Introductory Statistics by OpenStax Chapter 1 Flashcards

1
Q

also called mean; A number that describes the central tendency of the data

A

Average

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2
Q

Not telling participants which treatment a subject is receiving

A

Blinding

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3
Q

Variables that take on values that are names or labels

A

Categorical Variable

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4
Q

a method for selecting a random sample and dividing the population into groups; use simple random sampling to select a set of clusters. Every individual chosen in the clusters is included in the sample

A

Cluster sampling

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5
Q

a random variable (RV) whose outcomes are measured; i.e. the height of trees in the forest

A

Control Group

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6
Q

a nonrandom method of selecting a sample; this method selects individuals that are easily accessible and may result in biased data

A

Convenience Sampling

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7
Q

The term applies to an ordered set of observations from smallest to largest. It is the sum of the relative frequencies for all values that are less than or equal to the given value

A

Cumulative Relative Frequency

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8
Q

a set of observations (a set of possible outcomes)

A

Data

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8
Q

a random variable (RV) whose outcomes are counted

A

Discrete Random Variable

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9
Q

the act of blinding both the subjects of an experiment and the researchers who work with the subjects

A

Double-blinding

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10
Q

any individual or object to be measured

A

Experimental Unit

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11
Q

the independent variable in an experiment; the value controlled by researchers

A

Explanatory Variable

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12
Q

the number of times a value of the data occurs

A

Frequency

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13
Q

Any human subject in a research study must be cognizant of any risk or costs associated with the study. The subject has the right to know the nature of the treatments included in the study, their potential risks, and their potential benefits. Consent must be given freely by an informed, fit participant

A

Informed Consent

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14
Q

a committee tasked with oversight of research programs that involve human subjects

A

Institutional Review Board

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15
Q

a variable that has an effect on a study even though it is neither an explanatory variable nor a response variable

A

Lurking Variable

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16
Q

an issue that affects the reliability of sampling data other than natural variation; it includes a variety of human errors including poor study design, biased sampling methods, inaccurate information provided by study participants, data entry errors, and poor analysis.

A

Nonsampling Error

17
Q

variables that take on values that are indicated by numbers

A

Numerical Variable

18
Q

a number that is used to represent a population characteristic and that generally cannot be determined easily

19
Q

an inactive treatment that has no real effect on the explanatory variable

20
Q

all individuals, objects, or measurements whose properties are being studied

A

Population

21
Q

the number of success divided by the total numbers in the sample

A

Proportion

21
Q

a number between zero and one, inclusive, that gives the likelihood that a specific event will occur

A

Probability

22
Q

an attribute whose value is indicated by a label

A

Qualitive Data

23
an attribute whose value is indicated by a number
Quantitive Data
24
the act of organizing experimental units into treatment groups using random methods
Random Assignment
25
a method of selecting a sample that gives every member of the population an equal chance of being selected
Random Sampling
26
a subset of the population that has the same characteristics as the population
Representative Sample
27
the ratio of the number of times a value of the data occurs in the set of all outcomes to the number of all outcomes to the total number of outcomes
Relative Frequency
28
the dependent variable in an experiment; the value that is measured for change at the end of an experiment
Response variable
29
a subset of the population studies
Sample
30
not all members of the population are equally likely to be selected
Sampling Bias
31
the natural variation that results from selecting a sample to represent a larger population; this variation decreases as the sample size increases, so selecting larger samples reduces this
Sampling Error
32
Once a member of the population is selected for inclusion in a sample, that member is returned to the population for the selection of the next individual
Sampling with Replacement
33
A member of the population may be chosen for inclusion in a sample only once. If chosen, the member is not returned to the population before the next selection
Sampling without Replacement
34
a straightforward method for selecting a random sample; give each member of the population a number. Use a random number generator to select a set of labels. These randomly selected labels identify the members of your sample
Simple Random Sampling
35
a numerical characteristic of the sample
Statistic
36
a method for selecting a random sample used to ensure that subgroups of the population are represented adequately; divide the population into groups (strata). Use simple random sampling to identify a proportionate number of individuals from each stratum
Stratified Sampling
37
a method for selecting a random sample; list the members of the population. Use simple random sampling to select a starting point in the population. Let k = (number of individuals in the population)/(number of individuals needed in the sample). Choose every kth individual in the list starting with the one that was randomly selected. If necessary, return to the beginning of the population list to complete your sample
Systematic sampling
38
different values or components of the explanatory variable applied in an experiment
Treatments
39
a characteristic of interest for each person or object in a population
Variable