Survey Analysis and Reporting in the Cloud

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Innovative Survey Reporting - The movie

Drobots introduction movie (2 min)

Why Drobots are the innovation in Survey analysis

Why drobots are created to analyze surveys

what Drobots Survey Analysis software does

Drobots versus other survey analysis software

Drobots Software Screenshots

Analyzing frequencies

Selecting your data for analysis

Calculating means

Detailed drill down on answers

Cross tables

Advanced Survey Statistics

Survey Reporting examples using Drobots

Customer Satisfaction Survey

e-Government Survey

Lingerie Branding Survey

Software updates, release notes

Software Revision 6

Cross tables
Created by Drobots on 10/23/2010 2:05:28 PM

A cross table is used to plot all the responses for one question to a split variable. E.g. If you want to find out how the responses for a question are divided between men and women, or between income levels, or between involvement levels with your company, or between…

To start, select the column variable (split variable) and the row variable you want to cross. The cross table will appear below.

In the left column you will see the possible responses for the question you selected. In the top row you will see the response options for the split variable you selected.

In the second column you’ll see a legend for the values to the right.

“Count = Fij” shows the exact number of times that row’s response was given by that respondent with the column characteristic.
“Row %” provides you with the division (in percentages) of the split variables.
“Column %” provides you with the division (in percentages) of each question response.
“Std. Residual” indicates the amount of over- or underrepresentation of the cell’s values. In other words: considering the expected value for that cell, how does it compare to the real value?

The cell colors are determined based upon the Std. Residual value, for which you’ll find a legend below.

An example:
A course satisfaction study (see “DEMO” dataset) is set up by a university to find out what students think about the quality of the education the school offers.

The researcher wants to find out where the remarkable responses lie, considering the score for complexity students gave the course, and the professor’s friendliness.

The researcher uses a cross table for this. He selects “Complexity” for a column variable, and he selects “(Q16) The professor was friendly to individual students” as row variable.

In the new graph below the researcher concludes the following:

There were a remarkably high number of students that both said they felt the complexity of the course was too high and that certainly didn’t think the professor was friendly to students.
There were a remarkably low number of students that both said they felt the complexity of the course was too high and that certainly agreed that the professor was friendly to students.
There were a rather high number of students that both said they felt the complexity of the course was low and that certainly agreed that the professor was friendly to students.

As is to be expected, the researcher can safely say that students who feel the course is too complex, don’t perceive the professor as very friendly. (And vice versa)

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