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class 2 - May 22 > chapter 7 > Flashcards

chapter 7 Flashcards

1
Q

Describe sample results

A
  • provides only estimates
  • contains only a portion of the population
  • some sampling errors are to be expected
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2
Q

Describe a sample population

A
  • population from which the sample is drawn
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3
Q

Frame

A

a list of elements that the sample will be selected from

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4
Q

Simple Random sampling

A
  • can be used to select a sample from a finite pop

- and describes how a random sample can be taken from an infinite pop that is generated by an ongoing process

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5
Q

Element

A

entity on which data is collected

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6
Q

Population

A

collection of all elements of interest

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7
Q

sample

A

subset of the pop

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8
Q

Parameters

A

numerical characteristics of a population

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9
Q

Pop Parameter for mean

A

M = pop mean

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10
Q

pop parameter for SD

A

Q = pop SD

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11
Q

Pop parameter for Proportion

A

P= Pop proportion

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12
Q

Selecting a sample - FInite Pop

A
  • use a table of random #s to choose the elements for the sample one at a time in such a way that, at each step, each element remaining has the same prob of being selected
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13
Q

Sampling without replacement

A

it is possible that a random # used previously may appear again

  • any prevously used #s are ignored
  • used most often in practice
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14
Q

Sampling with Replacement

A
  • not used as often

- still a valid method

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15
Q

Sampling from an Infinite population - Simple Random sample

A
  • a random sample of size n from an infinite pop is a sample selected such that the following conditions are met
  1. each element selected comes form the same pop
  2. each element is selected independently - to prevent selection bias

care must be taken, each case may require a different selection procedure

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16
Q

when is the population considered infinite

A

when we cannot develop a list of all the elements that could be produced

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17
Q

Process for selecting an sample from an infinite pop and provide some examples

A
  • usually associated with a process that operates over time
    ex - parts being manufactured
  • repeated experimental trials in a lab
  • transactions occurring at a bank
  • telephone calls coming into a call center
  • customers entering a store
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18
Q

What is a sample statistic

A
  • a sample characteristic

- ie. sample mean xbar, sample SD, sample proportion etc.

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19
Q

Numerical values obtained for each sample statistic is called

A

a point estimate

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20
Q

by making calculations, we are calculating

A

point estimators

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21
Q

Target Pop

A

pop we want to make inferences about

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22
Q

Describe the sampling distribution of x bar

A
  • various possible values of x bar are the result of different simple random samples
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23
Q

the prob distribution of x is called the

A

sampling distribution of x bar

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24
Q

What does the sampling distribution of x bar allow us to do

A
  • make prob statements about how close the sample x bar mean is to the pop mean
  • can generate a variety of values of x bar and phat
    but in practice we only use one
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25
Q

WHat is the sampling distribution of x bar

A

the prob distribution of all possible values of the sample mean x bar

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26
Q

What is the expected value of x bar

A
  • b/c many different values of x bar are possible, we are often interested in the mean of all possible x bars that can be generated
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27
Q

What is another name for the expected value of x bar

A

mean

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28
Q

if x bar = the mean then

A

pop parameter is said to be unbiased

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29
Q

what is the name of the sd of x bar

A

standard error

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30
Q

what is N-n / N-1 called

A

the finite pop correction factor

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31
Q

What are the two rules for using Q/Square root of n

A
  1. pop is infinite

2. pop is finite and sample size is LESS THAN OR EQUAL TO 5% of the pop size

32
Q

when n increase the standard error does what

A

decreases

- when this happens there is less variation or it is closer to the sample mean

33
Q

What can the shape or form of x bar be

A
  1. pop normal distributed - any sample size will be normally disribuited
  2. Pop does not have a normal distribution
    - use central limit theorem
    - when sample size gets bigger, the shape becomes normally distributed (use size of 30 or more) or 50 if highly skewed or has outliers
34
Q

When the pop is discrete what is the form of the sample size

A

sample size depends on pop proportion
n/N is less than 0.05
I DON”T GET WHAT I AM TRYING TO SAY HERE

35
Q

What is the sampling distribution of p hat formula

A

p hat = x/n = sample proportion

36
Q

What is the sampling distribution of p hat formula

A

p hat = x/n = sample proportion

37
Q

what is the expected value of p hat

A

= the population proportion

38
Q

if you are using a finite pop for the sampling distribution of p hat, when can you use the infinite formula

A

use sample rule

n/N is less than or equal to 0.05

39
Q

if the sample size increases, what happens to the standard error of p hat?

A

it goes down which means it is less variable

40
Q

when using a binomial random variable for sampling, what are the conditons in order to use the normal distribution

A

np is greater than 5 and

n(1-p) is is greater than 5

41
Q

What are the 3 properties of point estimates

A
  1. unbiased
  2. efficiency
  3. consistency
42
Q

describe unbiased

A

M=x bar

43
Q

describe efficiency

A
  • point estimator with smaller sd is preferred

- b/c it tends to provide estimates closer to the pop parameter

44
Q

point estimators with smaller se is said to have what

A

greater efficiency than the other one

45
Q

describe consistency

A
  • if the value of the point estimator tends to become closer to the pop parameter as the sample size increases
  • larger sample size tends to provide a better point estimate than a smaller one
46
Q

What are the other 5 sampling methods

A
  1. stratified random sampling
  2. cluster sampling
  3. systematic sampling
  4. convenience sampling
  5. judgmental
47
Q

Describe random sampling

A

the pop is 1st divided into strata (or groups of the same)ie pink dresses, blue dress and purple dresses and a simple random sample is taken form each strata

48
Q

Describe cluster sampling

A
  • pop is 1st divided into clusters (ie all people on one street, all people on next etc)
  • then a simple random sample of the cluster is taken
    ie everyone on main street is interviewed
49
Q

Describe Systematic Sampling

A

we randomly select 1 of the 1st k elements and then select every kth element there after

50
Q

Describe Systematic Sampling

A

we randomly select 1 of the 1st k elements and then select every kth element there after

51
Q

Describe convenience sampling

A

non prob method

- elements are selected based on convenience

52
Q

Describe judgement sampling

A

non prob method

- selected based on the judgement of the person sampling

53
Q

the sampling distribution of x bar is the

A

probability distribution of the sample mean

54
Q

Parameters are

A

numerical characteristics of a population

55
Q

The prob distribution of all possible values of the sample proportion p hat is the

A

sampling distribution of p hat

56
Q

in computing the standard error of the mean, the finite pop correction factor is used when

A

n/N > 0.05

57
Q

Stratified random sampling is a method of selecting a sample in which the

A

population is first divided into strata, and then random samples are drawn from each stratum

58
Q

The closer the sample mean is to the population mean,

A

the smaller the sampling error

59
Q

since the smaples size is always smaller than the size of the population, the sample mean

A

can be smaller, larger or equal to the pop mean

60
Q

as the sample size increases, the standard error of the mean

A

decreases

61
Q

a simple random sample form an infinite pop is a sample selected such that each element is selected

A

independently and from the same pop

62
Q

in point estimation, the data from the sample is used to

A

estimate the population parameter

63
Q

the sample statistic s is the point estimator of

A

S

64
Q

The sample mean is the point estimator of

A

m

65
Q

if we condsier the simple random sampling process as an experiment, the sample mean is

A

a random variable

66
Q

the prob distribution of the sample mean is called the

A

sampling distribution of the mean

67
Q

the standard deviation of all possible x bar values is called the

A

standard error of the mean

68
Q

As the sample size becomes larger, the sampling distribution of the sample mean approaches a

A

normal distribution

69
Q

The sampling error is the

A

difference between the value of the sample mean and the value of the pop mean

70
Q

a prob distribution for all possible values of a sample statistic is known as

A

a sampling distribution

71
Q

a pop characteristic, such as a pop mean, is called

A

a parameter

72
Q

a sample statistic such as a sample mean, is known as

A

a statistic

73
Q

a single numerical value used as an estimate of pop parameter is known as

A

a point estimate

74
Q

the sampling statistic, such as x bar, s, or p hat, that provides the point estimate for the pop parameter is known as

A

a point estimator

75
Q

THe purpose of statistical inference is to provide information about the

A

sample based upon information contained in the population

class 2 - May 22 (9 decks)

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