Chapter 3 - Probability Flashcards Preview

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Flashcards in Chapter 3 - Probability Deck (16):
1

Sample space

the sample space is the set of all possible outcomes

2

Event

an event is any set of outcomes of interest

3

Probability of an event

the probability of an event is the relative frequency of the event over an indefinitely large (or infinite) number of trials

4

Theoretical probability models

- theoretical probability models may also be constructed
- comparing empirical probabilities with theoretical probabilities enables us to assess the goodness-of-fit probability models
- this is an example of statistical inference

5

Mutually exclusive

- the two events A and B are mutually exclusive if they cannot both happen at the same time

6

Positive predictive value

the positive predictive value (PV+) of a screening test is the probability that a person has a disease given that the test is positive

7

Negative predictive value

the negative predictive value (PV-) of a screening test is the probability that a person does not have a disease given that the test is negative

8

Sensitivity

the probability that the symptom (test) is present given that the person has a disease

9

Specificity

the probability that the symptom is not present given that the person does not have a disease

10

False negative

negative test result when the disease or condition being tested for is actually present

11

False positive

positive test result when the disease or condition being tested for is not actually present

12

Bayesian inference

- it is an alternative definition of probability and inference
- it rejects the idea of the definition of probability sometimes called the frequency definition of probability (a theoretical concept)
- conceives two types of probability = prior probability and posterior probability

13

Prior probability

- best guess by the observer of an event’s likelihood in the absence of data
- this may be a single number, or a range of likely values, perhaps with weights attached to each possible value

14

Posterior probability

- the likelihood that an event will occur after collecting some empirical data
- it is obtained by integrated information from the prior probability with additional data related to the event in question

15

Prevalence

the probability of currently having the disease regardless of the duration of time one has had the disease

16

Cumulative Incidence

also referred to as incidence, the probability that a person with no prior disease will develop a new case of the disease over some specified time period