Chapter 3 - Probability

Question 1

Sample space

Answer 1

the sample space is the set of all possible outcomes

Question 2

Event

Answer 2

an event is any set of outcomes of interest

Question 3

Probability of an event

Answer 3

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

Question 4

Theoretical probability models

Answer 4

• 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

Question 5

Mutually exclusive

Answer 5

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

Question 6

Positive predictive value

Answer 6

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

Question 7

Negative predictive value

Answer 7

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

Question 8

Sensitivity

Answer 8

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

Question 9

Specificity

Answer 9

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

Question 10

False negative

Answer 10

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

Question 11

False positive

Answer 11

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

Question 12

Bayesian inference

Answer 12

• 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

Question 13

Prior probability

Answer 13

• 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

Question 14

Posterior probability

Answer 14

• 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

Question 15

Prevalence

Answer 15

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

Question 16

Cumulative Incidence

Answer 16

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