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BusinessResearch Method
Chapter 20:
Basic Data Analysis: DescriptiveStatistics
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What are the limitations of descriptive statistics?Descriptive
statistics are limited in so much that they only allow youto make
summations about the people or objects that you haveactually
measured. You cannot use the data you have collected togeneralize
to other people or objects (i.e., using data from a sample to
infer the properties/parameters of a population). For example,
if youtested a drug to beat cancer and it worked in your patients,
you cannotclaim that it would work in other cancer patients only
relying ondescriptive statistics (but inferential statistics would
give you this
opportunity).
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Steps in Data Preparation
Editing
Coding
Entering Data
Data Tabulation
Reviewing Tabulations
Statistically adjusting the data
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EditingTreatment of Unsatisfactory Results:
Returning to the Field The questionnaires with
unsatisfactoryresponses may be returned to the field, where the
interviewers
recontact the respondents.
Assigning Missing Values If returning the questionnaires to
thefield is not feasible, the editor may assign missing values
tounsatisfactory responses.
Discarding Unsatisfactory Respondents In this approach,
therespondents with unsatisfactory responses are simply
discarded.
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Coding Data and Data Code book Data entry:Data entry refers to
the creation of a computer file that holds the raw data taken
fromall of the questionnaires deemed suitable for analysis.
Data code book :
Data Coding:Data Coding defined as the identification of codes
that pertain to the possibleresponses for each question on the
questionnaire.
Data code book identifies all of the variable names and
codenumbers associated with each possible response to eachquestion
that makes up the data set.
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A codebook generally contains the following information:column
numberrecord numbervariable numbervariable name
question numberinstructions for coding
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Data Reduction
Data Reduction is defined as the process of describing
datamatrix by computing a small number of measures that
characterize the data set.
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Four Functions of Data Reduction
1.Summarization2. Conceptualization3. Communication
4. Interpolation
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Types of Statistical Analyses Usedin Research
Five basic types of statistical analyses Descriptive analysis
Inferential analysis Differences analysis Associative analysis
Predictive analysis
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Types of Statistical Analyses
Used in Research Five Types of Statistical Analysis:
1. Descriptive analysis: used to describethe data set
2. Inferential analysis: used to generateconclusions about the
populationscharacteristics based on the sample data
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Types of Statistical Analyses
Used in Research3. Differences analysis: used to compare
the mean of the responses of one group
to that of another group4. Associative analysis: determines
the
strength and direction of relationships
between two or more variables
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Types of Statistical Analyses
Used in Research5. Predictive analysis: allows one to make
forecasts for future events
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Tabulation
Tabulation - Orderly arrangement of data ina table or other
summary format
Frequency table Percentages
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Frequency Table
The arrangement of statistical data in a row-and-column format
that exhibits the count
of responses or observations for eachcategory assigned to a
variable
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Descriptive Analysis
Two sets of descriptive measures: Measures of central tendency:
used to
report a single piece of information thatdescribes the most
typical response to aquestion
Measures of variability: used to reveal thetypical difference
between the values in aset of values
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Measure of
Central Measure ofType of Scale Tendency Dispersion
Nominal Mode NoneOrdinal Median PercentileInterval or ratio Mean
Standarddeviation
Central Tendency
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Measures of Central Tendency
Use to report a single piece of informationthat describes the
most typical response to aquestion
The term central tendency applies to anystatistical measure used
that somehowreflects a typical or frequently response
3 measures of central tendency arecommonly used mode, median
& mean
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Descriptive Analysis Measures of Central Tendency:
Mode: the value in a string of numbers thatoccurs most often
Median: the value whose occurrence lies inthe middle of a set of
ordered values
Mean: sometimes referred to as thearithmetic mean; the average
valuecharacterizing a set of numbers
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Descriptive Analysis Measures of Variability:
Frequency distribution: reveals the number (percent)
ooccurrences of each number or set of numbers
Range: identifies the maximum and minimum values inset of
numbers Standard deviation: indicates the degree of variation
in
a way that can be translated into a bell-shaped
curvedistribution
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Cross-Tabulation
A technique for organizing data by groups,categories, or
classes, thus facilitating
comparisons; a joint frequency distributionof observations on
two or more sets ofvariables
Contingency table- The results of a cross-tabulation of two
variables, such as surveyquestions
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Cross-Tabulation
Analyze data by groups or categories Compare differences
Contingency table Percentage cross-tabulations
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Base
The number of respondents or observations(in a row or column)
used as a basis for
computing percentages
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Tworatingscales 4 quadrants
two-dimensionaltable
Importance-PerformanceAnalysis)
Quadrant Analysis
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Data Transformation
Data conversion Changing the original form of the data to a
new format More appropriate data analysis New variables
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Interpretation
The process of making pertinent inferencesand drawing
conclusions
concerning the meaning and implications ofa research
investigation
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