AP Statistics vocabulary.
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| 6556151033 | context | ideally tells who was measured, what was measured, how the data were collected, where the data were collected, and when and why the study was performed | 0 | |
| 6556151034 | data | systematically recorded information, whether numbers or labels, together with its context | 1 | |
| 6556151035 | data table | an arrangement of data in which each row represents a case and each column represents a variable | 2 | |
| 6556151036 | variable | holds information about the same characteristic for many cases | 3 | |
| 6556151037 | categorical variable | a variable that names categories (whether with words or numerals) | 4 | |
| 6556151038 | quantitative variable | a variable in which the numbers act as numerical values; always has units | 5 | |
| 6556151039 | frequency table | lists the categories in a categorical variable and gives the count or percentage of observations for each category | 6 | |
| 6556151040 | bar chart | shows a bar representing the count of each category in a categorical variable | 7 | |
| 6556151041 | pie chart | shows how a "whole" divides into categories by showing a wedge of a circle whose area corresponds to the proportion in each category | 8 | |
| 6556151042 | marginal distribution | the distribution of either variable alone in a contingency table; the counts or percentages are the totals found in the margins (last row or column) of the table | 9 | |
| 6556151043 | conditional distribution | the distribution of a variable restricting the who to consider only a smaller group of individuals | 10 | |
| 6556151044 | independence | variables are said to be this if the conditional distribution of one variable is the same for each category of the other | 11 | |
| 6556151045 | distribution | gives the possible values of the variable and the frequency or relative frequency of each value | 12 | |
| 6556151046 | histogram | uses adjacent bars to show the distribution of vales in a quantitative variable; each bar represents the frequency (or relative frequency) of values falling in an interval of values | 13 | |
| 6556151047 | stem-and-leaf display | shows quantitative data values in a way that sketches the distribution of the data | 14 | |
| 6556151048 | dotplot | graphs a dot for each case against a single axis | 15 | |
| 6556151049 | shape | to describe this aspect of a distribution, look for single vs. multiple modes, and symmetry vs. skewness | 16 | |
| 6556151050 | spread | a numerical summary of how tightly the values are clustered around the "center" | 17 | |
| 6556151051 | mode | a hump or local high point in the shape of the distribution of a variable; the apparent locations of these can change as the scale of a histogram is changed | 18 | |
| 6556151052 | unimodal | having one mode; this is a useful term for describing the shape of a histogram when it's generally mound-shaped | 19 | |
| 6556151053 | bimodal | distributions with two modes | 20 | |
| 6556151054 | uniform | a distribution that's roughly flat | 21 | |
| 6556151055 | symmetric | a distribution is this if the two halves on either side of the center look approximately like mirror images of each other | 22 | |
| 6556151056 | tails | the parts of a distribution that typically trail off on either side; they can be characterized as long or short | 23 | |
| 6556151057 | skewed | a distribution is this if it's not symmetric and one tail stretches out farther than the other | 24 | |
| 6556151058 | outliers | extreme values that don't appear to belong with the rest of the data | 25 | |
| 6556151059 | center | summarized with the mean or the median | 26 | |
| 6556151060 | median | the middle value with half of the data above and half below it | 27 | |
| 6556151061 | measures of spread | summarized with the standard deviation, interquartile range, and range | 28 | |
| 6556151062 | range | the difference between the lowest and highest values in a data set | 29 | |
| 6556151063 | quartile | the lower of this is the value with a quarter of the data below it; the upper of this has a quarter of the data above it | 30 | |
| 6556151064 | interquartile range | the difference between the first and third quartiles | 31 | |
| 6556151065 | percentile | the ith ___ is the number that falls above i% of the data | 32 | |
| 6556151066 | 5-number summary | consists of the minimum and maximum, the quartiles Q1 and Q3, and the median | 33 | |
| 6556151067 | boxplot | displays the 5-number summary as a central box with whiskers that extend to the non-outlying data values | 34 | |
| 6556151068 | mean | found by summing all the data values and dividing by the count | 35 | |
| 6556151069 | variance | the sum of squared deviations from the mean, divided by the count minus one | 36 | |
| 6556151070 | standard deviation | the square root of the variance- The typical distance from the mean | 37 | |
| 6556151071 | comparing distributions | when doing this, consider their shape, center, and spread in context | 38 | |
| 6556151072 | shifting | adding a constant to each data value adds the same constant to the mean, the median, and the quartiles, but does not change the standard deviation or IQR | 39 | |
| 6556151073 | rescaling | multiplying each data value by a constant multiplies both the measures of position and the measures of spread by that constant | 40 | |
| 6556151074 | standardizing | done to eliminate units; values can be compared and combined even if the original variables had different units and magnitudes | 41 | |
| 6556151075 | standardized value | value found by subtracting the mean and dividing by the standard deviation (z-score) | 42 | |
| 6556151076 | parameter | numerically valued attribute of a model | 43 | |
| 6556151077 | statistic | value calculated from data to summarize aspects of the data | 44 | |
| 6556151078 | z-score | tells how many standard deviations a value is from the mean; have a mean of zero and a standard deviation of one | 45 | |
| 6556151079 | standard normal model | a normal model with a mean of 0 and a standard deviation of 1 | 46 | |
| 6556151080 | 68-95-99.7 rule | in a normal model, about 68% of values fall within 1 standard deviation of the mean, about 95% fall within 2 standard deviations of the mean, and about 99.7% fall within 3 standard deviations of the mean | 47 | |
| 6556151081 | normal percentile | this corresponding to a z-score gives the percentage of values in a standard normal distribution found at that z-score or below | 48 | |
| 6556151082 | normal probability plot | a display to help assess whether a distribution of data is approximately normal; if it is nearly straight, the data satisfy the nearly normal condition | 49 | |
| 6556151083 | scatterplots | shows the relationship between two quantitative variables measured on the same cases | 50 | |
| 6556151084 | direction | a positive ____ or association means that, in general, as one variable increases, so does the other; when increases in one variable generally correspond to decreases in the other, the association is negative | 51 | |
| 6556151085 | form | the ____ we care about most is straight | 52 | |
| 6556151086 | strength | a scatterplot shows an association that is this if there is little scatter around the underlying relationship | 53 | |
| 6556151087 | correlation | a numerical measure of the direction and strength of a linear association | 54 | |
| 6556151088 | outlier | a point that does not fit the overall pattern seen in the scatterplot | 55 | |
| 6556151089 | lurking variable | a variable other than x and y that simultaneously affects both variables, accounting for the correlation between the two | 56 | |
| 6556151090 | model | an equation or formula that simplifies and represents reality | 57 | |
| 6556151091 | linear model | an equation of the form y-hat = b0 + b1x | 58 | |
| 6556151092 | residuals | the differences between data values and the corresponding values predicted by the regression model; ____ = observed value - predicted value | 59 | |
| 6556151093 | predicted value | found by substituting the x-value in the regression equation; they're the values on the fitted line | 60 | |
| 6556151094 | slope | gives a value in "y-units per x-unit"; changes of one unit in x are associated with changes of b1 units in predicted values of y | 61 | |
| 6556151095 | regression to the mean | each predicted y-hat tends to be fewer standard deviations from its mean than its corresponding x was from its mean | 62 | |
| 6556151096 | regression line | the linear equation y-hat = b0 + b1x that satisfies the least squares criterion | 63 | |
| 6556151097 | intercept | this, b0, gives a starting value in y-units; it's the y-hat-value when x is 0 | 64 | |
| 6556151098 | least squares | this criterion specifies the unique line that minimizes the variance of the residuals or, equivalently, the sum of the squared residuals | 65 | |
| 6556151099 | r^2 | the square of the correlation between y and x; gives the fraction of the variability of y accounted for by the least squares linear regression on x; an overall measure of how successful the regression is in linearly relating y to x | 66 | |
| 6556151100 | subset | if data consist of two or more groups that have been thrown together, it is usually best to fit different linear models to each group than to try to fit a single model to all of the data | 67 | |
| 6556151101 | extrapolation | although linear models provide an easy way to predict values of y for a given value of x, it is unsafe to predict for values of x far from the ones used to find the linear model equation; predictions should not be trusted | 68 | |
| 6556151102 | outlier | any data point that stands away from the others; can be extraordinary by having a large residual or by having high leverage | 69 | |
| 6556151103 | influential point | when omitting a point from the data results in a very different regression model, the point is an ____ | 70 | |
| 6556151104 | random | an event is this if we know what outcomes could happen, but not which particular values will happen | 71 | |
| 6556151105 | random numbers | these are hard to generate without bias, but several websites offer an unlimited supply of equally likely random values | 72 | |
| 6556151106 | simulation | models random events by using random numbers to specify event outcomes with relative frequencies that correspond to the true real-world relative frequencies we are trying to model | 73 | |
| 6556151107 | trial | the sequence of several components representing events that we are pretending will take place | 74 | |
| 6556151108 | response variable | values of this record the results of each trial with respect to what we were interested in | 75 | |
| 6556151109 | population | the entire group of individuals or instances about whom we hope to learn | 76 | |
| 6556151110 | sample | a representative subset of a population, examined in hope of learning about the population | 77 | |
| 6556151111 | sample survey | a study that asks questions of a sample drawn from some population in the hope of learning something about the entire population | 78 | |
| 6556151112 | bias | any systematic failure of a sampling method to represent its population; common errors are voluntary response, undercoverage, nonresponse ____, and response ____ | 79 | |
| 6556151113 | randomization | the best defense against bias, in which each individual is given a fair, random chance of selection | 80 | |
| 6556151114 | matching | any attempt to force a sample to resemble specified attributes of the population | 81 | |
| 6556151115 | sample size | the number of individuals in a sample | 82 | |
| 6556151116 | census | a sample that consists of the entire population | 83 | |
| 6556151117 | population parameter | a numerically valued attribute of a model for a population | 84 | |
| 6556151118 | representative | a sample is this if the statistics computed from it accurately reflect the corresponding population parameters | 85 | |
| 6556151119 | simple random sample | this of sample size n is one in which each set of n elements in the population has an equal chance of selection | 86 | |
| 6556151120 | sampling frame | a list of individuals from whom the sample is drawn | 87 | |
| 6556151121 | sampling variability | the natural tendency of randomly drawn samples to differ | 88 | |
| 6556151122 | stratified random sample | a sampling design in which the population is divided into several subpopulations, and random samples are then drawn from each stratum | 89 | |
| 6556151123 | cluster sample | a sampling design in which entire groups are chosen at random | 90 | |
| 6556151124 | multistage sample | sampling schemes that combine several sampling methods | 91 | |
| 6556151125 | systematic sample | a sample drawn by selecting individuals systematically from a sampling frame | 92 | |
| 6556151126 | voluntary response bias | bias introduced to a sample when individuals can choose on their own whether to participate in the sample | 93 | |
| 6556151127 | convenience sample | consists of the individuals who are conveniently available | 94 | |
| 6556151128 | undercoverage | a sampling scheme that biases the sample in a way that gives a part of the population less representation than it has in the population | 95 | |
| 6556151129 | nonresponse bias | bias introduced to a sample when a large fraction of those sampled fails to respond | 96 | |
| 6556151130 | response bias | anything in a survey design that influences response | 97 | |
| 6556151131 | observational study | a study based on data in which no manipulation of factors has been employed | 98 | |
| 6556151132 | experiment | manipulates factor levels to create treatments, randomly assigns subjects to these treatment levels, and then compares the responses of the subject groups across treatment levels | 99 | |
| 6556151133 | random assignment | to be valid, an experiment must assign experimental units to treatment groups at random | 100 | |
| 6556151134 | factor | a variable whose levels are controlled by the experimenter | 101 | |
| 6556151135 | response variable | a variable whose values are compared across different treatments | 102 | |
| 6556151136 | experimental units | individuals on which an experiment is performed | 103 | |
| 6556151137 | level | the specific values that the experimenter chooses for a factor | 104 | |
| 6556151138 | treatment | the process, intervention, or other controlled circumstance applied to randomly assigned experimental units | 105 | |
| 6556151139 | principles of experimental design | control, randomize, comparison, replicate | 106 | |
| 6556151140 | statistically significant | when an observed difference is too large for us to believe that is is likely to have occurred naturally | 107 | |
| 6556151141 | control group | the experimental units assigned to a baseline treatment level, typically either the default treatment, which is well understood, or a null, placebo treatment | 108 | |
| 6556151142 | blinding | any individual associated with an experiment who is not aware of how subjects have been allocated to treatment groups | 109 | |
| 6556151143 | single-blind | when either those who could influence or evaluate the results is blinded | 110 | |
| 6556151144 | double-blind | when both those who could influence and evaluate the results are blinded | 111 | |
| 6556151145 | placebo | a treatment known to have no effect, administered so that all groups experience the same conditions | 112 | |
| 6556151146 | placebo effect | the tendency of many human subjects (often 20% or more of experiment subjects) to show a response even when administered a placebo | 113 | |
| 6556151147 | block | when groups of experimental units are similar, it is a good idea to gather them together into these | 114 | |
| 6556151148 | matched | in a retrospective or prospective study, subjects who are similar in ways not under study may be ____ and then compared with each other on the variables of interest | 115 | |
| 6556151149 | randomized block design | randomization occurring within blocks | 116 | |
| 6556151150 | completely randomized design | all experimental units have an equal chance of receiving any treatment | 117 | |
| 6556151151 | confounded | when the levels of one factor are associated with the levels of another factor so their effects cannot be separated | 118 |
