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Business Statistics I > Chapter 6 and Chapter 7 > Flashcards

Chapter 6 and Chapter 7 Flashcards

1
Q

A continuous probability distribution for which the probability that the random variable will assume a value in any interval is the same for each interval of equal length.

A

Uniform Probability Distribution

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2
Q

A continuous probability distribution that has a probability density function that is bell-shaped and determine by its mean μ and standard deviation σ.

A

Normal Probability Distribution

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3
Q

A normal distribution what a mean of zero and a standard deviation of one.

A

Standard Normal Probability Distribution

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4
Q

A continuous probability distribution that is useful in computing probabilities for the time it takes to complete a task.

A

Exponential Probability Distribution

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5
Q

A function used to compute probabilities for a continuous random variable. The area under the graph of this function over an interval represents probability.

A

Probability Density Function

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6
Q

A numerical characteristic of a population, such as a population mean μ, a population standard deviation σ, a population proportion p, etc.

A

Parameter

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7
Q

A sample characteristic, such as a sample mean x bar, a sample standard deviation s, a sample proportion p bar, etc.

A

Sample Statistic

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8
Q

The value of a sample statistic used in a particular instance as an estimate of a population parameter.

A

Point Estimate

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9
Q

A property of a point estimator that is present when the expected value of the point estimator is equal to the population parameter it estimates.

A

Unbiased

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10
Q

The population for which the statistical inferences such as point estimates are made.

A

Target Population

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11
Q

The population from which the sample is taken.

A

Sampled Population

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12
Q

A property of a point estimator that is present whenever larger sample sizes tend to provide point estimates closer to the population parameter.

A

Consistency

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13
Q

Given two unbiased point estimators of the same population parameter, the point estimator with the smaller standard error is more efficient.

A

Relative Efficiency

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14
Q

The population from which the sample is taken.

A

Sampled Population

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15
Q

Once an element has been included in the sample, it is returned to the population. A previously selected element can be selected again and therefore may appear in the sample more than once.

A

Sampling with Replacement

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16
Q

Once an element has been included in the sample, it is removed from the population and cannot be selected a second time.

A

Sampling without Replacement

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17
Q

A sample of size n from a finite population of size N is selected such that each possible sample of size n has the same probability of being selected.

A

Simple Random Sample

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18
Q

A probability sampling method in which the population is first divided into strata and a simple random sample is then taken from each stratum.

A

Stratified Random Sampling

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19
Q

A probability sampling method in which we randomly select one of the first k elements and then select every kth element thereafter.

A

Systematic Sampling

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20
Q

A probability sampling method in which the population is first divided into clusters and then a simple random sample of the clusters is taken.

A

Cluster Sampling

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21
Q

A nonprobability method of sampling whereby elements are selected for the sample on the basis of ease of collection.

A

Convenience Sampling

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22
Q

A nonprobability method of sampling whereby elements are selected for the sample based on the expertise of the person doing the study.

A

Judgment Sampling

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23
Q

A probability distribution consisting of all possible values of a sample statistic.

A

Sampling Distribution

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24
Q

The standard deviation of a point estimator.

A

Standard Error

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25
Q

The term that is used in the formulas whenever a finite population, rather than an infinite population, is being sampled.

A

Finite Population Correction Factor

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26
Q

A theorem that enables one to use the normal probability distribution to approximate the sampling distribution of the sample mean whenever the sample size is large.

A

Central Limit Theorem

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27
Q

The Excel function that returns the standard normal distribution.

A

NORM.S.DIST

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28
Q

The Excel function that returns the inverse of the standard normal cumulative distribution.

A

NORM.S.INV

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29
Q

The Excel function that returns the normal distribution for the specified mean and standard deviation.

A

NORM.DIST

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30
Q

The Excel function that returns the inverse of the normal cumulative distribution for the specified mean and standard deviation.

A

NORM.INV

31
Q

The Excel function that returns the exponential distribution.

A

EXPON.DIST

32
Q

The Excel function that rounds a number down.

A

ROUNDDOWN

33
Q

The Excel function that rounds a number up.

A

ROUNDUP

34
Q

The Excel function that returns a random number greater than or equal to 0 and less than 1, evenly distributed.

A

RAND()

35
Q

Name 3 continuous probability distributions.

A

Uniform Probability Distribution
Normal Probability Distribution
Exponential Probability Distribution

36
Q 
f(x) = 1/(b-a) for a <= x <=b
f(x) = 0 elsewhere
A

Uniform Probability Density Function

37
Q

E(x) = (a+b)/2

A

Expected Value of a Uniform Probability Distribution

38
Q

Var(x) = (b-a)^2 / 12

A

Variance of a Uniform Probability Distribution

39
Q

The most important distribution for describing a continuous random variable. It is widely use in statistical inference for applications such as heights of people, tests scores, rainfall amounts, scientific measurements, etc.

A

Normal Probability Distribution

40
Q

Which probability distribution has a skewness measure of zero (i.e. it is symmetric).

A

Normal Probability Distribution

41
Q

Normal probability distributions are defined by its _________ and ___________ .

A

Mean

Standard Deviation

42
Q

The highest point on the normal curve is at the _______ / _______ / _______ .

A

Mean
Median
Mode

43
Q

The _________ determines the width of the normal curve.

A

Standard Deviation

44
Q

The empirical rule states that _____ % of values of a normal random variable are within +/- 1 standard deviation of its mean.

A

68%

45
Q

The empirical rule states that _____ % of values of a normal random variable are within +/- 2 standard deviation of its mean.

A

95%

46
Q

The empirical rule states that _____ % of values of a normal random variable are within +/- 3 standard deviation of its mean.

A

99.7%

47
Q

The letter ___ is used to designate the standard normal random variable.

A

z

48
Q

z = (x-μ)/σ

A

The formula for z-scores. Used to convert a normal probability distribution to a standard normal probability distribution.

49
Q

The probability distribution used to describe time between vehicle arrivals at a toll booth, time required to complete a questionnaire, distance between major defects in a highway, etc.

A

Exponential Probability Distribution

50
Q

For an exponential distribution, the ________ and ________ are equal.

A

Mean

Standard Deviation

51
Q

The probability distribution that is skewed to the right.

A

Exponential Probability Distribution

52
Q

An entity on which data are collected.

A

Element

53
Q

A collection of all the elements of interest.

A

Population

54
Q

A subset of the population.

A

Sample

55
Q

The population from which the sample is drawn.

A

Sampled Population

56
Q

A list of the elements from which the sample will be selected.

A

Frame

57
Q

Some examples of ________ populations are: organization membership rosters, credit card account numbers, inventory product numbers, etc.

A

Finite

58
Q

Some examples of _______ populations are: parts being manufactured on a production line, transactions occurring at a bank, telephone calls arriving at a technical help desk, etc.

A

Infinite

59
Q

A form of statistical inference in which data from the sample are used to compute a value of a sample statistic that serves as an estimate of a population parameter.

A

Point Estimation

60
Q

_____ is the point estimator of the population mean μ.

A

X Bar

61
Q

_____ is the point estimator of the population standard deviation σ.

A

S

62
Q

_____ is the point estimator of the population proportion p.

A

P Bar

63
Q

The population about which we want to make inferences.

A

Target Population

64
Q

The population from which the sample is actually taken.

A

Sampled Population

65
Q

The probability distribution of all possible values of the sample mean x bar.

A

Sampling Distribution of X Bar

66
Q

E(x bar) = ?

A

Population Mean μ

67
Q

When the sample size is increased, the standard error of the sample mean is increased / decreased.

A

Decrease

68
Q

The probability distribution of all possible values of the sample proportion p bar.

A

Sampling Distribution of P Bar

69
Q

E(p bar) = ?

A

Population Proportion p

70
Q

In stratified random sampling, the best results are obtained when the elements in one stratum form a heterogeneous / homogeneous group.

A

Homogeneous

71
Q

In cluster sampling, ideally, the elements in each cluster form a heterogeneous / homogeneous group.

A

Heterogeneous

72
Q

Name 4 probability sampling methods.

A

Simple Random
Stratified
Cluster
Systemic

73
Q

Name 2 nonprobability sampling method.

A

Convenience

Judgment

Business Statistics I (5 decks)

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