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Flashcards in Exam 1 Deck (59)
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1
Q

Data

A
  • the facts and figures collected, analyzed, and summarized for presentation and interpretation
2
Q

Observation

A
  • the set of measurements obtained for a particular element.
3
Q

Nominal Scale

A
  • the data for a variable consists of labels or names (the order of the labels IS NOT meaningful).
4
Q

Ordinal Scale

A
  • the data for a variable consists of labels or names (the order of the labels IS meaningful).
5
Q

Interval Scale

A
  • numeric data where the interval between values is a fixed unit of measure.
6
Q

Ratio Scale

A
  • the data have the properties of the interval scale, and the ratio of 2 values is meaningful.
7
Q

Categorical Data

A
  • use labels or names to identify an attribute of an ele-ment.
8
Q

Quantitative Data

A
  • Use of numbers
9
Q

Cross-Sectional Data

A
  • are data collected at approximately the same point in time.
10
Q

Time Series Date

A
  • data collected over several time periods.
11
Q

Statistical Inference

A
  • The process of using data collected on a sample to draw conclusions about a population
12
Q

Population

A
  • the set of all elements of interest in a particular study.
13
Q

Census

A
  • The process of collecting data on the entire population
14
Q

Sample

A
  • a subset of the population
15
Q

Sample Survey

A
  • The process of collecting data on a sample
16
Q

Frequency Distribution

A
  • Tabular summary of the data showing the number of items in each class.
17
Q

Relative Frequency Distribution

A
  • Shows the proportion of items belonging to a class.

- Relative Frequency = Frequency/n

18
Q

Bar Graph

A
  • Graph showing the frequency, relative frequency or percent frequency distribution.
19
Q

Pie Chart

A
  • Presents the relative or percent frequency distribution.
20
Q

Histogram

A
  • Graph that shows the frequency, relative frequency or percent frequency distribution
21
Q

Cumulative Frequency Distributions

A
  • Shows the number of data items with values less than or equal to the upper class limit
22
Q

Stem and Leaf Display

A
  • Shows the rank order of the data.

- Shows the shape of the data set

23
Q

Cross Tabulations

A
  • Tabular summary of two variables
24
Q

Scatter Diagram

A
  • a graphical representation for two quantitative variables.
25
Q

Sample Statistics

A
  • Numbers that describe a sample
26
Q

Population Parameters

A
  • Numbers that describe a population
27
Q

Mean

A
  • Average Value
28
Q

Median

A
  • Middle Value
29
Q

Mode

A
  • Value that occurs most often
30
Q

Percentiles

A
  • The pth percentile is the value with at least p percent of the observations less than or equal to it and at least (100p) percent of the observations greater than or equal to it.
31
Q

Quartiles

A
  • 1st Quartile = 25th percentile
  • 2nd Quartile = 50th percentile = median
  • 3rd Quartile = 75th percentile
32
Q

Outliers

A
  • observations that are much larger or smaller than the rest of the data.
33
Q

Small Outliers

A
  • less than Q1 − 1.5(Q3 − Q1).
34
Q

Large Outliers

A
  • greater than Q3 + 1.5(Q3 − Q1)
35
Q

Range

A
  • The difference between the largest and smallest numbers in the data set.
36
Q

Interquartile Range (IQR)

A
  • The difference between the third quartile and the first quartile.
37
Q

Variance

A
  • The variance is based on the difference between each observation and the mean.
38
Q

Standard Deviation

A
  • The square root of the variance.
39
Q

Z-Scores

A
  • z-scores give the relative locations of observations within the data
  • z-scores show how far a particular value is from the mean
  • Z-Score = (Observation - Mean) / Standard Deviation
  • z is the number of standard deviations the observation is from the mean
40
Q

Empirical Rule

A
  • For a mound-shaped distribution (uni modal, symmetric, normal distribution) we can get better approximations
    – 68.3% of the values of a normal random variable are within plus or
    minus one standard deviation of its mean.
    – 95.4% of the values of a normal random variable are within plus or minus two standard deviation of its mean.
    – 99.7% of the values of a normal random variable are within plus or minus three standard deviation of its mean
41
Q

Probability

A
  • a numerical measure of the likelihood that an event will occur
42
Q

Experiment

A
  • a process that generates well defined outcomes
43
Q

Sample Space

A
  • the set of all outcomes
44
Q

Classical Method

A
  • Used when all the experimental outcomes are equally likely.
45
Q

Relative Frequency Method

A
  • used when data are available to estimate the proportion of the time each outcome occurs
46
Q

Subjective Method

A
  • used when we cannot assume that the outcomes are equally likely, and we have little relevant data available
47
Q

Event

A
  • A collection of outcomes (or sample points)
48
Q

Complement of an event

A
  • Suppose A is an event. The complement of A, denoted by Ac is another event that consists of all possible outcomes that are not in A.
49
Q

Union of Two Events

A
  • If A and B are events, the union of A and B, denoted A ∪ B, is the event containing all outcomes that belong to A, B, or both.
50
Q

Intersection of 2 events

A
  • If A and B are events, the intersection of A

and B, denoted A ∩ B, is the event containing all outcomes that belong to both A and B.

51
Q

The Addition Law

A
  • P(A ∪ B) = P(A) + P(B) − P(A ∩ B)
52
Q

Mutually Exclusive

A
  • If events A and B have no outcomes in common

- P(A ∪ B) = P(A) + P(B)

53
Q

Random Variable

A
  • a numerical description of an experiment.
54
Q

Discrete Random Variable

A
  • A random variable that assumes either a finite number of values or an infinite sequence of values such as 0, 1, 2
55
Q

Continuous Random Variable

A
  • A random variable that may assume any numerical value in an interval or collection of intervals
56
Q

Probability Distributions

A
  • describe how probabilities are distributed over the values of the random variable.
57
Q

Expected Value or Mean

A
  • compute a measure of central location for a discrete random variable.
58
Q

Variance (Probability)

A
  • measure the variability for a discrete random variable.
59
Q

Normal Distribution

A
  • the most important probability distribution for continuous random variables.