data analysis - intro [compatibility mode]

7/29/2019 Data Analysis - Intro [Compatibility Mode]

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DATA ANALYSIS USING

SPSS


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Overview Variable

Types of variables

Qualitative

Quantitative

Data Analysis Using SPSSDr. Nelson Michael J.

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Hypothesis Testing

Type I and Type II Errors

Significance Level SPSS

Data Analysis


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Variable

A characteristic of an individual orobject that can be measured


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Types:

Qualitative and Quantitative


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Types of Variables Qualitative variables: Variables which

differ in kind rather than degree

Measured on:

1) Nominal scale indicates categorizing intorou s or classes.


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Eg. Gender, religion, race, colour,occupation, etc

2) Ordinal scale indicates ordering of items.

Eg. Agreement disagreement scale,customer satisfaction ratings, etc


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Quantitative variables: Variables whichdiffer in degree rather than kind.

Measured on:

1) Interval scale indicates rank anddistance from an arbitrary zeromeasured in unit intervals.

Eg. Temperature, examination scores,


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etc.2) Ratio scale indicates rank and distance

from a natural zero.

Eg. Height, monthly consumption,annual budget, etc


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Reliability The confidence we can place on the

measuring instrument to give us the same

numerical value when measurement isrepeated on the same object.

E . Instrument to measure the number of


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things a child can recallAssessing reliability:

Cohens kappa coefficient for categoricaldata

Cronbachs alpha for internal reliability fora set of questions


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Validity

To see how accurate is the relationshipbetween the measure and the underlying

trait it is trying to measure Eg. An instrument claimed to measure IQ

may just be testing memory


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Assessing validity:

Face validity

Predictive validity

Content validity

Construct validity


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Hypothesis Testing A Hypothesisis an assumption or claim

about some characteristic of a population,which we should be able to support orreject on the basis of empirical evidence.


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Null Hypothesis (H0) It is the presumptionthat is accepted as correct unless there isstrong evidence against it.

Alternative Hypothesis (H1) it isaccepted if H0 is rejected


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Marketing: Did the advertising strategy haveany impact in increasing the level ofproduct awareness?

Production: Is the average output of twofactories the same?

Finance: Is the avera e stock rice of the


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companys stocks less than that of thecompetitors stocks?

Human Resource: Has there been any

significant impact of 360 degree feedbacksystem on employees performance?


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Type I and Type II Errors

While testing a hypothesis, if wereject a hypothesis when it should beaccepted, it amounts to TYPE I error


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Accepting a hypothesis when itshould be rejected amounts to TYPEII error

Both types of errors can be reducedif we increase the sample size


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Significance level (p value)

The criterion that is used for acceptingor rejecting a null hypothesis is called p-value


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A p-value of 0.05 means that there is95% confidence of making the right

decision.


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SPSS

Main menus Data Editor


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Importing and Exporting data


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Data Analysis

Descriptive Statistics Frequency distribution


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- Comparison of means

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