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```					    SPSS Tutorial

AEB 37 / AE 802
Marketing Research Methods
Week 5
SPSS
• You can open an excel file directly
from SPSS
information on the variables
network drive:
www.rdg.ac.uk/~aes02mm/supermarkets.sav
• Start SPSS
• Open the file
Variable view
Data view
Case summaries
• Analyze / Report / Case
summaries
– Select target variable(s)
– Select grouping variable(s)
Variable(s) you are
interested in

Grouping
variables

Do not limit/display
cases
the statistics you
need
Output window
Categorising
variables

• Transform/categorize variables
– Select variable
– Choose number of categories
Tables

• Analyze / Custom Tables / General Tables
– Choose variables to be represented
– Tick summary option
– Choose summary statistic
– Choose layer
Example: average amount spent for each supermarket by
those with and without a car (layer)
TABLES

1. Select the variable to be
measured and summarised

2. Click “Is summarized” +
EDIT STATISTICS and
select the statistics you want

5. Select
columns and
layers vars

6. Click OK
for output
Own a car No
Supermarket
Asda     Kwiksave      Safeway     Tesco     Waitrose
Monthly   Mean                      55.57      33.52         52.21     65.06      67.58
amount    Std Deviation              8.02       4.54          4.46       5.50       3.29
spent     Standard Error of Mean     1.75         .93         1.69       1.42       2.33

Own a car Yes
Supermarket
Asda     Kwiksave      Safeway     Tesco     Waitrose
Monthly   Mean                      53.59      30.75         54.11     66.28      70.66
amount    Std Deviation              9.44       4.15          6.52       5.29       3.39
spent     Standard Error of Mean     1.75       1.25          1.81       1.18       1.20
Basic statistics and
confidence intervals
• Analyze /
Descriptive
Statistics /
Explore
– Choose variables
– Choose factor(s)
– Chose level of
confidence
Graphs

• Graphs / Histogram
• Graphs / Pie or
• Graphs / Interactive / Pie
Correlations
• Analyze / Correlate / Bivariate
– Choose variables
– Check / edit output

Example:   relation between income,
monthly amount spent and age
Principal components
analysis
Principal components
analysis: basic steps
• Select the variables to perform the
analysis
• Set the rule to extract principal
components
• Give instruction to save the
principal components as new
variables
• Examine output
Analyze /Data reduction
Select the variables

Press here

Select
here
Define extraction method

2. Select
Correlation       3. Extraction
matrix            technique

1. Click
here first         Extraction rule
Save components score

1. Click
here first

Tick this
box
Run the analysis
Output(1)

Communalities
Output (2)
Component Matrixa

Component
1             2        3                4           5
Vegetables expenditure       .192         -.345     -.127            .383        .199
% spent in own-brand
.646         -.281        -.134        -.239       -.207
product
Own a car                    .536          .619        -.102         -.172 6.008E-02
% spent in organic food      .492         -.186         .190          .460      .342
Vegetarian              1.784E-02    -9.24E-02          .647         -.287      .507
Household Size               .649          .612         .135    -6.12E-02 -3.29E-03
Number of kids               .369          .663         .247          .184 1.694E-02     Components
Weekly TV watching
(hours)
.124    -9.53E-02          .462         .232       -.529
interpretation
2.989E-02          .406        -.349         .559   -8.14E-02
(hours)
Surf the web                 .443         -.271          .182   -5.61E-02       -.465
Yearly household income      .908    -4.75E-02     -7.46E-02         -.197 -3.26E-02
Age of respondent            .891    -5.64E-02     -6.73E-02         -.228 6.942E-04
Monthly amount spent         .810         -.294    -4.26E-02          .183       .173
Meat expenditure             .480         -.152          .347         .334 -5.95E-02
Fish expenditure             .525         -.206         -.475   -4.35E-02        .140
Extraction Method: Principal Component Analysis.
a. 5 components extracted.

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 views: 53 posted: 7/30/2012 language: English pages: 25