4-7 Flashcards

1
Q

Probability

A

Numerical measure between 0 and 1 that describes the likelihood that an event will occur. Probabilities closer to 1 indicate that the event is more likely to occur. Probabilities closer to 0 indicate that the event is less likely to occur.

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

P(A) - probability of event A

A
P(A) = 1, event is certain to occur
P(A) = 0, event is certain not to occur
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
3
Q

Intuition

A

Incorporates past experience, judgement, or opinion to estimate likelihood of an event

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

Relative frequency

A

Uses formula:

Probability of event = f/n

Where f = frequency of event in a sample of n outcomes

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

Equally likely outcomes

A

Uses formula:

Probability of event =

of outcomes favorable divided by total number of outcomes

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

Law of large numbers

A

As sample size increases and increases, the relative frequencies of outcomes get closer and closer to the theoretical or actual probability value

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

Statistical experiment

A

Any random activity that results in definite outcome

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

Event

A

A collection of one or more outcomes of a statistical experiment or observation

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

Simple event

A

One particular outcome of a statistical experiment

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

Sample space

A

Set of all simple events

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

Sum of probabilities

A

Always equal to 1

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

Compliment of event A

A

Event that A does not occur

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

Independent events

A

If occurrence or nonoccurence of one event does not change the probability that the other event will occur.

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
14
Q

Multiplication rule for INDEPENDENT events

A

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

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
15
Q

Conditional probability

A

P(A and B) = P(A) • P(B | A)

P(A and B) = P(B) • P(A | B)

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
16
Q

Mutually exclusive events

A

Don’t occur together

Addition rule: P(A or B) = P(A) + P(B)

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

General addition rule for any events A and B

A

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

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
18
Q

Permutations

A

Number of ways to arrange in order n distinct objects taking them r at a time

    n!
-------
(n - r)!
19
Q

Combinations

A

Number of combinations of n objects taken at r time (grouping)

      n! ---------------- r!( n - r )!
20
Q

Random variable

A

If the value that x takes on in a given experiment or observation is a chance or random outcome

21
Q

Discrete random variable

A

Can take on only a FINITE number of values or a countable number of values

Ie: whole numbers

22
Q

Continuous random variable

A

Can take on any of the countless number of values in a line interval

Ie: measurements - weight, Length, temperature, elapsed time

23
Q

Binomial experiment

A

Fixed number of trials (n)

Trials are independent and repeated under same conditions

Two outcomes Success (p) , Failure (q)

Probability of success is the same for each trial

P + q = 1; q = 1 - p

Want to find probability of r successes out of n trials

24
Q

Mean of binomial experiment (u)

A

U = np

Where:
n = # of trials
p = probability of success

25
Q

Standard deviation of binomial

A

Square root of (npq)

26
Q

Unusual values

A

U + 2.5o

U - 2.5o

27
Q

Variance of binomial probability distribution

A

O^2 = npq

28
Q

Normal curve

A

1) bell shaped
2) symmetrical about vertical line thru u (mean)
3) curve approaches horizontal axis
4) inflection points between cupping upward and downward occur above u + o and u - o
5) area under curve equals 1

29
Q

Empirical rule

A

1) 68% of data values lie within 1 std deviation
2) 95% of data values lie within 2 std deviation
3) 99.7% of data values lie within 3 std deviation

30
Q

Out of control signals

A

Out of control signal 1:
One point falls beyond the 3o level

Out of control signal 2:
A run of 9 consecutive points on one side of center line (u)

Out of control signal 3:
At least 2 of 3 consecutive points lie beyond 2o level on same side of center line

31
Q

Z value / z score

A

Difference between the measurement and the mean divided by std deviation

Z = x - u
———
O

32
Q

Raw score x

A

x = zo + u

33
Q

Statistic

A

Numerical descriptive measure of a SAMPLE

34
Q

Parameter

A

Numerical descriptive measure of a POPULATION

35
Q

Estimation

A

Estimate value of population parameter

36
Q

Testing

A

Formulate a decision about value of the population parameter

37
Q

Regression

A

Make predictions or forecasts about the value of a statistical variable

38
Q

Sampling distribution

A

Probability distribution of a sample statistic based on all possible simple random samples of the same size from the same population

39
Q

Normal approximation of the binomial distribution

A

Conditions

If

1) np > 5
2) nq > 5

Then:
R has a binomial distribution that is approximated by a normal distribution with

U = np and o = sq root npq

40
Q

Mean of std deviation of a discrete population probability distribution

A

U = summation of (xP(x))

41
Q

Std deviations of a discrete population probability distribution

A

Steps:

1) Find x(given)
2) Find P(x) (percentage given, turn to decimal)
3) Multiple x and P(x)
4) Calculate u by adding up xP(x) values
5) x - u for all values
6) square values
7) multiply by P(x)
8) add together to find variance/ square root the sum to find the std deviation

42
Q

Find sample size n for estimating u when std deviation is known

A

n = ( z score times std deviation divided by E) all squared

Where E is error

43
Q

T variable

A

T =

     X - u
-----------
       S 
      ---
      n^1/2

Degrees of freedom = n - 1

44
Q

Binomial distribution

A

P = r/n

q = 1 - p

N = # of trials , r = number of successes