group of subjects. (Part of Experimental Design) |
| Census | A count or measure of an entire population. Can be difficult or costly to perform. (Part of Sampling Techniques) |
| Sampling | A count or measure of part of a population, and is more commonly used. (Part of Sampling Techniques) |
| Random Sample | Every member of the population has an equal chance of being selected. (Part of Sampling Techniques) |
| Simple Random Sample | Every possible sample of the same size has the same chance of being selected. (Part of Sampling Techniques) |
| Stratified Sample | Divide a population into groups (strata) and select a random sample from each group. (Part of Sampling Techniques) |
| Cluster Sample | Divide the population into groups (clusters) and select all of the members in one or more, but not all, of the clusters. (Part of Sampling Techniques) |
| Systematic Sample | Choose a starting value at random. Then choose every Kth (Xth) member of the population. (Part of Sampling Techniques) |
| Convenience Sample | Choose only members of the population that are easy to get. Often leads to biased results. NOT recommended. (Part of Sampling Techniques) |
Created by:
Tain45
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