How to Read Data Tables

If you are new to reading data tables, you may feel slightly disoriented the first time you come face to face with a mass of data. This article provides a quick overview of data tables, and how to read them.

What are Data Tables?

Most quantitative survey data is presented as a computer or data tabulation, sometimes referred to as "Data Tabs". Different software packages present data in slightly different ways; data analysis software tools provide extra options for formatting data, and presenting statistical tests.
Standard Data Tables
Surveygoo provides a basic, but very easy to read format for data tables. The Standard Data Tables downloaded from Surveygoo and opened in Excel looks like this...
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The Table consists of:
• Columns - which show the breaks in the data, such as age or region
• Rows - which show question titles, and answer codes for each question 
Reading Total Data
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The question title is shown in bold blue, and includes a question no. reference. In line 11, in the above example, we see "1" which refers to the question number as stored in the data file, followed by the question number reference and question text, used in the survey.
Directly underneath the question title is the Total, also known as the "base". This is the total number of people who answered the question. The Total is shown in Column E, row 13.
Underneath the Total (rows 14 to 20) are the answer codes for the question. As with the Total, the number of cases who have an answer to each question (answer codes), is shown in Column E. For example, 3 people provided the answer "In House Marketing".
Since this was a single code question (each respondent provided one answer from the question options) the answer codes add to the base number for all the sample, which is 105.
The usual way to report data is to express the answers as a %. In column F, the % score has been calculated for each answer code of each question. So for Q1, the percentage result for the question answer "In House Marketing" was 2.86%.
Reading Column Data (Breaks)
The Standard Data Breaks in many consumer surveys would be age, gender and region. When using Online Panel Access, you can select these demographic options as standard, and they will appear in the data tables automatically. For example, in Column K, row 13 shows 17 people answered the survey from London. We read the answers to question 1 for London survey participants the same way as the Total column.
We can now compare the answers between the Total sample, and just London survey participants. So, we can see that the answer "In House Marketing", whereas 3 out of 105 people, or 2.86% of the total sample gave this answer, among London is was 5.88% (1 out of 17). In this example, it would not be wise to assume that the results are statistically reliable (we would need at least 30 responses for London to start making comparisons with other groups). But this example demonstrates the way column data (or standard breaks) are read in data columns.

What is a Cross Tabulation?

Cross Tabulations, or "Cross Tabs" as they are sometimes called, are a really effective analysis technique which can save time exploring data tables and help identify useful patterns in the data. A cross tabulation is a data table which displays the distribution of the data of two or more variables (or questions). In simple terms, the cross tab allows the user to compare survey data responses, analysed by different questions.

Lets look at an example.
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In this example, we are looking at the results of a question (q8) shown in the image rows, against another which is displayed in the columns.
Download Cross Tab Report
At this point, you may find it easier to download the example pdf report of Q8 cross tab. At the bottom of the page, click on the Download button.
On page 2 of the Cross Tab report, we can see four columns under q3. In each table cell underneath the columns we have the absolute number of survey participants indicating an answer to each question, and two % scores.
To compare the responses for q3, we need to read down the columns. So, for the the attribute "Knowing how to phrase a question objectively", in the first column 27.3% (or 6 out of 22 cases) Strongly Agreed with the statement. If you move two columns to the right to the Column "no", and look at the same rating level of Strongly Agree, we see a percentage of 21.8%, or 12 out of 55 cases. We can now compare the responses of the people who say their organisation has used a survey tool with those who have not.
That's the basics for reading a cross tabulation. Running tables is a relatively easy task; the real difficulty lies in making sense of the data: analysing the data. That takes patience, experience, a sense of context and a reasonably high degree of concentration. In this sense generating data tables should be regarded as the first step (and the easy bit), followed by the longer task of reading and digesting the data.

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