Review Vocabulary

Bias A systematic error that tends to cause the observations to deviate in the same direction from the truth about the population whenever a sample or experiment is repeated. (p. 295)

Confidence interval An interval of values used to estimate a population parameter with a specific level of confidence. A 95% confidence interval is an interval computed from a sample by a method that surrounds the unknown parameter 95% of the time, so when we calculate the interval for a single sample, we are 95% confident that the interval contains the unknown parameter. (pp. p. 320 p. 321)

Confounding Two variables are confounded when their effects on the outcome of a study cannot be distinguished from each other. (pp. p. 306 p. 307)

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Control group A group of experimental subjects that is given a standard treatment, no treatment, or a fake treatment (such as a placebo). (p. 307)

Convenience sample A sample that consists of individuals who are easily reachable, such as people passing by on the street. A convenience sample is usually biased. (p. 294)

Double-blind experiment An experiment in which neither the experimental subjects nor the persons who interact with them know which treatment each subject received. (p. 310)

Experiment A study in which treatments are applied to people, animals, or things to observe the effect of such treatments. (p. 305)

Margin of error The number to the right of the ± sign in a 95% confidence interval and equal to half of the width of the full interval. For a 95% confidence interval, it equals about 2 standard deviations of the sampling distribution of the estimated parameter. If you conducted a very large number of polls, about 95% of the time the difference between a particular poll’s result and the true value of the population parameter would be within the margin of error. (p. 321)

Nonresponse Some individuals chosen for a sample cannot be contacted or refuse to participate. (p. 303)

Observational study A study (e.g., a sample survey) that observes individuals and measures variables of interest but does not attempt to influence the responses. (p. 311)

Parameter A number that describes some characteristic of the population. In statistical inference, the goal is often to estimate an unknown parameter or make a decision about its value. (p. 315)

Placebo effect The beneficial effect of a dummy treatment (such as an inert pill in a medical experiment) on the response of subjects. (p. 310)

Population The entire group of people or things about which we want information. (p. 292)

Prospective study An observational study that follows two or more groups of subjects forward in time. (p. 312)

Randomized comparative experiment An experiment to compare two or more treatments in which people, animals, or things are assigned to treatments by chance. (p. 307)

Retrospective study An observational study that uses interviews or records to collect information about past behaviors of subjects in two or more groups. (p. 312)

Sample A part of the population that is actually observed and used to draw conclusions, or inferences, about the entire population. (p. 292)

Sample proportion The proportion of the members of a sample having some characteristic (e.g., agreeing with an opinion poll question). The sample proportion from a simple random sample is used to estimate the corresponding proportion in the population from which the sample was drawn. (p. 317)

Sampling distribution The distribution of values taken by a statistic when all possible random samples of the same size are drawn from the same population. The sampling distributions of sample proportions are approximately normal. (p. 317)

Simple random sample (SRS) A sample chosen by chance, so that every possible sample of the same size has an equal chance of being selected. (p. 297)

Statistic A number that describes a sample. A statistic can be calculated from the sample data alone; it does not involve any unknown parameters of the population. (p. 315)

Statistical inference Methods for drawing conclusions about an entire population on the basis of data from a sample. Confidence intervals are one type of inference method. (p. 314)

Statistically significant An observed effect is statistically significant if it is so large that it is unlikely to occur just by chance in the absence of a real effect in the population from which the data were drawn. (p. 308)

Table of random digits A table whose entries are the digits 0, 1, 2, 3, 4, 5, 6, 7, 8, 9 in a completely random order. That is, each entry is equally likely to be any of the 10 digits and no entry gives information about any other entry. (p. 297)

Undercoverage The process of choosing a sample may systematically leave out some groups in the population, such as households without landline telephones. (p. 302)

Voluntary response sample A sample of people who select themselves by responding to a general invitation to give their opinions. Such a sample is usually strongly biased. (p. 296)