probability

Question 1

what is probability?

Answer 1

the likelihood or chance of an event occurring (numerical measure of how likely an event will occur)

Question 2

what is the purpose of probability?

Answer 2

business statistics apply mathematical formulas or models to business information in an attempt to determine the probability of success relating to an opportunity

(will new delivery service improve customer satisfaction)
stats used to measure this probability

Question 3

how is probability used in inferential statistics?

Answer 3

predict the probability that the whole sample will be the same as the population

Question 4

what is the numerical value of probability?

Answer 4

range from 0 - 1

percentages or odds

Question 5

what ate the 3 sources of probability?

Answer 5

• subjective
• classical (theoretical)
• empirical (statistical)

Question 6

what is subjective probability?

Answer 6

• lilihood of particular event assigned by individual based on whatever info is available
• if little or no info, prob is based on subjectivity
• soley based on intuition
  (football predictions)

Question 7

what is classical / theoretical probability?

Answer 7

• all outcomes are equally likely

- probability is a logical thing

Question 8

what is the formula for classical / theoretical prob?

Answer 8

no. of favourable outcomes / no. of possible outcomes

roll of a dice = 1/6

Question 9

what is empirical (statistical) prob?

Answer 9

• based on experiments
• relative freqenecuy
  = proportion of times the outcome has occurred over many repetitions
• probability has come from historical records?
  = frequency probability

example rainy days

169/365 = 0.43 x 100 = 43%

• assumption that it doesn’t deviate from past outcomes

Question 10

what is an experiment?

Answer 10

action / process with a well defined set of outcomes on a single repetition (trial) only one possible outcome occurs

Question 11

what is a sample space?

Answer 11

set of all possible outcomes

Question 12

what is an element?

Answer 12

specific outcome (sample point)

Question 13

what is an event?

Answer 13

subset to sample space, it may be specific outcome or combination of outcomes

Question 14

what is th eporbabaility of an event?

Answer 14

sum of all probabilities of all elements that make up every

Question 15

what is combining events?

Answer 15

rules of probability

• addition rules
• multiplication rules

one event with another

Question 16

what is meant by general and specific?

Answer 16

wether two events are indpeneet of eahcother

Question 17

what is the specific event for addition rule? ‘or’

Answer 17

indenpenedant of other event (don’t happen at same time, not influenced)

P(A or B) = P(A) +P(B)

Question 18

what is the general rule for addition rule?

Answer 18

not indépendant

P(A or B) = P(A) +P(B) - P(A and B)

Question 19

what is the specific rule for multiplication?

‘and’

Answer 19

P(A and B) = P(A) x P(B)

Question 20

what is the general rule for the multiplication rule?

Answer 20

e.g. if you pick a card out of a pack of a cards this will have an event on the likelihood of picking other cards

P(A and B) = P(A) x P(B | A) - given that A has already happened

e.g. 4 / 52 then one card picked so it becomes 4 / 51

Question 21

what are expected values?

Answer 21

we can calculate them based on probability

the return you can expect for some kind of outcome

Question 22

what is the formula for expected value?

Answer 22

sum of [ P(outcome) x result of outcome ]

Question 23

what is porbabailty distribution?

Answer 23

statistical model that shows the possible outcomes of a particular event as well as statistcial likelihood of each event

Question 24

what is discrete probability distribution?

Answer 24

finite no. of values only take on certain no. of values

X can take on values from 1-6 with probabilities of 1-6

Question 25

what is continuous probability distribution?

Answer 25

• as the number of trials increases, bar charts become more of a smoother curve
• variable X can assume a continuous set of variable
  total area of relative frequency polygon = 1
  (probability function density)

Question 26

what is normal distribution?

Answer 26

one of the most important examples of continuous probability dstrbtion

most common

Question 27

why would you transform normal distribution into standard normal distraction?

Answer 27

because every normal dis has a diff mean and SD whereas SND has a mean of 0 and SD of 1