Module 2 Flashcards
(16 cards)
Why does quantifying uncertainty matter relative to probability
Because in public health, we rarely deal with certainties. Instead, we encounter situations with varying levels of uncertainty
What does making predictions matter relative to probability
Forecasting the future, especially in disease spread or health outcomes, is vital in public health for preparedness and intervention
Why is risk assessment important relative to probability?
Understanding and communicating risks is essential for public health decision-making and for informing the public
How does probability support Decision-making under uncertainty
we often need to make decisions with incomplete information. Probability offers a structured approach to make the best possible decisions in these scenarios
How does probability support testing hypotheses
Hypothesis testing is a cornerstone of scientific research, helping to determine if observed effects (like the efficacy of a drug) are genuine or if they could have occurred by random chance
How does probability support designing experiments and studies
Properly designed experiments help ensure valid and reliable results. Probability helps in determining sample sizes, understanding potential variability, and ensuring the generalizability of findings
What are the three axioms of probability
- That the probability of the entire sample space =1
- Any event’s probability is at least 0
- For any two mutually exclusive events, the probability of their union is the sum of their individual probabilities = the additive rule
What is an event
An event is the basic element to which probability can be applied. It is the result of an observation or experiment, or the description of some potential outcome. Events are represented as uppercase letters A, B, and C
Frequency definition
The probability of an event A is the proportion of times the event occurs in a large number of trials repeated under virtually identical conditions. P(A) = m/n
Null event
An event that can never occur.
How is complementary probability calculated
1 - P(A)
Mutually Exclusive
When two events cannot occur simultaneously. The intersection of the two cannot exist = 0
Mutually exclusive deals with the overlap of events
What is the additive rule
That for two mutually exclusive events, the probability that either of these two events will occur is equal to the sum of their probabilities P(A)+P(B). This can also be applied to three variables
When two events are not mutually exclusive, how do we determine the probability that either of the events will occur?
P(A) + P(B) - the Probability of AnB
Multiplicative Rule of Probability - Conditional Probability
The probability that two events will occur is equal to the probability of A multiplied by the probability of B given that A has already occurred
P(B|A) = P(AnB)/P(A)
Independent Event
For independent events, the variables do not influence the likelihood of one another: P(A∩B)=P(A)×P(B) since the occurrence of one does not affect the occurrence of the other.
