Complete the following for this assignment· Compare and contras.docx

Complete the following for this assignment:
· Compare and contrast the management information systems
(MIS) in place in 2 distinctly different organizations.
· Compare each organization's use of information systems to
help manage internal operations and to make decisions.
· Assess how these two organizations use information
technology for competitive advantage.
· Appraise the individual and organizational consequences of
the use of information technology, and recognize potential
security breaches and computer crimes.
Present your findings in a Word document of 4-5 body pages
(1400-1750 words) formatted in APA style.
Title page, Reference page, Abstract, Introduction, and
Conclusion
Copyright © 2012 Wolters Kluwer Health | Lippincott Williams
& Wilkins
Chapter 16
Descriptive Statistics
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& Wilkins

Question
Tell whether the following statement is true or false:
Nominal measurement is the ranking of objects based on their
relative standing on an attribute.
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Answer
False
Nominal measurement: the classification of characteristics into
mutually exclusive categories
Ordinal measurement: the ranking of objects based on their
relative standing on an attribute
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MeasurementNominal measurement: the classification of
characteristics into mutually exclusive categoriesOrdinal
measurement: the ranking of objects based on their relative
standing on an attributeInterval measurement: indicating not
only the ranking of objects but the amount of distance between
themRatio measurement: distinguished from interval
measurement by having a rational zero point
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Descriptive StatisticsSummarize quantitative dataDescribe
quantitative data

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Question
Frequency distributions impose order on raw data. Numeric
values are ordered from lowest to highest, accompanied by a
count of the number of times each value was obtained.
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Answer
True
Frequency distributions impose order on raw data. Numeric
count of the number (or percentage) of times each value was
obtained.
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Frequency DistributionsImpose order on raw data Numeric
count of the number (or percentage) of times each value was
obtained.Common methods of displayHistogramsFrequency
polygons

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Distribution Symmetric: two halves are mirror images of each
otherSkewed: asymmetric with one tail longer than the
otherPositively skewedNegatively skewedModality: number of
peaksUnimodalMultimodalNormal distribution
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Question
What is the median?
Average or typical value of a set of scores
Value that occurs most frequently in a distribution
Point above which and below which 50% of the cases fall
Arithmetic average of all scores
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Answer
C
Central tendency are indexes, expressed as a single number, that
represent the average or typical value of a set of scores. The
mode is the value that occurs most frequently in a distribution,
the median is the point above which and below which 50% of
the cases fall, and the mean is the arithmetic average of all
scores.
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Central TendencyCentral tendency are indexes, expressed as a
single number, that represent the average or typical value of a
set of scores. Mode: value that occurs most frequently in a
distributionMedian: point above which and below which 50% of
the cases fallMean: arithmetic average of all scores
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Question
Range is the distance between the highest and lowest scores.
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Answer
True
Range is the distance between the highest and lowest scores.
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VariabilityVariability: how spread out the data areRange:
distance between the highest and lowest scoresStandard
deviation: indicates how much, on average, scores deviate from
the meanCalculationDeviation scores represent the degree to
which each person’s score deviates from the mean. The variance
is equal to the SD squared.

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Bivariate Descriptive StatisticsRelationships between two
variablesContingency table two-dimensional frequency
distribution in which the frequencies of two nominal- or
ordinal-level variables are crosstabulatedCorrelation
coefficients describe the direction and magnitude of a
relationship between two variables. Product–moment correlation
coefficient (Pearson’s r)—interval or ratioSpearman’s rho
coefficient—ordinalScatter plot
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Risk IndexesAbsolute risk reduction: expresses the estimated
proportion of people who would be spared from an adverse
outcome through exposure to an interventionRelative risk:
estimated proportion of the original risk of an adverse outcome
that persists among people exposed to an interventionRelative
risk reduction: estimated proportion of untreated risk that is
reduced through exposure to the intervention
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Risk IndexesOdds ratio: ratio of the odds for the treated versus
untreated groupNumber needed to treat: estimate of how many
people would need to receive the intervention to prevent one
adverse outcome

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Chapter 15
Developing and Testing Self-Report Scales
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Question
Scale development begins with a sound conceptualization of the
construct (the latent variable) to be measured, excluding its
dimensionality.
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Answer
False
Scale development begins with a sound conceptualization of the
construct (the latent variable) to be measured, including its
dimensionality.

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Conceptualizing the ConstructScale development begins with a
sound conceptualization of the construct (the latent trait) to be
measured, including its dimensionality.Unobservable latent
traitUnidimensional
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Type of ScaleScale selection is done before items can be
generated.
Two broad categories of multi-item reflective scalesTraditional
summated rating (Likert)Latent trait
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Generating Item PoolSourcesExisting instrumentsResearch
literatureConcept analysesIn-depth studiesClinical observations
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Decisions about Item FeaturesNumber of itemsResponse
itemsPositive and negative stemsItem intensityItem time frames
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Number of ItemsDomain sampling model: homogeneous set of
items from a hypothetical universe of itemsGoal is to provide
appropriate redundancy so idiosyncrasies can be cancelled
out.Recommends starting with 3 to 4 times as many items as
you will have in your final scale
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Response OptionsScale items contain:A stem Response
optionsFor example, strongly disagree, disagree, agree, strongly
agree
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Positive and Negative StemsThe objective was to include items
that would minimize the possibility of an acquiescence response
set—the tendency to agree with statements regardless of their
content.Many experts currently advise again including negative
and positive items on a scale.

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Item IntensityThe intensity of the statements (stems) should be
similar and fairly strongly worded.Statements should not be so
extremely worded as to result in universal rejection.
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Item Time FramesA time frame should not emerge as a
consequence of item development. It should be decided upon in
advance, based on the conceptual understanding of the construct
and the needs for which the scale is being constructed.
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Wording the Items—ReadabilityClarityJargonLengthDouble
negativesDouble-barreled items
*

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Question
Once content validity has been established at a satisfactory
level, the scale must be administered to a development sample.
What is the typical number of respondents who are
representative of the target population?
100
150
250
300
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Answer
D
Once content validity has been established at a satisfactory
level, the scale must be administered to a development sample—
typically 300 or more respondents who are representative of the
target population.
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Content ValiditySatisfactory levelDevelopment sample300 or
more respondents representative of target population
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Field Testing the InstrumentDeveloping the sampling
planDeveloping a data collection planPreparing for data
collection
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Question
Exploratory factor analysis is used to reduce a small set of
variables into a larger set of underlying dimensions, called
factors.
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Answer
False
Exploratory factor analysis is used to reduce a large set of
variables into a smaller set of underlying dimensions, called
factors.
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Analysis of Scale Development Data
Basic item analysisInter-item correlationItem–scale correlations
Exploratory factor analysis (EFA)Factor extractionPrincipal
components analysis (PCA)Factor rotation—orthogonal or
oblique

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Illustration of Factor Rotation
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Scale Refinement and ValidationRevising the scaleScoring the
scaleConducting a validation study
Confirmatory factor analysis
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Confirmatory Factor Analysis CFA is a second study often
undertaken to validate the scale.A subset of sophisticated
statistical techniques (structural equation modeling)Involves
tests of a measurement modelStipulates the hypothesized
relationship between latent traits and manifest variables (items)
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& Wilkins
Interpretability of Scale ScoresInterpretability: the degree to
which one can assign qualitative meaningPercentileStandard
scoresNormsCutoff points
& Wilkins
Critiquing Scale Development StudiesMethods used Whether
the evidence regarding the scale’s psychometric adequacy is
sufficiently soundSee Box 15.1
*

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