Lecture 5 Flashcards

Role of Probability

1
Q

What is probability?

A

the likelihood that an event will occur out of all the events ran (trials/rounds)

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2
Q

What is the probability equation?

A

p = # ways an event can occur (a possible outcome) / total # of possible events

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3
Q

What are complementary event’s probability total?

A

p is a total of 1 (100%)

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4
Q

What are mutually exclusive (disjoint) events?

A

when events A and B CANNOT be occurring at the same time - P(A or B)

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5
Q

What is the equation/rule used to calculate probability of a disjoint event?

A

addition rule
P(A or B) = P(A) + P(B) - [P(A and B)]

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6
Q

What are joint events?

A

when events A and B CAN be occurring at the same time and the combination of the two events need to be occurring at the same time to calculate its probability

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7
Q

If both conditions are not an option to be occurring at the same time, what is the probability?

A

probability is 0

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8
Q

What is conditional probability?

A

the probability of event A occurring after the assumption that event B has already occurred - P(A | B)

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9
Q

What time of variable can use conditional probability?

A

categorical variables

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10
Q

What is the numerator when calculating conditional probability?

A

A’s condition frequency while also meeting B’s condition

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11
Q

What is the denominator when calculating conditional probability?

A

B’s condition/event total frequency

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12
Q

What are the 6 types of conditional probability tests ran in the medical field?

A
  • sensitivity (true positive)
  • specificity (true negative)
  • false positive
  • false negative
  • positive predictive value (PPV)
  • negative predictive value (NPV)
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13
Q

Which piece of data always goes in the columns of a table when answering conditional probability?

A

the GOLD standard test or outcome (A and A bar)

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14
Q

Which piece of data always goes in the rows of a table when answering conditional probability?

A

the new type of test or screening test (E and E bar)

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15
Q

What is the sensitivity equation?

A

(screen + | outcome +) =
screen+ and has outcome +/outcome+ total

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16
Q

What is the specificity equation?

A

(screen - | outcome -) =
screen - and has outcome - / outcome - total

17
Q

What is the false negative equation?

A

(screen - | outcome +) =
screen - and has outcome + / outcome + total

18
Q

What is the false positive equation?

A

(screen + | outcome -) =
screen + and has outcome - / outcome - total

19
Q

What is Bayes’ Theorem?

A

the probability of a new test or screening being true to the result shown

20
Q

What is the positive predictive value equation?

A

-PPV = (P(A) * sensitivity) /
[(P(A) * sensitivity) + (P(A bar) * false positive)]

21
Q

What is the negative predictive value equation?

A

NPV = (P(A bar) * specificity) /

[P(A bar) * specificity) + (P(A) * false negative)]

22
Q

What is the skewness of a normal distribution?

A

the spread of the x axis

23
Q

What is the kurtosis of a normal distribution?

A

the spread of the y axis

24
Q

What is the equation to convert data into a z-score?

A

z = x (the value) - mew (population mean) / sigma (population SD)

25
Q

What information does the standard z-table give?

A

P (z < Z), only gives probability to the LEFT of the calculated z-score

26
Q

How does one solve for the RIGHT of the distribution probability?

A

when P(z > Z) , 1 - z-score value = probability

27
Q

How does one solve for how many people based on a probability?

A

of participants within that probability = n * probability decimal

28
Q

How does one solve for a range of values?

A

subtracting the z-score of the LOWER limit from the z-score of the UPPER limit- the value is the probability results will fall within that range