This document discusses probability and related concepts. It begins by noting that researchers use probability to establish confidence in their findings given uncertainties that arise from using sample data to make generalizations. It then defines key probability laws and rules, including: the probability of an event occurring or not occurring; the sum of probabilities equaling 1; complementary events; compound events involving unions and intersections; and conditional probability. Examples are provided to illustrate these concepts. The document also discusses independence in probability.

1. YEAR 3
By
Vitumbiko Chijere Chirwa
16 November 2017
RES 311 (STATISTICS)
(BT-Kameza Campus)

2. PROBABILITY

3. Probability
• We live in a world full of uncertainties...
• Researchers use probability to establish
confidence in their findings. The reason why
researchers are concerned with establishing
confidence in their findings is a consequence of
their using data that are collected from samples.
• Because we make generalizations from samples
to infer about the population, there is always a
chance to commit errors
• Researchers try to establish confidence by talking
about their findings with regard to probability

4. Probability laws (axioms)

5. Basic laws (axioms) of probability
• The probability that an event will CERTAINLY
NOT occur: P(E) = 0 (examples?)
• The probability that an event will CERTAINLY
occur: P(E) = 1
• The probability of any event is ALWAYS
between (and can include) 0 and 1:
 𝟎 ≤ 𝑷 𝑬 ≤ 𝟏
• The sum of all probabilities of all simple
events in a sample space = 1

6. Probability rules

7. Rule of Complementary events
• Definition: A complement of an event E is the
set of all outcomes in the sample space that
are not included in the outcome(s) of E
• Denoted as 𝑬𝒄
𝑜𝑟 𝑬′
𝑜𝑟 𝑬
E 𝑬𝒄

8. Rule of Complementary events
• The outcomes of an event and the outcomes
of the complement make up the entire sample
space
• Therefore: 𝑃 𝐸 + 𝑃 𝐸𝑐
= 1
• 𝑃 𝐸 = 1 − 𝑃 𝐸𝑐
and 𝑃 𝐸𝑐
= 1 − 𝑃 𝐸
E 𝑬𝒄

9. Example
What is the probability that a randomly chosen
person cannot donate blood to everyone of any
blood type?

10. Rules of Compound events
• Definition: a compound event is a
combination of two or more events
a) Union of events: the union of two events A
and B is the set of outcomes that are
included in A or B or both A and B
b) Intersection of events: the intersection of
two events A and B is the set of outcomes
that are included in both A and B

11. Rules of Compound events
a) Union of events: 𝐴 ∪ 𝐵
 𝑷 𝑨 𝒐𝒓 𝑩 = 𝑷 𝑨 + 𝑷 𝑩 − 𝑷 𝑨 𝒂𝒏𝒅 𝑩
𝑷 𝑨 ∪ 𝑩 = 𝑷 𝑨 + 𝑷 𝑩 − 𝑷 𝑨 ∩ 𝑩
b) For mutually exclusive events: P 𝐴 ∩ 𝐵 = 0
 𝑷 𝑨 ∪ 𝑩 = 𝑷 𝑨 + 𝑷 𝑩 − 𝑷 𝑨 ∩ 𝑩
A B

12. Example
What is the probability that a randomly chosen
person is a potential donor for a person with
blood type A?

13. Conditional probability
• This is a probability of an event A given that
an event B has already occurred
a) P(A given B): is denoted as P(A/B)
 P(A/B) =
𝑃(𝐴∩𝐵)
𝑃(𝐵)
where P(B) ≠ 0
b) P(B given A): is denoted as P(B/A)
P(B/A) =
𝑃(𝐴∩𝐵)
𝑃(𝐴)
where P(A) ≠ 0

14. Independence in probability
• Two (or more) events are said to be
independent if the occurrence of one event
DOES NOT INFLUENCE the occurrence of the
other
a) P(A given B): is just P(A)
b) P(B given A): is just P(B)
 Therefore: 𝑷 𝑨 ∩ 𝑩 = 𝑷 𝑨 × 𝑷 𝑩 , and
𝑷 𝑨 ∪ 𝑩 = 𝑷 𝑨 + 𝑷 𝑩 − 𝑷 𝑨 × 𝑷(𝑩)

15. Example
• A cross-tabulation table was used from a study of
emergency department (ED) services for sexual assault
victims in Virginia (Table on following slide) (Plichta,
Vandecar-Burdin, Odor, Reams, and Zhang, 2007). This
study examined the question: Does having a forensic
nurse trained to assist victims of sexual violence on
staff in an ED affect the probability that a hospital will
have a relationship with a rape crisis centre? Some
experts thought that having a forensic nurse on staff
might actually reduce the chance that an ED would
have a connection with a rape crisis centre. The two
variables of interest here are “forensic nurse on staff ”
(yes/no) and “relationship with rape crisis centre”
(yes/no). A total of 53 EDs provided appropriate
responses to these two questions.

16. Find the probability:
a) that the ED will have a forensic nurse on staff
b) of not having a forensic nurse on staff
c) that the ED will have a relationship with a rape crisis center
d) that the ED will not have a relationship with a rape crisis center
e) (relationship with rape crisis center|no forensic nurse)
f) (relationship with rape crisis center|forensic nurse)

17. Example
• Consider randomly selecting one individual
from those represented in the following table
regarding the periodontal status of individuals
and their gender. Periodontal status refers to
gum disease where individuals are classified
as either healthy, have gingivitis, or have
periodontal disease.

18. Find:
a) P(Male)
b)P(Female)
c) P(Healthy)
d)P(Not Healthy)
e) P(Male and Healthy)
f) P(Male or Healthy)

19. Example
• A doctor gives a patient a 60% chance of
surviving bypass surgery after a heart attack. If
the patient survives the surgery, he has a 70%
chance that the heart damage will heal. Find
the probability that the patient survives
surgery and the heart damage does not heal.