Analyzing data in SPSS Using
Descriptive Statistics Procedures:
It helps
you draw conclusions from your data by statistically analysing it using SPSS
(Statistical Package for the Social Sciences).
There
are four areas that will influence you choice of analysis;
1
The type of data you have gathered, (i.e. Nominal/Ordinal/Interval/Ratio)
2
Are the data paired?
3
Are they parametric?
4
What are you looking for? Differences, correlation etc?
The type
of data you gather is very important in letting you know what a sensible method
of analysis would be and of course if you don't use an appropriate method of
analysis your conclusions are unlikely to be valid. Consider a very simple
example, if you want to find out the average age of cars in the car park how would
you do this, what form of average might you use? The three obvious ways of
getting the average are to use the mean, median or mode. Hopefully for the
average of car you would use the mean or median. How might we though find the
average colour of car in the car park? It would be rather hard to find the
mean! for this analysis we might be better using the mode, if you aren't sure
why consult the glossary. You can see then even in this simple example that
different types of data can lend themselves to different types of analysis.
In the
example above we had two variables, car age and car colour, the
data types were different, the age of car was ratio data, we know this
because it would d be sensible to say "one car is twice as old as
another". The colour however isn't ratio data; it is categorical (often
called nominal by stats folk) data.
Tips before you begin:
• Make sure
your data set is open before attempting to run any analyses.
• During
analyses, right click on terms or buttons in the dialog boxes to learn about
their functions.
• The Help
button in the dialog boxes maybe clicked at any time during analyses for more
information on that particular procedure.
• Click the
Reset button to clear the dialog box and begin a fresh analysis.
• Click the
Cancel button to exit that dialog box without saving changes.
Choose a Procedure:
• Frequencies
• Descriptives
• Explore
• Crosstabs
• Ratio
FREQUENCIES
The
Frequencies procedure provides statistics and graphical displays that are
useful for describing many types of variables. For a first look at data, the
Frequencies procedure is a good place to start.
For
a frequency report and bar chart, the distinct values can be arranged in
ascending or descending order or the categories can be ordered by their
frequencies. The frequencies report can be suppressed when a variable has many
distinct values. Charts may be labeled with frequencies (the default) or
percentages.
DESCRIPTIVES
The
Descriptives procedure displays univariate summary statistics for several
variables in a single table and calculates standardized values (z scores).
Variables can be ordered by the size of their means (in ascending or descending
order), alphabetically, or by the order in which you select the variables (the
default).
EXPLORE
The
Explore procedure produces summary statistics and graphical displays, either
for all of your cases or separately for groups of cases. There are many reasons
for using the Explore procedure - data screening, outlier identification,
description, assumption checking, and characterizing differences among
subpopulations (groups of cases). Data screening may show that you have unusual
values, extreme values, gaps in the data, or other peculiarities. Exploring the
data can help to determine whether the statistical techniques that you are
considering for data analysis are appropriate. The exploration may indicate
that you need to transform the data if the technique requires a normal
distribution. Or, you may decide that you need nonparametric tests.
CROSSTABS
The
Crosstabs procedure forms two-way and multiway tables and provides a variety of
tests and measures of association for two-way tables. The structure of the
table and whether categories are ordered determine what test or measure to use.
Crosstabs
statistics and measures of association are computed for two-way tables only. If
a row, a column, and a layer factor (control variable) are specified, the
Crosstabs procedure forms one panel of associated statistics and measures for
each value of the layer factor (or a combination of values for two or more
control variables). For example, if gender is a layer factor for a table of
married (yes, no) against life (is life exciting, routine, or dull), the
results for a two-way table for the females are computed separately from those
for the males and printed as panels following one another.
RATIO
The
Ratio Statistics procedure provides a comprehensive list of summary statistics
for describing the ratio between two scale variables. The output can be sorted
by values of a grouping variable in ascending or descending order. The ratio
statistics report can be suppressed in the output and the results saved to an
external file.
By: Team H
Author: Akanksha Durgvanshi
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