AP STAT exam review 1
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| 286356598 | stem and leaf plot, dot plot | name two types of quantitative plots from which the original data can be recovered | |
| 286356599 | the standard deviation squared | the variance | |
| 286356600 | Q3-Q1 | IQR | |
| 286356601 | median > mean | a distribution is skewed to the left | |
| 286356602 | median < mean | a distribution that is skewed to the right | |
| 286356603 | mean = median | a symmetric distribution | |
| 286356604 | quantitative | the number of years each of your teachers has taught | |
| 286356605 | categorical | classifying a statistic as quantitative or qualitative | |
| 286356606 | 1.5(IQR) add to the third quartile, subtract from the first quartile... | find outliers | |
| 286356607 | 99.7,95,68 | distribution of scores percentages | |
| 286356608 | residual | how far away from the LSRL the point is...above= positive, below=negative | |
| 286356609 | simpsons paradox | phenomenon when a third variable is thrown into the observation amd tje association changes | |
| 286356610 | no | do influential points necessarily have large residuals | |
| 286356611 | LSRL will change significantly | what happens if you remove influential points from a data set | |
| 286356612 | 1 or -1 | what numbers = perfect correlational relationships | |
| 286356613 | stratified | sampling technique | |
| 286356614 | blocking | a design technique | |
| 286356615 | control, randomization, and replication | three principles of experimental design | |
| 286356616 | stratified sampling | subgroups are homogenous | |
| 286356617 | cluster sampling | subrgroups are heterogenous | |
| 286356618 | Confounding Variables | factors that cause differences between the experimental group and the control group other than the independent variable | |
| 286356619 | convenience sampling | create a sample by using data from population members that are readily available | |
| 286356620 | response sampling | when cases systematically exclude themselves from the sample Can be helped by using oversampling or weighting cases | |
| 286356621 | matched pairs design | design where before and after experiments the same subjects are used for pre-testing and post-testing a treatment | |
| 286356622 | completely randomized design | An experimental design where all individuals participating in the experiment are assigned at random to the treatments and have equal chances. | |
| 286356623 | binomial probability model | the variable of interest is the number of successes in a fixed number of trials; counts the number of successes in a certain number of trials | |
| 286356624 | geometric probability model | the variable of interest is how many trials it takes to obtain the first success. |