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Business Statistics > Vocabulary > Flashcards

Vocabulary Flashcards

0
Q

Data

A

Facts and figures collected, analyzed, and summarized for presentation and interpretation

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1
Q

Statistics

A

Art of science of collecting, summarizing, analyzing, presenting, and interpreting data

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2
Q

Data Set

A

All the data collected in a particular study

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3
Q

Elements

A

Entities on which data are collected

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4
Q

Variable

A

A characteristic of interest for elements

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5
Q

Observation

A

Set of measurements obtained for a particular element

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6
Q

Nominal Scale

A

Scale of measurement for a variable when data are labels or names used to identify an attribute of an element. Nominal data may be nonnumeric or numeric

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7
Q

Ordinal Scale

A

Scale of measurement for a variable if the data exhibit the properties of nominal data and the order or rank of the data is meaningful. Can be nonnumeric or numeric

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8
Q

Interval Scale

A

Scale of measurement for a variable if the data demonstrate the properties of ordinal data and interval between values is expressed in terms of a fixed unit of measure. Always numeric

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9
Q

Ratio Scale

A

Scale of measurement for a variable if the data demonstrate all properties of interval data and ratio of two values is meaningful. Always numeric

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10
Q

Categorical Data

A

Labels/names used to identify an attribute of each element. Use either nominal or ordinal scale of measurement. May be nonnumeric or numeric

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11
Q

Quantitative Data

A

Numeric values that indicate how much or how many of something. Obtained using either the interval/ratio scale of measurement

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12
Q

Categorical Data

A

Has categorical data

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13
Q

Quantitative Data

A

Variable with quantitative data

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14
Q

Cross-Sectional Data

A

Data collected at the same or approximated the same point in time

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15
Q

Time Series Data

A

Data collected over several time periods

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16
Q

Descriptive Statistic

A

Tabular, graphical and numerical summaries of data

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17
Q

Population

A

Set of all elements of interest in a particular study

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18
Q

Sample

A

Subset of the population

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19
Q

Census

A

Survey to collect data on entire population

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20
Q

Sample Survey

A

Survey to collect data on a sample

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21
Q

Statistical Inference

A

Process of using data obtained from a sample to make estimates or test hypotheses about the characteristics of a population

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22
Q

Frequency Distribution

A

Tabular summary of data showing the number (frequency) of data values in each of several non overlapping classes

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23
Q

Relative Frequency Distribution

A

Tabular summary of data showing the fraction or proportion of data values in each of several non overlapping classes

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24
Q

Percent Frequency Distribution

A

Tabular summary of data showing the percentage of data values of each of several non overlapping classes

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25
Q

Bar Chart

A

Graphical device for depicting categorical data that have been summarized in a frequency, relative frequency or percent frequency distribution

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26
Q

Pie Chart

A

Graphical device for presenting data summaries based on subdivision of a circle into sectors that correspond to the relative frequency for each class

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27
Q

Class Midpoint

A

Value halfway between the lower and upper class limits

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28
Q

Dot Plot

A

Graphical device that summarizes data by the number of dots above each data values on the horizontal axis

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29
Q

Histogram

A

Graphical presentation of a frequency distribution, relative frequency distribution, or percent frequency distribution of quantitative data constructed by placing the class intervals on the horizontal axis and the frequencies, relative frequencies, or percent frequencies on the vertical axis

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30
Q

Cumulative Frequency Distribution

A

Tabular summary of quantitative data showing number of data values that are less than or equal to the upper class limit of each class

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31
Q

Cumulative Relative Frequency Distribution

A

Tabular summary of quantitative data showing the percentage of data values that are less than or equal to the upper class limit of each class

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32
Q

Ogives

A

Graph of a cumulative distribution

33
Q

Exploratory Data Analysis

A

Methods that use simple arithmetic and easy to draw graphs to summarize data quickly

34
Q

Stem-and-Leaf Display

A

Exploratory data analysis technique that simultaneously rank orders quantitative data and provides insight about the shape of the distribution

35
Q

Crosstabulation

A

Tabular summary of data for two variables. The classes for one variable are represented by the rows; the classes for the other variable are represented by the columns

36
Q

Simpson’s Paradox

A

Conclusions drawn from two or more desperate cross tabulations that can be reversed when the data are aggregated into a single crosstabulation

37
Q

Scatter Diagram

A

Graphical presentation of the relationship between two quantitative variables. One variable is shown on horizontal axis and other is shown on vertical axis

38
Q

Trendline

A

Line that provides an approximation of the relationship between 2 variables

39
Q

Sample Statistic

A

Numerical value used as a summary measure for a sample

40
Q

Population Parameter

A

Numerical value used as a summary measure for a population

41
Q

Point Estimator

A

Sample statistic (Greek letters) that are used to estimate the corresponding population parameter

42
Q

Mean

A

Measure of central location computed by summing the data values and dividing by the number of observations

43
Q

Median

A

Measure of central location provided by the value in the middle when the data are arranged in ascending order

44
Q

Mode

A

A measure of location, defined as the value that occurs with greatest frequency

45
Q

Percentile

A

Value such that at least p percent of the observation are less than or equal to this value and at least (100-p) percent of the observations are greater than or equal to this value. The 50th percentile is the median

46
Q

Quartiles

A

Can be used to divide a data set into four parts, when each part containing approximately 25% of the data

47
Q

Range

A

A measure of variability, defined to be the largest value minus the smallest value

48
Q

Interquartile Range (IQR)

A

Measure of variability, defined to be the difference between the 3rd and 1st quartiles

49
Q

Variance

A

Measure of variability based in the squared deviations of the data values about the mean

50
Q

Standard Deviation

A

Measures of variability computed by taking positive square root of the variance

51
Q

Coefficient of Variation

A

Measure of relative variability computed by dividing he standard deviation by the mean and multiplying by 100

52
Q

Skewness

A

Measure of the shape of a data distribution. Data skewed to the left result in negative skewness; a symmetric data distribution results in zero skewness; and data skewed to the right result in positive skewness

53
Q

Z-score

A

Value computed by dividing the deviation about the mean by the standard deviation. A z-score value and denotes the number of standard deviations the variable is from the mean

54
Q

Chebyshev’s Theorem

A

Theorem that can be used to make statements about the proportion of data values that must be within a specified number of standard deviations of the mean

55
Q

Empirical Rule

A

Rule that can be used to compute the percentage of data values that must be within one, two, and three standard deviations of the mean for data that exhibit a bell shaped distribution

56
Q

Outlier

A

Unusually small or large data value

57
Q

Covariance

A

Measure of linear association between two variables. Positive values indicate a positive relationship; negative values indicate a negative relationship

58
Q

Correlation Coefficient

A

Measure of linear association between 2 variables that takes on values between -1 and +1. Values near +1 indicate a strong positive linear relationship; values near -1 indicate a strong negative linear relationship; and values near zero indicate the lack of a liner relationship

59
Q

Weighted Mean

A

Mean obtained by assigning each observation a weight that reflects its importance

60
Q

Grouped Data

A

Data available in class intervals as summarized by a frequency distribution. Individual values of the original data are not available

61
Q

Probability

A

A numerical measure of the likelihood that an event will occur

62
Q

Complement of A

A

The event consisting of all sample points that are not in A

63
Q

Venn Diagram

A

A graphical representation for showing symbolically the sample space and operations involving events in which the sample space is represented by a rectangle and events are represented as circles within the sample space

64
Q

Union of A and B

A

The event containing all sample points belonging to A or B or both. The union is denoted A U B

65
Q

Intersection of A and B

A

The event containing the sample points belonging to both A and B. The intersection is denoted A n B

66
Q

Addition Law

A

A probability law used to compute the probability of the Union of two events. It is P(A U B) = P(A) + P(B) - P(A n B). For mutually exclusive events, P(A n B) = 0; in this case the addition law reduces to P(A U B) = P(A) + P(B)

67
Q

Mutually Exclusive Events

A

Events that have no sample points in common; that is, A n B is empty and P(A n B) = 0

68
Q

Conditional Probability

A

The probability of an event given that another event already occurred. The conditional probability of A given B is P(A|B) = P(A n B)/P(B)

69
Q

Joint Probability

A

The probability of two events both occurring; that is, the probability of the intersection of two events

70
Q

Marginal Probability

A

The values in the margins of a joint probability table that provide the probabilities of each event desperately

71
Q

Independent Events

A

Two events A and B where P(A|B) = P(A) or P(B|A) = P(B); that is the events have no influence on each other

72
Q

Multiplication Law

A

A probability law used to compute the probability of the intersection of two events. It is P(A n B) = P(B)P(A|B) or P(A n B) = P(A)P(B|A). For independent events it reduces to P(A n B) = P(A)P(B)

73
Q

Random Variable

A

A numerical description of the outcome of an experiment

74
Q

Discrete Random Variable

A

A random variable that may assume either a finite number of values or an infinite sequence of values

75
Q

Continuous Random Variable

A

A random variable that may assume any numerical value in an interval or collection of intervals

76
Q

Probability Distribution

A

A description of how the probabilities are distributed over the values of the random variable

77
Q

Probability Function

A

A function, denoted by f(x), that provides the probability that x assumes a particular value for a discrete random variable

78
Q

Discrete Uniform Probability Distribution

A

A probability distribution for which each possible value of the random variable has the same probability

79
Q

Expected Value

A

A measure of the central location of a random variable

80
Q

Variance

A

A measure of the variability, or dispersion, of a random variable

81
Q

Standard Deviation

A

The positive square root of the variance

Business Statistics (1 decks)

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