Exam 1 Flashcards

(57 cards)

1
Q

Frequency Distribution

A

A table that lists each possible value of a QUALITATIVE variable with the number of occurrences within a data set

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2
Q

Class

A

Qualitative data can be classified into this category

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3
Q

Class frequency

A

Number of observations in a data set that fall into a class

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4
Q

Class relative frequency

A

The class frequency / the total number of observations. Should total to 1, a ratio.

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5
Q

Class Interval

A

Involved in quantitative data where classes aren’t naturally occurring, therefore it would be the intervals on the x-axis

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6
Q

Skewed left

A

Mean < Median

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7
Q

Skewed Right

A

Mean > Median

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8
Q

Kurtosis

A

Measure of the amount of outliers a data set encompasses

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9
Q

Histogram

A

A graph that groups together similar values

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10
Q

Bar graph

A

A graph that displays classes of qualitative variables

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11
Q

Low standard deviation

A

Centered around the mean

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12
Q

High standard deviation

A

Spread out across a range of values

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13
Q

Experimental/Observational unit

A

An object from which we collect data

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14
Q

Population

A

Set of all units we are interested in studying

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15
Q

Sample

A

A subset of the population

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16
Q

Variable

A

A characteristic/property of an individual, usually being measured

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17
Q

Descriptive Statistics

A

Utilizes graphical methods in order to look for patterns and summarize the data set

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18
Q

Inferential statistics

A

Utilizes sample data to extend upon a population in order to make predictions and decisions

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19
Q

Discrete variable

A

Countable

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20
Q

Continuous Variable

A

Must be measured

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21
Q

Z-Score

A

The distance a data value is from the mean in terms of standard deviations

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22
Q

Boxplot

A

In descriptive statistics, it’s used to graphically demonstrate the spread of a dataset

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23
Q

IQR

A

Interquartile Range. 75th quartile - 25th quartile

24
Q

Unimodal

A

Involves one mode, one single highest value

25
Empirical Rule
68-95-99.7
26
Probability
The measure of likelihood of a random phenomenon or chance occurring. Describes what will happen short-term by looking at what will happen long-term
27
Experiment
A process that leads to a single outcome that cannot be predicted with certainty
28
Sample Point
Most basic outcome of an experiment
29
Sample Space
A collection of all possible data points
30
Event
Specific collection of data points
31
Probability of an event happening:
P(x) = Event / Sample Space
32
Combination
A collection without order and without repetition
33
Union
Sample points belonging to both A and B or points belonging to A OR B
34
Intersection
Sample points belonging to both A AND B
35
Complement Rule Formula
P(x) = P(A) + P(A^c)=1
36
Conditional Probability
Takes into account additional info about the results of an experiment
37
Events are independent if:
The occurrence of Event E doesn't affect the probability of Event F. And vv
38
What do the words "at least" signify?
The complement rule
39
Complement
The event doesn't occur, or the event consisting of all sample points that are not in Event A
40
Permutation
Arrangement of objects in a definite order and sequence
41
If numbers are allowed to repeat, what rule should you use?
Multiplication Rule
42
Conditional Probability of AB
To find that Event A occurs given that Event B occurs
43
Additive Rule
P(A) + P(B) - P(A(intersection)B)
44
Conditional Probability Formula of AB
(P(A(intersection)B) / P(B) (Take the intersection of the 2 events / the event that is given
45
Multiplicative Rule of Probability
P(A(intersection)B) = P(A) * P(BA) or P(B) * P(AB)
46
Events are independent if
The occurrence of Event E doesn't affect the probability of Event F
47
Intersection of Independent Events Formula
A * B
48
Union of Independent Events Formula
A + B - (intersection)
49
Events are Independent if
P(AB) = P(A) or P(BA) = P(B)
50
Are mutually exclusive and independent the same thing?
NO!
51
Multiplicative Rule of Counting
n1 * n2 * n3 * ... * nk
52
Permutations Rule of Counting
N! / (N-n)! Arranging them in a DISTINCT ORDER
53
Partitions Rule of Counting
N! / n1! * n2! * n3! * ... * nk! Partitioning the elements of a set of N elements into k GROUPS
54
Combinations Rule of Counting
N! / n! (N-n)!
55
To be mutually exclusive, P(A(intersection)B) =
0
56
N
The number of things from which you can choose from
57
n
The number of things that will be chosen