Introduction to AP Statistics: Common Terms
Terms : Hide Images
| 198449222 | statistics | the science of collecting, analyzing, and interpreting data | |
| 198449223 | data, datum | the numbers or information collected in a study or experiment | |
| 198449224 | variable | any characteristic of a person or thing that can be expressed as a number | |
| 198449225 | quantitative data | (numerical) data, numerical values for which arithmetic operations make sense | |
| 198449226 | categorical data | also called count data, simply records which category a person or thing falls into | |
| 198449227 | descriptive statistics | methods of organizing, displaying, and describing data using tables, graphs, and summary measures | |
| 198449228 | inferential statistics | uses collected data to make generalizations about the entire group (never with complete certainty, can not be used to make predictions about individual cases) | |
| 198449229 | population | the entire group to be studied | |
| 198449230 | sample | the part of the population actually examined | |
| 198449231 | statistic | a numerical measurement describing some characteristics of a sample | |
| 198449232 | parameter | a numerical measurement describing some characteristics of a population | |
| 198449233 | discrete data | values are only isolated points on the number line | |
| 198449234 | continuous data | values form an entire interval on the number (measurement is often needed) | |
| 198449235 | observational study | no treatment is assigned; the researchers merely observe a characteristic | |
| 198449236 | experimental study | uses a deliberate treatment to observe the response and measures its effect | |
| 198449237 | confounding/lurking variable | a variable that has an important effect on the response but is not included among the explanatory variables studied | |
| 198449238 | census | an attempt to include the entire population | |
| 198449239 | bias | when a study systematically favors certain outcomes (selection, measurement, nonresponse) | |
| 198449240 | randomization | the use of chance to assign subjects to different treatments to eliminate bias | |
| 198449241 | simple random sample | every unit has an equal chance of being selected and all combinations of subjects are possible | |
| 198449242 | stratified random sample | the population is divided into groups (strata), then this is selected from each group | |
| 198449243 | systematic random sample | a system such as choosing every fourth subject is used | |
| 198449244 | explanatory variable | explains the observed outcome (most often the x-variable) | |
| 198449245 | response variable | measures an outcome of the study (most often the y-variable in bivariate data) | |
| 198449246 | experimental units | objects on which the experiment is performed | |
| 198449247 | subjects | human experimental units | |
| 198449248 | treatment | the specific experimental process applied to each case | |
| 198449249 | control group | a group given no treatment or a sham treatment | |
| 198449250 | placebo | a dummy or sham treatment such as a sugar pill | |
| 198449251 | block design | a group that is known to be similar before the experiment in some way that is expected to affect the response to the treatment; used to reduce variation | |
| 198449252 | double blind experiment | neither the subject nor the evaluators know which treatment the subject receives | |
| 198449253 | statistical significance | a difference too large to be attributed to chance | |
| 198449254 | voluntary response samples | only those who choose to respond are evaluated; usu. very biased | |
| 198449255 | independence | knowing whether one event occurs does not alter the chance of another event occurring | |
| 198449256 | association vs. causation | just because things are associated does not mean one causes the other | |
| 198449257 | disjoint/mutually exclusive | events have no outcomes in common | |
| 198449258 | 3 questions to ask about data | 1. What variable is being measured? 2. What instrument do I use to measure? 3. What units do I measure in? | |
| 198449259 | 3 Principles of Experimental Design | 1. Control 2. Randomize 3. Replicate | |
| 198449260 | Cautions about Experimentation | 1. hidden bias 2. lack of realism | |
| 198449261 | Cautions about Sample Surveys | 1. undercoverage 2. nonresponse 3. response bias 4. wording of questions | |
| 204875130 | undercoverage | gives a part of the population less representation than it has in the population | |
| 204875131 | nonresponse | when a large fraction of those sampled fails to respond | |
| 204875132 | response bias | anything in a survey design that influences responses | |
| 204875133 | wording of question bias | may suggest a favored response | |
| 204875134 | matching | any attempt to force a sample to resemble specified attributes of the population | |
| 204875135 | simulation | models random events by using random numbers to specify event outcomes with relative frequencies | |
| 204875136 | simulation component | the most basic situation in which something happens at random | |
| 204875137 | factor | a variable whose levels are controlled by the experimenter | |
| 204875138 | level | the specific values that the experimenter chooses for a factor | |
| 204875139 | retrospective study | an observational study in which subjects are selected and then their previous conditions or behaviors are determined | |
| 204875140 | prospective study | an observational study in which subjects are followed to observe future outcomes |
