Brainscape's Knowledge GenomeTM

Browse over 1 million classes created by top students, professors, publishers, and experts.


See full index

class 1 > additional 2 > Flashcards

additional 2 Flashcards

1
Q

What is probability

A

a numerical measure of the likelihood that an event will occur

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
2
Q

What can probability be used for

A

used as measures of the degree of uncertainty

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
3
Q

probability values are always assigned on a scale of

A

0 to 1

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
4
Q

what is a prob of near zero indicate

A

event is unlikely to occur

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
5
Q

what is prob of near 1 indicate

A

an event is almost certain to occur

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
6
Q

what is an experiment

A

a process that generates well-defined outcomes

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
7
Q

what is a sample space

A

set of all experimental outcomes

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
8
Q

what is an experimental outcome also called

A

a sample point

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
9
Q

what is a sample point

A

identifies an element of the sample space

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
10
Q

What is the counting rule for a multistep experiment

A

if an experiment can be described as a sequence of k steps with n1 possible outcomes on the first step, n2 possible outcomes on the second step, and so on

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
11
Q

What is a tree diagram

A

a graphical representation that helps us visualize the multi-step experiment

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
12
Q

In a tree diagram, along the branches you

A

multiply

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
13
Q

What are the 3 useful Counting Rules

A
  1. Multistep experiment
  2. Combinations
  3. Permutations
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
14
Q

What are combinations

A
  • allows us to count the # of experimental outcomes when the experiment involves select n objects for a set of N objects and ORDER DOES NOT MATTER
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
15
Q

What are permutations

A
  • allows us to compute the # of experimental outcomes when n objects are to be selected from a set of N objects and ORDER MATTERS
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
16
Q

Does permutations or combinations result in more

A

permutations

b/c every selection of n objects can be ordered in n! different ways

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
17
Q

What are the 3 most useful approaches for assigning probabilities

A
  1. Classical Method
  2. Relative Frequency method
  3. Subjective method
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
18
Q

Explain classical method

A

use when: all experimental outcome are EQUALLY LIKELY

  • the 2 basic requirements are satisfied
  • example tossing a coin
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
19
Q

Explain when to use the Relative Freq. Method

A

use when: data re available to estimate PROPROTION Of TIME and the experimental outcome will occur if the experiment is REPEATED a LARGE # of TIMES
- 2 basic requirements are satisfied

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
20
Q

Explain when you would use the Subjective Method

A

Use When: we CANNOT realistically assume that the experimental outcomes are Equally Likely and when Little relevant data is available - degree of belief

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
21
Q

Which method would we use Bayes Theorem for

A

Subjective method

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
22
Q

what are the basic requirements for assigning Probabilities

A
  1. the prob assigned to each experimental outcome must be b/w 0 and 1 inclusively
  2. Sum of prob for all experimental outcomes must equal 1.0
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
23
Q

What is an event

A

collection of sample points

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
24
Q

what is the prob of an event

A

equal to the sum of the prob(s) of the sample points in the event

25
Q

Even in business situations where either the classical or relative freq. method is used, managers may want to provide subjective prob estimates. In such cases, the best prob estimates often are obtained by combining the estimates from the classical or relative frequency with the

A

subjective method

26
Q

Prob of A OR B is shown as and what rule does it use

A

P(AUB) A Union B - uses addition rule

P(A) + P(B) - P(ANB)

27
Q

If A and B are mutually exclusive the how do you compute the Prob of A OR B

A

P(AUB) = P(A) + P(B) - 0

28
Q

How do you compute the prob of A AND B

A

P(AnB) = P(A) x P(B)

Dependent: P(AnB) = P(A)+P(B) - P(AUB)?

29
Q

If events are Independent then the P(A/B) =

A

P(A)

30
Q

When do you use the addition law P(AUB)

A

knowing the prob of at least one of two events occurring

- prob that event A OR event B OR Both occur

31
Q

Event A and B is the event containing

A

all sample points belong to A or B or Both

32
Q

What is the intersection of two events

A

the event containing the sample points belonging to BOTH A and B denoted by A n B

33
Q

P(A) = .3, P(B) = .7 P(A|B) = .40 are they independent or dependent

A

they are dependent b/c P(A|B) does not equal P(A)

34
Q

P(A) = .3 P(B) = .4 and P(ANB) = .12 are they independent or dependent

A

they are independent because P(A) x P(B) = .12

35
Q

The multiplication law is used to compute the

A

intersection of 2 events

36
Q

The multiplication law is based on the definition of

A

conditional probability, need to know if it is dependent or independent

37
Q

With Multiplication law P (ANB) the item has replacement then it is

A

independent (b/c the prob of being chosen is the same every time)

38
Q

with multiplication law P(ANB) the item is not replaced then it is

A

Dependent (b/c chances change with each selection

39
Q

When do you use Bayes Theorem

A

when revising probabilities when new info is obtained
(used subject method prior)
- for computing posterior probabilities

40
Q

What is a random variable

A

a numerical description of the outcome of an experiment

- must assume numerical values

41
Q

what types of random variables are there

A
  1. Discrete

2. Continuous

42
Q

Describe a discrete random variable

A

finite
# of books, age, can count them
values of f(x) must be greater than or equal to 0

43
Q

Describe a continuous random variable

A
  • infinite
  • glass of water, temperature, size, weight, distance, time
  • collection of intervals
44
Q

What does a prob distribution for a random variable describe

A

describes how prob(s) are distributed over the values of the random variable

45
Q

what are the 3 methods used for discrete random variables

A
  1. relative frequency method
  2. classical method
  3. subjective method
46
Q

When do you use the Relative Frequency method

A
  • when reasonably large amounts of data are available
  • treats the data as though it was a population
  • more widely used in practice
  • leads to what is called an Empirical Discrete distribution
47
Q

When do you use the classical method

A
  • when experimental outcomes generate values of the random variable that are equally likely
48
Q

What are the required conditions for the discrete prob function f(x)

A

F(x) must be greater than or equal to 0

Sum f(x) =1

49
Q

What is the primary advantage of defining a random variable and its prob distribution

A

once the prob distribution is known, it is realtively easy to determine the prob of a variety of events

50
Q

what are the 4 properties of a binomial experiment

A
  1. experiment consists of n identical trails (fixed number of trials)
  2. 2 outcomes are possible on each trial (success or failure)
  3. The prob of a success is denoted by p Does not change from trial to trial
    the prob of failure is denoted by 1-p does not change from trial to trial
  4. the trials are independent
51
Q

What are the properties of a Bernoulli process

A
  1. 2 outcomes are possible
  2. prob of success is denoted by p, failure 1-p
  3. trails are independent (prob does not change)
52
Q

What is a possion probability distribution

A

often used to model random arrivals in waiting line situations,
- useful in estimating the # of OCCURRENCES over a SPECIFIED INTERVAL of time or space

53
Q

What are the properties of a poisson distribution

A
  1. the prob of an OCCURRENCE is the same for any 2 intervals of equal length
  2. the occurrence or nonoccurrence in ANY interval is independent of the occurrence or non-occurrence in any other interval
54
Q

When do you use the Hypergeometric

A

when

  1. the trials are not independent (no replacement)
  2. prob of success changes from trial to trail
55
Q

for hypergeometric r is

A

the number of elements in the pop labelled as successes

56
Q

Hypergeometric N-R is

A

the number of elements in the pop labelled failure

57
Q

Hypergeometric N is

A

number of elements in the population

58
Q

Hypergeometric x is

A

prob of success we are looking for

59
Q

Hypergeometric n is

A

number of trials

class 1 (22 decks)

Brainscape helps you reach your goals faster, through stronger study habits.
© 2024 Bold Learning Solutions. Terms and Conditions