Likert Scale – What is it? When to Use it? How to Analyze it?

Posted 04.24.12 by in: Know How, Most Popular Posts 20 Responses

In all likelihood, you have used a Likert scale (or something you’ve called a Likert scale) in a survey before.

It might surprise you to learn that Likert scales are a very specific format and what you have been calling Likert may not be.

Not to worry — researchers that have been doing surveys for years still get their definitions confused. In fact, many researchers do not even agree on the best way to report on the numeric values in a Likert scale.

This article will explain the traditional and, in our opinion, most valuable way to use Likert scales and report on them.

What is a Likert Scale vs. a Likert Item

A “Likert scale” is actually the sum of responses to several Likert items. These items are usually displayed with a visual aid, such as a series of radio buttons or a horizontal bar representing a simple scale.

In a “good” Likert scale, the scale is balanced on both sides of a neutral option, creating a less biased measurement. The actual scale labels, as well as the numeric scale, may vary.

A “Likert Item” is a statement that the respondent is asked to evaluate. In the example below, this item, “The checkout process was easy” is a Likert item — and the table as a whole is the Likert scale.

Here’s how to remember it: The “scale” in “Likert scale” refers to the total sum of all Likert items in the question — not the 1-5 range you see for each item. In the example below, the scale would be 4 to 20.

Below is an example of a nearly perfect Likert scale. It has one potential flaw which we’ll discuss later.

Please select the number below that best represents how you 
feel about your recent online software purchase for each statement.

                    Strongly                             Strongly 
                     Agree    Agree  Undecided  Disagree Disagree
==================================================================
1. The software I 
wanted was easy        1       2        3         4        5
to find.

2. The checkout        1       2        3         4        5
process  was easy

3. The software        1       2        3         4        5
solved my needs

4. I am happy with     1       2        3         4        5
my purchase
Historic Trivia: The Likert scale question itself was invented by the educator and psychologist Rensis Likert in his thesis at Columbia University. You never know when this might come up in Market Research Trivia night at your local bar.

So given this new information, when should you use a Likert scale?

To answer that, it’s important to look at how you’d report and analyze the data for this question type. So let’s take a look.

Reporting on Likert Scales

The traditional way to report on a Likert scale is to sum the values of each selected option and create a score for each respondent. This score is then used to represent a particular trait (particularly when used for sociological or psychological research).

This is also quite useful for evaluating a respondent’s opinion of important purchasing, product, or satisfaction features. The scores can be used to create a chart of the distribution of opinion across the population. For further analysis, you can cross tabulate the score mean with contributing factors.

Important Tip: For the score to have meaning, each item in the scale should to be closely related to the same topic of measurement.

In the example Likert scale above, the third option is actually slightly out of place, as it doesn’t relate to the purchasing or checkout process — which is the intended topic.

Ideally, in a Likert scale question, all of the items would be categorically similar so the summed score becomes a reliable measurement of the particular behavior or psychological trait you are measuring.

If you have an item on the scale that doesn’t fit, the total score for the respondent becomes potentially polluted and you’ll end up spending a great deal of time deciphering the results!

When to Use Likert Scales

This is a very useful question type when you want to get an overall measurement of a particular topic, opinion, or experience and also collect specific data on contributing factors. Measuring the satisfaction (the trait) of a recent shopping experience is a common use.

You should not use this form of question (or at least you should not call it a Likert scale) when the items in the question are unrelated to each other, or when the options are not in the form of a scale.

As with all other rating and scale questions — we encourage you not to mix scales within your surveys. Choose a particular scale (3 point, 5 point, 7 point, etc) and use it as your standard to cut down on potential confusion and fatigue. This will also allow for comparisons within and between your data sets!

Discussion

Use the Comments & Discussions area below the article to discuss Likert scales! Here are some ideas:

  • Have additional information you want to share?
  • Do you have successful examples of Likert scales you’d like to share?
  • Follow up questions?

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  • Sklonis

    The direction used in the example is different from what I usually use.  I assign the 1 to ‘strongly disagree’ and the 5 to ‘strongly agree’ so that more points means a more positive attitude.

  • sgizmo

    That’s a good point Sklonis.  The direction of the numeric scale depends on how you will be reporting and presenting the information.  Your way is much more common and makes more intuitive sense.

    -CV

    • ashly

      what if i collated the five point scale to three point? what would be the mean then?

  • Laurie Gelb

    There is no reason to show numbers to the respondent at all. They should be unlabeled radio buttons. Use the reporting value for your numbers. Moreover, your scale is flipped.
    Sometimes you want to show 0 as “strongly disagree” and “10″ as “completely agree” with unlabeled points between, so your data have a natural but unseen midpoint and a base 10 foundation. Usually there is no reason to label a midpoint on an intensity scale.
    “Undecided” is not an option. Phrase the question so you can have your “out” (if not a legitimate forced choice) be the same across the grid: “Not sure yet,” “Does not apply” “Did not use” or whatever. In some situations, you will differentiate between don’t know/don’t care/wasn’t aware and so on.
    Sorry, but contrary to your rule, many surveys require a “mix” of categorical and ordinal
    scales. There’s nothing wrong w/ this as long as categorical scales are
    fully and naturalistically labeled (e.g. “about half the time” as
    opposed to “40-60%”) and the question flow is smooth.
    I could also add that these answer items are overlapping and generally imprecise. Not a good example overall. Definitely not “nearly perfect”!

  • Patrick

    Hmm – in your example your mid point is scored a 3 (out of a possible 5) – in other words, 60% .. I feel skewed reports coming on.

    Obviously 50% is a more accurate score for a mid point / neutral / undecided score.

    • William

      You are looking at the scale wrong: If you are looking at each number as a percentage, you need to realize that each number actually is a range:
      1=0-20%
      2=20-40%
      3=40-60%
      4=60-80%
      5=80-100%

      This shows the 3 as a midpoint, not 50%, as if it were 50%, it is less than the middle, and 51% is more than the middle. Essentially, I am saying that you are arguing semantics.

  • Joe-hobbs

    The Likert scale is fantastic and very accurate I think, with respect to what Patrick said, I do not think that is 50% … I am not sure that is as well.
    Regards,
    Joe Hobbs – Recetas Faciles y Rapidas

  • dong

    Instead of Summing up the scores, you can use mean

  • Norm

    There are two large and potentially fatally flawed problems here. The first is that using a Likert type Scale with 5 choices is an ordinal scale only, ie. it has rank but no magnitude. So we know that “Strongly Agree” is lower than “Agree” but we don’t know by HOW MUCH. This is like the gold medal winner is better than the silver medal winner but the scale doesn’t indicate the difference or magnitude between them.
    This then creates a second problem: creating a ratio scale which has rank and magnitude from an ordinal scale with no magnitude. This is to say that respondents believe “Strongly Agree” is different from “Agree” but probably not the same amount of difference as between, say “Agree” and “Undecided”. But we all know that the difference between 3 & 4 is the same as the difference between 2 & 3. Therefore you CANNOT perform mathematical calculations on this for reporting – you can ONLY report the number of responses for each answer ,ie. 3- Strongly Disagree; 1 – Disagree. Given this, you cannot add up these false numbers to give a true sum. If you want to manipulate numbers given them a scale of at least 1-7 or better 1-10. One to ten is a true ratio (scale or interval scale if there is a true zero) and the numbers can be descriptively and inferentially analyzed.

  • kasema

    The Likert scale is fantastic but I still encounter difficulties to interpret scale 3 Undecided in a five scale item. eg. 1 SD= very low, 2 D=Low, 3 Undecided=? (what about this scale?) 4 A=High, 5 SA=Very high

  • Eric

    I entirely agree with you Skions, it makes more sense to award more points to more positive attitude

  • disqus_axxSSa22H6

    After summing up the responses of respondents, how about the statistical limits? Which is correct 1.00-1.49, 1.50-2.49, 2.50-3.49, 3.50-4.49, 4.50-5.00……….or…… 1.00-1.80, 1.81-2.60, 2.61-3.40, 3.41-4.20, 4.21-5.00

  • murianki

    i agree with sklonis 5 should be assigned to strongly agree

  • melanie

    does it matter, using this scale can potentially provoke bias for one were using this scale in voluntary response sample, meaning that the individual (depending on how strongly they feel about the subject) will chose to respond to this survey, additionally because of that we cant just “use” the averages or data given on this sample, it cant possibly represent an entire population only the specific people that feel strongly enough about the subject -_-

    • http://twitter.com/cvanek Christian Vanek

      Melanie,

      That’s true. If it was voluntary and you believe that only people that left polarized about the issue were going to reply then you do have a bias. But that’s more a sample bias than a question bias.

      A very common form of sample bias like this can be found in service satisfaction surveys. People that had an alarmingly bad experience or a fantastically good experience are more likely to apply. That’s why companies have to be careful about drawing conclusions about their customer base from customer service feedback.

  • http://www.facebook.com/indika.priyamali Indika Priyamali

    I used likert scale method to my research

    • http://twitter.com/cvanek Christian Vanek

      Excellent!

  • DocRox

    I don’t like these kind of scales. There is NEVER an answer that fits how I truly feel and there is rarely a space for free response. I know it’s a quick and idrty way to get what you hope is a valid statistic about your product/service/etc. but they are almost always poorly written and don’t reflect the reality of the situation.

    • Christian

      Hi Doc,

      That can be true sometimes. No respondent ever likes feeling railroaded into an answer — and it does make an assumption that your opinion will fit nicely on a linear scale.

      Adding a comment section under the scale (optional of course) is a good thing for researchers to consider. The researcher can use that information to help qualify your opinion more and decide if it matches with the rest of the data set.

      Thanks for your comment!

      -Christian

  • Jaya kumara

    I used Likert scale method for my research, really it is very good to get good responses from the users, and for analysis of data i used mean, Standard Deviation and Chi-square test for evaluation of hypotheses. The out put of research work is good.

About the Author

Christian Vanek
Christian is the CEO and co-founder of SurveyGizmo. Before building SurveyGizmo 1.0, he came from an 13-year consulting background focusing on marketing and content management tools. When not working on new ways to gather data, he spends time developing games and actively supports innovative youth education programs. In spite of living in Boulder, he does not ski. On Twitter @cvanek

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