Stats Flashcards

1
Q

Conditions for a binomial distrubution

A
  • The probability remains constant
  • The events are independent
  • data is discrete
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2
Q

AND

A

Multiply

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3
Q

OR

A

ADD

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4
Q

by default how does a binomial distrubution measure

A

≤ / ≥

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5
Q

P(X less than x)

A

= P(X ≤ x-1)

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6
Q

P(a≤X≤b) =

A

= P(X ≤ b) - P(x ≤ a-1)

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7
Q

P(X≥x)=

A

= 1- P(X≤x-1)

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8
Q

P(X>x)=

A

= 1 - P(X≤x)

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9
Q

Where do points of inflection occur on a normal distribution curve

A

1 standard deviation from the mean

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10
Q

standard variable

A

z = (x - μ) / σ

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11
Q

Normal approximation to binomial test

A

np>5

nq>5

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12
Q

Normal approximation to binomial conditions

A

n must be large

p must be close to 1/2

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13
Q

Normal approximation to the binomial

A

X ~ N (np, npq)

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14
Q

μ+-σ

A

2/3 or 67%

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15
Q

μ+-2σ

A

95%

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16
Q

μ+-3σ

A

97.7%

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17
Q

standard normal distrubution

A

mean = 0 , standard deviation = 1

18
Q

npq

A

varience (standard deviation^2)

19
Q

When is stem and leaf good

A

when representing small amounts of discrete data

20
Q

Outlier =

A

μ +- 2σ
or
UQ + 3/2 * IQR
LQ - 3/2 * IQR

21
Q

When is the median + IQR better than mean and standard deviation?

A

when there are outliers.

IQR and Median are not effected by outliers

22
Q

frequency standard deviation

A

√((Σx²f/Σf) - x̅²)

23
Q

standard deviation

A

√((Σx²/n) - x̅²)

24
Q

frequency density =

A

frequency / class width

25
Q

estimating the mean for grouped data

A

Σx* midpoint / n

26
Q

position of the nth percentile

A

n/100 * frequency

27
Q

lower class boundary / upper class boundary

A

if ≤ / ≥ then its the actual value

if < / > then its the value +- 0.5

28
Q

ploting culmulative frequency

A

always plot upper class boundary

29
Q

P(A∪B) =

A

P(A) + P(B) - P(A∩B)

30
Q

P(A|B)

A

P(A∩B) / P(B)

31
Q

P(A∩B) for mutually exclusive

A

= 0

32
Q

For independent events P(A∩B) =

A

P(A)P(B)

33
Q

For independent events P(A|B) =

A

P(A)

34
Q

sum of probabilities in a probability distribution =

A

1

35
Q

nCr =

A

n!/r!(n-r)!

36
Q

how many ways can n objects be arranged

A

n!

37
Q

How many ways can n objects be arranged is r of those objects are the same?

A

n!/r!

38
Q

For binomial: P(success) =

A

nCr * P(success)^r * P(failure)^n

39
Q

conditions for a normal distrubution

A
  • data is continous
  • data is symmetrically distrubuted with a peak
  • data tails off either side of the mean
40
Q

critical value normal hypothesis tests method

A

critical value = μ +- kσ/√n
k = Ф(sig level)
if observed mean more extreme than critical value then reject H0

41
Q

Normal hypothesis test method

A

Z = observed - expected / sample standard deviation
k = Ф(sig level)
if Z is more extreme than k reject H0