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AP Statistics > All Statistics > Flashcards

All Statistics Flashcards

1
Q

Center

A

Mean, Median or Mode

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2
Q

Measures of Spread

A

How far apart the numbers are in relation to each other

Range, IQR, Variance and Standard Deviation

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3
Q

Shape

A

Symmetric, normal, skewed left, skewed right, uniform, bimodal

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4
Q

Variability

A

How spread out numbers in a set are in relation to each other. Measured by spread.

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5
Q

Box Plot

A

A graph of the 5 number summary

A modified box plot shows if the data set has outliers.

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6
Q

Stemplot

A

A graph for quantitative data. Each value of the data set is represented by a stem and a leaf. Each leaf may only be 1 digit. Stem plots may have rounded values in place of the actual data.

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7
Q

Histogram

A

Common distribution for one variable

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8
Q

Dot Plot

A

A simple graph for small data sets

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9
Q

Mean

A

Average

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10
Q

Median

A

The middle number in a data set when the numbers are in order.

Sometimes called Q2 or MED

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11
Q

Mode

A

Most common value within the data

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12
Q

Outliers

A

A value that doesnt follow the general trend of the data.

Upper limit = Q3 + 1.5(IQR)

Lower limit = Q1 - 1.5(IQR)

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13
Q

Standard Deviation

A

A measure of spread. The average distance from the mean.

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14
Q

Range

A

A measure of spread

Maximum-Minimum

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15
Q

5 Number Summary

A

Used in box plots

Min-Q1-Median-Q3-Max

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16
Q

Individuals

A

Person/object that is a member of the studied population

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17
Q

Quantitative

A

Numerical measures (order)

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18
Q

Qualitative

A

Classification of individuals based on attributes/characteristics (categorical, grouping)

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19
Q

Bar Graph

A

Used for categorical data

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20
Q

Ogive

A

A relative cumulative frequency histogram

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21
Q

Pie Chart

A

Categorical data separated into percentages

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22
Q

Symmetric

A

Equal on both sides

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23
Q

Minimum

A

Smallest value within the data

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24
Q

Q3

A

The median between the median and the maximum

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25
Q

Time Plot

A

Used to follow trends based on time (connecting)

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26
Q

Q1

A

Median between the minimum and median

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27
Q

Normal

A

Perfectly symmetric distribution

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28
Q

Uniform

A

Histogram with bars of all the same height

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29
Q

Bi-Modal

A

A graph with 2-peaks

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30
Q

Maximum

A

Largest value in the data set

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31
Q

Density Curve

A

On/above horizontal (x) axis; the area underneath is exactly 1

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32
Q

Inflection Points

A

The point where the graph changes from concave upward to concave downward

Approximately where one standard deviation lies from the mean

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33
Q

68-95-99.7 Rule

A

Empirical Rule

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34
Q

N(μ, σ)

A

Short-hand notation for normal distribution

N=Normal

Center=μ (mean)

Spread=σ (standard deviation)

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35
Q

Standard Normal Distribution

A

Mean=0

Standard Deviation=1

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36
Q

z = (x - μ) / σ

A

Normal Distribution Equation

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37
Q

Normal Probability Plot

A

Shows linearity

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38
Q

Explanatory Variable

A

x, input, independent

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39
Q

Response Variable

A

y, output, dependent

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40
Q

Scatterplot

A
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41
Q

Regression Outlier

A

f

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42
Q

Independent Variable

A

One event has no effect on the other

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43
Q

Dependent Variable

A

Two events have effects on eachother

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44
Q

Influential Observation

A

A point in a scatter plot that changes the regression line

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45
Q

LSRL

A
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46
Q

Positive Association

A

As x increases, y increases

As x decreases, y decreases

Positive correlation

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47
Q

Negative Association

A

As x increases, y decreases

As x decreases, y increases

Negative correlation

48
Q

Correlation

A

“r”

As r-value becomes closer to 1, the correlation becomes stronger

49
Q

Coefficient of Determination

A

r²

written as a decimal/percentage (% of the change in y is explained by the change in x)

50
Q

Regression Line

A

ŷ = a + bx

“line of best fit”

51
Q

Residual

A

observed - expected (y-ŷ)

52
Q

Slope

A

“b” value in ŷ=a+bx

53
Q

y-intercept

A

“a” value in ŷ=a+bx

54
Q

Residual Plot

A

A plot representing the x values and residual values (y-ŷ)

55
Q

Causation

A

Changes in x cause changes in y

56
Q

Extrapolation

A

When you predict for a value outside of the domain

57
Q

Confounding

A

effect of y on x, mixed up with effects on y with another variable, z

58
Q

Common Response

A

x and y respond to changes in unobserved variables

59
Q

Lurking Variable

A

variable that has an important effect on the relationship among variables in the study, but not included

60
Q

Conditional Distribution

A
61
Q

Marginal Distribution

A

Totals of rows and columns

62
Q

Observational Study

A

Does not attempt to influence responses; just observing

63
Q

Experiment

A

Deliberately imposes some treatment on individuals in order to observe their response

64
Q

Population

A

Entire group of individuals to be studied

65
Q

Sample

A

Subset of studied population

66
Q

Census

A

Attempting to contact every individual in population

67
Q

Bias

A

Systematically favoring certain outcomes

68
Q

Voluntary Response Sample

A

A sample from volunteers who are choosing to participate

69
Q

Convenience Sample

A

Choosing random participants for a sample convienently instead of stratigically

70
Q

SRS

A

Simple Random Sample

71
Q

Stratified Random Sample

A

Group(strata) by a common variable, then take SRS of each group (strata)

72
Q

Table of Random Digits

A

Used to choose subjects within a sample

73
Q

Undercoverage

A

Some group of the population left out in choosing process

74
Q

Nonresponse

A

Individual cannot be contacted/does not cooperate

75
Q

Response Bias

A

Interviewer may have an influence on respondant’s answers

76
Q

Experimental Units

A

Individuals on which an experiment is done

77
Q

Subjects

A

Units are people

78
Q

Placebo Effect

A

Dummy treatment with no physical effect

79
Q

Treatment

A

Specific experimental condition applied to units

80
Q

Control Group

A

Group of subjects with no treatment/given a placebo

81
Q

Statistically Significant

A

Observed effect is too large to attribute plausibly to chance

82
Q

Double Blind

A

Neither subjects/people who have contact with them know which treatment a subject recieves

83
Q

Block Design

A

Random assignment of units to treatments is carried out within each block

84
Q

Matched Pairs

A

2 treatments:

  • match subjects (pairs)
  • each subject gets both treatments in random order

(blocking)

85
Q

Sample Space

A

Set of all possible outcomes

86
Q

Probability

A

Outcome of a random phenomenon is the proportion of times the outcome would occur in a very long series of repetition

87
Q

Venn Diagram

A

Probability

Represents probability using area (2+ events)

P(S)=1

88
Q

Tree Diagram

A

Probability

89
Q

Independent

A

One event does not change the probability of another event

90
Q

P(S)=1

A

Area within a venn diagram

91
Q

P(A&B)=P(A)P(B)

A

Testing for Independence (Probability)

92
Q

P(AorB)=P(A)+P(B)-P(A&B)

A

Disjoint/Mutually Exclusive

93
Q

Conditional Probability

A

The probability of A, given B

94
Q

Complement of an event

A

(1-p)

95
Q

Mutually Exclusive/Disjoint

A

Events cannot occur at the same time

96
Q

Continuous Random Varibale

A

Graphed by a density curve (ex. normal curve)

97
Q

Discrete Random Variable

A

x has a amount that is countable for possible values

98
Q

Law of Large Numbers

A

As sample number increases, the sample results become more accurate

99
Q

Binomial Distribution

A

f

100
Q

Independence

A

f

101
Q

PDF

A

binompdf(n,p,k)

n= trials

p= probability of success

k= number of successes

102
Q

CDF

A

binomcdf(n, p, k)

n= trials

p= probability success

k= number of successes

103
Q

What is the shape of the graph?

A

Skewed Left

104
Q

What is the shape of the graph?

A

Skewed Right

105
Q

Back to Back Stem Plot

A

Used for comparing two distributions. Leaves are increasing in values away from the stem.

106
Q

σ2x+y=σ2x+σ2y

A

Combining variances (population)

107
Q

μa+bx=a+bμx

A

property of means

108
Q

σ2a+bx=bσ2x

A

property of variances

109
Q

μx+y=μx+μy

A

Combining means (population)

110
Q

σ2x=Σ(Xi- μx)2 Pi

A

Variance for discrete distribution

111
Q

μx=ΣXi(Pi)

A

Mean for discrete distribution

112
Q

μx=np

A

Mean of binomial distribution

113
Q

σ=√np(1-p)

A

Standard deviation of binomial distribution

114
Q

Z-Score

A

The standardized score

z = (x - μ) / σ

115
Q

B(n,p)

A

B= binomial distribution

n= sample size (trials)

p= prob of success

116
Q

Designing Experiments

A
  1. Control (Lurking variables)
  2. Randomization (Treatments)
  3. Replication

AP Statistics (12 decks)

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