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Stats 121 > Midterm 1 Glossary > Flashcards

Midterm 1 Glossary Flashcards

1
Q

A group of experimental units sharing some common characteristic. In a randomized complete block design, random allocation of treatments is carried out separately within each group

A

block

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2
Q

A plot of data that incorporates the maximum observation, the minimum observation, the first quartile, the second quartile (median), and the third quartile.

A

boxplot

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3
Q

Changes in the explanatory variable directly affect the response variable. Experiments are needed to verify

A

causation

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4
Q

A summary number about which observations tend to cluster. Measures of center include the mean and the median

A

center

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5
Q

a variable that can take on any possible value

A

continuous random variable

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6
Q

A treatment where no experimental condition is applied to the units in order to determine whether the active treatments affect the response. This enables the researcher to “control” for lurking variables

A

control treatment

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7
Q

A sample type where the researcher contacts those subjects who are readily available and does not use any random selection. The results are almost always biased.

A

convenience sample

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8
Q

​A mathematical model used to describe the overall pattern of the distribution of a random variable.

A

density curve

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9
Q

The difference (distance) between an observation and the mean of all the observations in a data set, or the difference between an observation and the corresponding regression model estimate.

A

deviation

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10
Q

A random variable that can only take on certain specific values

A

discrete random variable

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11
Q

A list of all possible values of a variable together with the frequency (or probability) of each value

A

distribution

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12
Q

probability obtained from repeating an experiment many times

A

empirical (observational) probability

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13
Q

A study where treatments are deliberately imposed on the individuals in the study before data is gathered in order to observe their responses to the treatment

A

experiment

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14
Q

A variable that may or may not explain the outcomes (responses) of a study, also called independent or predictor variable.

A

explanatory variable

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15
Q

​the median of the set of data less than the median of the whole data set, 25% of data is less than it, 75% is greater than it.

A

first quartile (Q1)

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16
Q

These five values: minimum, Q1, median, Q3, maximum; preferred numerical summary when data are very skewed or outliers are present.

A

five number summary

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17
Q

​A value that is a possible outlier

A

flagged value

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18
Q

A graphical display of a quantitative data set; data are grouped into intervals
(usually of equal width) and a bar is drawn over each interval having height proportional to the frequency (or percentage) of values in the interval. Values of the variable are given on the x axis and frequencies (or percentages) are given on the y axis. Histograms are examined to determine shape, center and spread.

A

histogram

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19
Q

Each object or unit described or examined in a data set.

A

individual​

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20
Q

Using results from a sample statistic value to draw conclusions about the population parameter

A

inference

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21
Q

The difference between Q3 and Q1 (i.e. Q3 – Q1); the length of the box in a boxplot; contains 50% of the data.

A

interquartile range (IQR)

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22
Q

Bias introduced into survey results by body language, voice intonation, gender, race, etc. of an interviewer

A

interviewer bias

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23
Q

The fact that the average of observed values in a sample ( x ) will tend to get closer and closer to as the sample size increases.

A

law of large numbers

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24
Q

A variable that the researcher is not necessarily interested in studying but which affects the relationship between the explanatory variable and the response variable.

A

lurking variable

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25
Q

A design of experiment that combines matching of subject or measurements with randomization. Either two measurements taken on each unit (such as pre and post) OR measurements taken on two individuals matched by some characteristics different from the explanatory variable and the response variable.

A

matched-pairs design

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26
Q

A measure of the center of the data; a value that “balances” the data; found by summing all the data and dividing by the number of data points.

A

mean

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27
Q

The largest value in a data set

A

maximum

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28
Q

A recorded fact about an individual; may be either numerical (quantitative) or qualitative (categorical).

A

measurement

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29
Q

A measure of the center of data; a value that splits the data in half; the “middle” number after the data have been sorted.

A

median (Q2)

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30
Q

The smallest value in a data set.

A

minimum

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31
Q

A type of sample from a population that has groups and sub-groups. First, some groups are randomly selected, and then some sub-groups from within the selected groups are randomly sampled. Finally, individuals are randomly selected from within the sampled sub-groups. This can be extended to sub-sub-groups, etc.

A

multistage sampling

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32
Q

Bias introduced into survey results because individuals refuse to participate.

A

non-response bias

33
Q

​A bell-shaped, symmetric density curve that is often used as a model for data or other random variables; specified by µ and σ.

A

Normal distribution

34
Q

A study that merely observes conditions of individuals in a population and records information; the population is disturbed as little as possible. (Note: treatments are not imposed on individuals nor are individuals randomly assigned to treatment groups.)

A

observational study

35
Q

The difference between the observed value of the statistic and the hypothesized value of the corresponding parameter; (e.g. ​x ̄ – μ​0​).

A

observed effect

36
Q

An observation that falls outside the pattern of the data set. Outliers inflate the mean and often prevent us from using statistical procedures like the one sample t.

A

outlier

37
Q

A fake imitation treatment that resembles the real treatment in all respects except for the active ingredient.

A

placebo

38
Q

The entire group of individuals of interest in a study.

A

population

39
Q

Mean of all the observations in the population.

A

population mean (μ)

40
Q

The standard deviation of all observations in a population; a measure of the variability of all the population values about their mean.

A

population standard deviation (𝛔)

41
Q

​All possible events and their associated probabilities

A

probability distribution

42
Q

A sample chosen using some type of random device. The probability of any specific sample can be computed and is greater than zero.

A

probability sample

43
Q

A variable with numerical values such as height or weight.

A

quantitative variable

44
Q

A type of bias that can occur in sample surveys, in which the order of the question influences the responses of participants

A

question order bias

45
Q

Sample results that differ from the truth because of the wording of the question used to obtain the information.

A

question wording bias

46
Q

A sample selected to fill quotas for different population characteristics like gender, race, age, etc

A

quota sample

47
Q

A table consisting of the digits 0 through 9 in equal proportions such that the digit in any position in the table is independent of the digits in neighboring positions (i.e., there is no pattern in the order of the digits.)

A

random number table

48
Q

A method of assigning experimental units to treatment groups that eliminates bias and gives each unit the same probability of being assigned to any treatment group.

A

randomization

49
Q

An experimental design where treatments are randomly allocated within each block.

A

randomized block design (RBD)

50
Q

An experimental design where all subjects are randomly allocated to different treatments

A

randomized controlled experiment

51
Q

The maximum observation minus the minimum observation

A

range

52
Q

a measure of how often a particular event occurs in a long series of trials

A

relative frequency

53
Q

Having more than one individual per treatment in an experiment.

A

replication
(Note: Replication is NOT same as reproducibility of results or repetition of an experiment.)

54
Q

A variable that gives the outcomes of interest of the study (may not be a number); also called the dependent variable.

A

response variable

55
Q

The subset of the population that we actually examine and measure

A

sample

56
Q

Average of data in a sample.

A

sample mean (x-bar)

57
Q

a normal distribution contains 68% of the data between one standard deviation above and below the mean, 95% of the data between two standard deviations above and below the mean, and 99.7% of data between three standard deviations above and below the mean

A

standard deviation rule

58
Q

obtained from a set of sample data, used to predict population variables

A

sample variable

59
Q

Whether the data is bell-shaped or skewed

A

shape of a distribution

60
Q

Two or more boxplots displayed on the same scale

A

side-by-side boxplots

61
Q

A sample of size n selected from the population in such a way that each possible sample of size n has an equal chance of being selected.

A

simple random sample (SRS)

62
Q

A summary number representing variability of the observations. Measures of spread include range, interquartile range, and standard deviation.

A

spread

63
Q

A measure of the “average” or typical deviation of the observations about the mean; measures variability of data about the mean.

A

standard deviation

64
Q

A normal distribution with mean of zero and standard deviation of one. Probabilities are given in a table for values of the standard normal variable.

A

standard Normal distribution

65
Q

Displays the area under the standard normal curve to the left of a z-score

A

standard normal table

66
Q

The z-score obtained from standardizing an x-value.

A

standardized value

67
Q

A number computed from sample data (without any knowledge of the value of a parameter) used to estimate the value of the parameter.

A

statistic

68
Q

The study of data analysis-collecting data, organizing and summarizing data, and drawing conclusions from sample data to answer research questions in the presence of variation.

A

statistics

69
Q

A graphical representation of a quantitative data set. Leading values of each data point are presented as stems and second digits are given as leaves.

A

stem plot (also called stem and leaf plot)

70
Q

A sampling scheme where the population is divided into strata according to some characteristic and a simple random sample is selected from each strata.

A

stratified sample

71
Q

An individual or unit in a study, usually a person

A

Subject

72
Q

“logical” probability, one divided by the total number of possible outcomes

A

theoretical (classical) probability

73
Q

​the median of the set of data greater than the median of the whole data set, 75% of data is less than it, 25% is greater than it.

A

third quartile (Q3)

74
Q

The condition or conditions applied to a subject or individual in an experiment; a placebo or no treatment is often considered a treatment. The collection of treatments is the explanatory variable.

A

treatment

75
Q

Bias that occurs in sample results because a segment of the population with a certain characteristic is not sampled.

A

under-coverage bias

76
Q

Any characteristic of an individual or object; it may take on any number of values either categorical or numerical.

A

variable

77
Q

A method of sample selection that consists of people choosing themselves by responding to a general appeal.

A

voluntary response

78
Q

The number of standard deviations a value or observation is from the mean; a standardized x-value (i.e. z = (x - µ) / σ )

A

z-score

Stats 121 (3 decks)

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