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8/14/2019 Business Research Session 11 Data Analysis
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Session 11
Data Analysis and Presentation
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Prior to analysis
Field and in house editing for consistency
and completeness
Coding of free response questions
Behavioural and segmenting data (SPSS)
Method of entry into computer
Descriptive and cross tabulation data Analysis by difference / Quadrant analysis
/ Perceptual mapping / Bakers box
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Forms of Analysis
Normally analysis is question drivenwhat information is required to answer aspecific question
Two broad main types of analysis:
Analysis of difference
Analysis of relationships / causation
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Hypothesis testing
The null and alternative hypothesis
Significance level is crucial. Could thedifference observed be due to chance, orcan we be at least 95% sure that it is dueto the phenomenon being tested.
Sample size is also critical in assuring thelevel of confidence and error which mightbe anticipated.
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Exercise: Are IIS students more
satisfied than those at Ram?
The hypothesis is that IIS students are
more satisfied than students at RAMoverall.
Average rating for students overall at Ramis 3.6 For IIS it is 3.9, based on a sampleof 100, with an SD of 1.5
Two tailed test (0.025% either end, Z =1.96)
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Chi Squared Test
A test for significance in the analysis of
frequency distributions
Based on the difference betweenobserved and expected results if therewas no difference
Can be used for both ordinal and nominaldata sets
Easiest and most widely used test!
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Exercise: Boys are better than girls!
Out of the 99 students who took the MBA
Interim examination in Business ResearchMethods, 14 of the 33 men present scored
less than 30 marks, and overall 33 peoplescored below 30.
Is there a significant difference in
performance between the men andwomen?
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Other methods of testing between
groups
t-test, used to calculate differences
between means
Z test for comparing proportions
Analysis of variance (ANOVA)
F test / F ratio
(See Zikmund: Pages 521 534)
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Measures of Association
Association: Where one variable correlates withanother
Co-variance: Where two variables are
associated together, but both are associatedwith a third (undefined) variable
Coefficient of determination: A measure of theexplanation of one variable by another. It is thesquare of the correlation coefficient and is thebasis of factor analysis
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Regression
Linked to association, but regression seeks tocreate a formula to explain the association.
Two forms; straight line (y = mx + c) or non
linear of several forms Regression line plotted by least squares and is
the line of best fit
Used extensively in sales forecasting, butignores the point of inflexion problem seen alsoin extrapolation
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Bakers Box: An example of best
fit regression line
I Dont
Believe
IT
Value
Added
The GoldenTriangle
Avis
Country
Cheap AndNasty
Cheap AndCheerful
ITS A
Rip Off
You MustBe Joking
Low Quality
High QualityLine Of
Expectation
High
Price
Low
Price
Gullibility
Credibility
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Exercise: Expansion at Rotiboy!
Rotiboy have established that the sales for anoutlet of their business (y) can be defined by thenumber of people living within one mile of the
outlet (x) by the line y = 20 + 0.55x, where boththe constant is denominated in 000 baht, and x
as 000 population.
On the basis of this data what is the likely
weekly revenue (in baht 000) for an outletestablished where there is a local population of10,000
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Multivariate Analysis
Multivariate regression analysis ( TheFishbein model of attitude measurement)
Multivariate Analysis of Variance
(MANOVA) Factor analysis: Reduction of complex
variables into smaller number of factors
Cluster analysis CHAID (Chi squared automatic interaction
detection)
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Tesco and the use of AID
Based on customer data collected at POS
Analysed by AID to establish levels ofproduct penetration and specific customercharacteristics
Can isolate groups as small as 5,000 froma population of 26 million!
Visit www.dunnhumby.co.uk
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Communicating Research
The communicator
The message
The medium The Audience
Feedback
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Oral communication
Stand up, speak up, and shut up. There isa limit to peoples concentration
Graphics need to be simple (not more than
12 figures on a slide). More than thishighlight
Be aware of your personal body language
If you use technology, make sure it works! Have clear objectives as to what to put
over
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Some tips on oral presentations
Variety; in voice, tone, movement, bodylanguage, all elements of posture, etc. Suit yourbody language to the message
Be sure you can get away with humour. Be verycareful if you use it with an internationalaudience as it is very cultural!
Look at your audience, good eye contact
Do not distribute report beforehand if you wantto be selective in how you take from it.
Leave time at the end for questions
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Presenting statistical results
Never assume the audience knows as muchabout statistics as you do!
Dont try and blind them with statistics
Remember there are lies, dam lies, andstatistics Many are very cynical of them!
Use statistics to demonstrate data in terms of its
use in making a decision. Applied statisticsrather than statistics for their own sake!
Explain what they mean!
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Written reports
Length and level of reading are inversely related Always provide an annotated executive
summary with guideposts to deeperexplanations as required.
Make sure the report provides the informationrequired in order to come to the decisionrequired
Use tables, graphs and charts as appropriate to
illustrate data and make points. Remember a multicoloured pie chart loses a lot
in black and white!
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Specialist AnalyticalTechniques
CHAID (Chi Squared Automatic Interaction
Detection)
ACORN / TGI Retail Location
Market Penetration Analysis
Sensitivity Analysis
Resource Allocation