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STAT 121 > Exam 1: Glossary > Flashcards

Exam 1: Glossary Flashcards

1
Q

Block

A

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

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2
Q

Boxplot

A

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

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3
Q

causation

A

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

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4
Q

center

A

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

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5
Q

continuous random variable

A

a variable that can take on any possible value

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6
Q

control treatment

A

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

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7
Q

convenience sample

A

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.

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8
Q

density curve

A

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

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9
Q

density curve

A

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

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10
Q

deviation

A

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.

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11
Q

discrete random variable

A

A random variable that can only take on certain specific values

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12
Q

distribution

A

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

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12
Q

distribution

A

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

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13
Q

empirical (observational) probability

A

probability obtained from repeating an experiment many times

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13
Q

empirical (observational) probability

A

probability obtained from repeating an experiment many times

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14
Q

experiment

A

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

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14
Q

experiment

A

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

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15
Q

explanatory variable

A

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

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16
Q

first quartile (Q1)

A

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.

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17
Q

five number summary

A

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

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18
Q

flagged value

A

A value that is a possible outlier

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19
Q

histogram

A

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.

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20
Q

individual

A

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

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20
Q

individual

A

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

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21
Q

inference

A

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

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22
Q

interquartile range (IQR)

A

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

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23
Q

interviewer bias

A

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

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24
Q

law of large numbers

A

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

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24
Q

law of large numbers

A

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

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25
Q

lurking variable

A

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

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26
Q

matched-pairs design

A

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.

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27
Q

maximum

A

The largest value in a data set.

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28
Q

mean

A

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.

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29
Q

measurement

A

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

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30
Q

median (Q2)

A

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

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31
Q

minimum

A

The smallest value in a data set.

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32
Q

multistage sampling

A

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.

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33
Q

multistage sampling

A

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.

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34
Q

non-response bias

A

Bias introduced into survey results because individuals refuse to participate.

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35
Q

non-response bias

A

Bias introduced into survey results because individuals refuse to participate.

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36
Q

Normal distribution

A

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

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37
Q

observational study

A

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.)

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38
Q

observed effect

A

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

39
Q

outlier

A

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.

40
Q

placebo

A

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

41
Q

population

A

The entire group of individuals of interest in a study.

41
Q

population

A

The entire group of individuals of interest in a study.

42
Q

population mean (μ)

A

Mean of all the observations in the population

43
Q

population standard deviation (𝛔)​

A

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

43
Q

population standard deviation (𝛔)​

A

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

44
Q

probability distribution

A

All possible events and their associated probabilities

45
Q

probability sample

A

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

46
Q

quantitative variable

A

A variable with numerical values such as height or weight.

47
Q

quantitative variable

A

A variable with numerical values such as height or weight.

48
Q

question order bias

A

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

49
Q

question wording bias

A

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

50
Q

quota sample

A

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

51
Q

random number table

A

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.)

52
Q

random number table

A

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.)

53
Q

randomization

A

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.

Purpose: Elminate bias associated with lurking variables. Ex: Caffine, if people choose maybe they didn’t get any sleep the night before

54
Q

randomized block design (RBD)

A

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

55
Q

randomized controlled experiment

A

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

55
Q

randomized controlled experiment

A

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

56
Q

range

A

The maximum observation minus the minimum observation

57
Q

relative frequency

A

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

57
Q

relative frequency

A

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

58
Q

replication

A

Having more than one individual per treatment in an experiment. (Note: Replication is NOT same as reproducibility of results or repetition of an experiment.)

58
Q

replication

A

Having more than one individual per treatment in an experiment. (Note: Replication is NOT same as reproducibility of results or repetition of an experiment.)

59
Q

response variable

A

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

59
Q

response variable

A

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

60
Q

sample

A

The subset of the population that we actually examine and measure

61
Q

sample mean (x-bar)

A

Average of data in a sample.

62
Q

standard deviation rule

A

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

63
Q

sample variable

A

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

64
Q

Shape of a distribution

A

Whether the data is bell-shaped or skewed

65
Q

side-by-side boxplots

A

Two or more boxplots displayed on the same scale

66
Q

simple random sample (SRS):

A

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.

67
Q

spread

A

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

67
Q

spread

A

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

68
Q

standard deviation

A

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

69
Q

standard Normal distribution

A

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.

69
Q

standard Normal distribution

A

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.

70
Q

standard normal table

A

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

71
Q

standardized value

A

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

72
Q

standardized value

A

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

73
Q

statistic

A

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

73
Q

statistic

A

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

74
Q

statistics

A

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.

75
Q

stem plot (also called stem and leaf plot)

A

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.

76
Q

stem plot (also called stem and leaf plot)

A

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.

77
Q

stratified sample

A

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

77
Q

stratified sample

A

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

78
Q

subject

A

An individual or unit in a study, usually a person

78
Q

subject

A

An individual or unit in a study, usually a person

79
Q

theoretical (classical) probability

A

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

79
Q

theoretical (classical) probability

A

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

80
Q

third quartile (Q3)

A

​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.

80
Q

third quartile (Q3)

A

​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.

81
Q

treatment

A

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.

82
Q

under-coverage bias

A

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

82
Q

under-coverage bias

A

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

83
Q

variable

A

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

84
Q

variable

A

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

85
Q

voluntary response

A

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

86
Q

voluntary response

A

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

87
Q

z-score

A

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

88
Q 
x-bar ( x ): Sample mean
s: Sample standard deviation
μ: Mean of a population
σ: Standard deviation of a population
n: The number of observations in a sample
N: Population size
N(μ,σ): Normal distribution with mean, μ, and standard deviation, σ
z = x−μ : z-score (standardized value) σ
A 
x-bar ( x ): Sample mean
s: Sample standard deviation
μ: Mean of a population
σ: Standard deviation of a population
n: The number of observations in a sample
N: Population size
N(μ,σ): Normal distribution with mean, μ, and standard deviation, σ
z = x−μ : z-score (standardized value) σ

STAT 121 (6 decks)

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