Review 1 Flashcards

(31 cards)

1
Q

Data Set

A

A collection of objects or elements (e.g., numbers
or letters)

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2
Q

Population

A

The complete collection of all elements or subjects to be studied. The size is represented by N.

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3
Q

Sample

A

A subset of elements drawn from the population. The size is represented by n.

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4
Q

Random Sample

A

A sample that is selected randomly from the population so that each member has an equal chance of being chosen. Also called a simple random sample.

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5
Q

Statistics

A

The field of study concerned with collecting, organizing, summarizing, presenting, analyzing, interpreting and drawing conclusions from data.

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6
Q

Variable

A

A characteristic or attribute that can take on different values. Variables can be categorical (gender) or numerical (test score).

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7
Q

Frequency Distribution

A

An organized tabulation of the number of times each value of a variable occurs.

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8
Q

Relative Frequency

A

The frequency of a value expressed as a proportion or percentage of the total number of values.

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9
Q

Probability

A

A measure of the likelihood or chance that an event will occur, ranging from 0 (impossible) to 1 (certain).

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10
Q

Sample Space

A

The set of all possible outcomes of an experiment.

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11
Q

Event

A

A set of one or more outcomes of an experiment.

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12
Q

Probability Space

A

Contains the complete set of probabilities and can be represented by a Venn diagram.

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13
Q

Set

A

A collection of distinct objects or elements. Sets are represented with curly brackets {}.

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14
Q

Element

A

An individual member of a set.

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15
Q

Union

A

The set of all elements that are in set A, in set B, or in both sets. Written as A ∪ B.

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16
Q

Intersection

A

The set of all elements that are common to both set A and set B. Written as A ∩ B.

17
Q

Complement

A

The set of all elements not in the original set.

18
Q

Mutually Exclusive Events

A

Events that cannot both occur at the same time, so the probability of their intersection is 0.

19
Q

Addition Rule for Probability

A

For mutually exclusive events A and B, P(A or B) = P(A) + P(B)

20
Q

Subjective Probability

A

Based on personal judgment or belief rather than objective data.

21
Q

Objective Probability

A

Determined through logic, relative frequency, or other quantifiable means.

22
Q

Measures of Central Tendency

A

Common measures include the mean, median and mode.

23
Q

Measures of Variability

A

Include range, interquartile range, variance and standard deviation.

24
Q

Graphical Displays

A

Useful for exploring and summarizing data, such as histograms, box plots, scatter plots.

25
Probability Distributions
Assign probabilities to all possible outcomes of a random variable based on its behavior. Common examples include the binomial and normal distributions.
26
Random Number
no one will have the same set of values
27
RANDBETWEEN()
Returns a random number between the numbers you specify, inclusive, universally distributed
28
RAND()
Returns a random number > = 0 < 1, uniformly distributed (i.e., each number has an equal chance of being chosen).
29
Venn Diagram
uses circles that overlap or don't overlap to show the commonalities and differences among things or groups of things
30
Collectively Exhaustive
A set of probabilities that covers all the probability space.
31
Logic
Used to determine the probability of an event without performing a series of trials through intuition