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An introduction to analyzing survey results

When we receive and collect enough responses for a survey, it is time to analyze the data. Actually, being able to analyze these data in a proper way, is even more important than designing the questionnaire itself.

There are many different ways through which one can extract a proper analysis from the collected survey data. All these ways will lead to achieving a realistic insight about the responses. In this article we are going to have a quick and elementary review of the essential steps and techniques needed to analyze the survey results.

Analyzing collected survey data is a science for itself. So I’ve made this article for you, to help you get a good grasp of this subject. So make sure to click the ‘continue reading’ button, and read the whole article!

Sampling and Data Collection

What is sampling?

When a survey has been generated and tested carefully, it is time to send out the survey in order to collect responses. The distribution procedure and data collecting process, is one of the most important parts of the survey processing which has a big influence on further analysis.

Sometimes, even the entire population will be sufficiently small and researcher can consider an obvious way to perform that by sending out the survey to all the possible individuals and then waiting for their responses. This type of research is called a “census study”. Although this method seems to be easy and good, it is not applicable and efficient most of the time. Especially when the target population is huge or simply not entirely reachable.

In order to apply the distribution procedure it is usually needed to use some statistical tools and methods to select a small, but carefully chosen group of potential respondents from the total target population. In statistics these useful methods of choosing a subgroup from a population is referred as “Sampling”.

The goal of sampling is to decrease the cost, save time and reduce the amount of work that it would take to survey the entire target population. Since all further analysis is based on the gathered data, it is necessary to select the samples carefully.

What is “Rating scale”

A “rating scale” is a set of answers designed with the aim of collecting information about a quantitative or a qualitative attribute. Some common examples of rating scales in social sciences, particularly psychology are the “likert-type scales” in which a person selects an statement among several statement or “1-10 rating scales” in which a person selects the number which is considered to reflect the perceived quality of the asked subject.

Additionally, in interactive environments such as the web, “Rating stars”, “Thumbs up and down” and “Sliders” can be considered as Rating scale types of questions. Such rating scales are used widely online in websites, blogs, websites and online surveys, in an attempt to provide indications of consumer or users opinions of products or services.

When you use the rating scale questions in your surveys, you require the raters (survey participants) to assign a value -which can be even numeric-, to the rated object, or to some attributes of it.

What is “Likert-type scale”

A Likert scale provides a great way of measuring attitudes, knowledge, perceptions, values, and behavioral changes. A Likert-type scale involves a series of statements that survey respondents may choose from, in order to rate their responses to evaluative questions.

When to Use Likert-type Scales

This type of question is very useful when you need an overall measurement of a particular topic, opinion or experience. When you use these questions, simultaneously you can collect data on contributing factors. It is very common to use likert-type scales when researchers want to evaluate the level of satisfaction for a recent shopping or visiting experience.

Tip:
Just like other types of rating questions — it’s recommended not to mix different scales within your surveys. Just pick a specific type of scale (3 point, 5 point, 7 point, etc) and use it as your standard to reduce potential confusion and fatigue. This will also make the comparison of your statistics easier!

Using our mobile-ready Likert Scale table

We have redesigned the Likert questions from scratch. They are not only mobile-friendly, but also allow you to add unlimited numbers of Likert Items. Feel free to try the question type out in your next online surveys. Read more about our Liker Scale table.

Here are some examples that show you how you can ask such questions in your online surveys:

Note:
For the following examples, numbers in the answers indicate the relative position of items, but not the magnitude of difference. You do not have to include them in your survey questions if you desire so.

Examples

Comparing 2 Products

1 – Much worse
2 – Somewhat worse
4 – Somewhat better
5 – Much better

1 – Poor
2 – Fair
3 – Good
4 – Very good
5 – Excellent

Support / Opposition

1 – Strongly oppose
2 – Somewhat oppose
3 – Neutral
4 – Somewhat favour
5 – Strongly favour

Barriers

1 – Not a barrier
2 – Somewhat of a barrier
3 – Moderate barrier
4 – Extreme barrier

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