What is a Likert Scale?<\/h2>\n\n\n\n
A Likert Scale is a unidimensional scale that researchers use to collect respondents’ attitudes and opinions. Researchers often use this psychometric scale to understand the views and perspectives towards a brand, product, or target market.<\/span><\/p>\n\n\n\n There are different variations, and each one<\/span> are focused directly on measuring people’s opinions, such as the <\/span>Guttman scale<\/span><\/a>, <\/span>Bogardus scale<\/span><\/a>, and <\/span>Thurstone scale<\/span><\/a>.<\/span><\/p>\n\n\n\n Psychologist Rensis Likert established a distinction between a scale that materializes from a collection of responses to a group of items (maybe 8 or more). Responses are measured in a range of values.<\/span><\/p>\n\n\n\n Given its importance for budding research professionals, we have created a guide to help you understand the critical aspects of this tool and best practices for mastering it to conduct better research. We hope you find it helpful!<\/p>\n\n\n\n The Likert Scale<\/strong> has become a favorite among researchers to collect opinions about customer satisfaction<\/a> or employee experience<\/a>. You can divide this scale primarily into two major types:<\/span><\/p>\n\n\n\n Researchers use even Likert Scale to collect extreme feedback without providing a neutral option.<\/span><\/p>\n\n\n\n Researchers use the odd Likert Scale to give the respondents the choice of responding neutrally.<\/span><\/p>\n\n\n\n Likert Scale questions are fundamental for surveys and research, allowing respondents to express their attitudes, opinions, or behaviors across various options. Here’s how each type of Likert Scale question works, along with practical examples:<\/p>\n\n\n Agreement-based Likert Scale questions assess the capacity to which respondents agree or disagree with a statement, permitting researchers to capture their attitudes and opinions on particular topics.<\/p>\n\n\n\n Example Question:<\/strong><\/p>\n\n\n\n “The training program met my expectations.”<\/em><\/p>\n\n\n\n Response Scale:<\/strong><\/p>\n\n\n\n This type of question is ideal for gauging satisfaction, perception, or approval of services, policies, or experiences.<\/p>\n\n\n\n Frequency-based questions assess how often a respondent performs or experiences a particular action or behavior. This type of question helps identify patterns in usage or behavior over time.<\/p>\n\n\n\n Example Question:<\/strong><\/p>\n\n\n\n “How often do you use our mobile app?”<\/em><\/p>\n\n\n\n Response Scale:<\/strong><\/p>\n\n\n\n Use this question type to monitor frequency patterns and habits among respondents, especially for product or service usage.<\/p>\n\n\n\n Importance-based Likert questions evaluate the significance or priority respondents place on certain elements, features, or aspects. They help researchers understand what matters most to their audience.<\/p>\n\n\n\n Example Question:<\/strong><\/p>\n\n\n\n “How important is access to 24\/7 customer support?”<\/em><\/p>\n\n\n\n Response Scale:<\/strong><\/p>\n\n\n\n Such questions are essential for prioritizing features, services, or policies according to user needs and preferences.<\/p>\n\n\n\n Interest-based questions measure respondents’ enthusiasm or engagement toward a topic or activity. They’re useful for identifying preferences and gauging how likely respondents are to pursue or engage in future offerings.<\/p>\n\n\n\n Example Question:<\/strong><\/p>\n\n\n\n “How interested are you in attending future workshops?”<\/em><\/p>\n\n\n\n Response Scale:<\/strong><\/p>\n\n\n\n This type of question is valuable for gauging potential interest in new programs, events, or products.<\/p>\n\n\n\n By crafting questions that suit each purpose, researchers can gain insightful, actionable data on attitudes, behaviors, and priorities, guiding better decision-making and improved experiences.<\/p>\n\n\n\n The Likert Scale came into existence in 1932 in the form of the 5-point scale, which is used extensively. These scales range from a group of general topics to the most specific ones that ask respondents to indicate their level of agreement, approval or, belief. Some significant characteristics of the Likert Scale, are:<\/span><\/p>\n\n\n\n Items should be easily related to the sentence’s answers, regardless of whether the relationship between item and sentence is evident.<\/span><\/p>\n\n\n\n The items must always have two extreme positions and an intermediate answer option that serves as graduation between the extremes.<\/span><\/p>\n\n\n\n It is essential to mention that although the most common Likert Scale is that of 5 items, the use of more items helps to generate greater precision in the results.<\/span><\/p>\n\n\n\n Researchers often increase the ends of the scale to create a seven-point scale by adding \u201cvery\u201d to the top and bottom of the five-point scales. The seven-point scale reaches the upper limits of the reliability of the scale.<\/span><\/p>\n\n\n\n As a general rule, Likert and others recommend that it be better to use a scale as wide as possible. One can always collapse the answers into concise groups, if appropriate, for analysis.<\/span><\/p>\n\n\n\n By considering these details, scales are sometimes curtailed to an even number of categories (usually four) to eliminate the \u201cneutral\u201d possibility on a \u201cforced choice\u201d survey scale.<\/span><\/p>\n\n\n\n The primary Likert record clearly states that there could be an inherent variable whose value marks the feedback or attitudes of the respondents, and this underlying variable is the interval level, at best.<\/span><\/p>\n\n\n\n To better understand this concept, we have created this example where we suppose that a researcher uses a Likert Scale question as a dichotomous option question to collect product feedback. He\/ she frames the question as \u201cThe product was a good purchase,\u201d with the options listed as agree or disagree. The other way to frame this Likert Scale questionnaire is, \u201cPlease state your satisfaction level with the products,\u201d and the options range from very dissatisfied to very satisfied.<\/span><\/p>\n\n\n\n When responding to an item on the likert Scale, the user responds based explicitly on their agreement or disagreement level. These scales allow for determining the level of agreement or disagreement of the respondents.<\/span><\/p>\n\n\n\n The Likert Scale assumes that the strength and intensity of the experience are linear<\/strong>. Therefore it goes from a complete agreement to a complete disagreement, assuming that attitudes can be measured.<\/span><\/p>\n\n\n\n Do you need more examples?<\/strong> Check out these Likert Scale examples<\/a>.<\/p>\n\n\n\n Researchers use surveys regularly to measure and analyze the quality of products or services. The Likert Scale is a standard classification format for studies. The respondents provide their opinion (data) about the quality of a product\/service from high to low or better to worse using two, four, five, or seven levels.<\/span><\/p>\n\n\n\n Researchers and auditors generally group collected data into a hierarchy of four fundamental measurement levels \u2013 nominal, ordinal, interval, and ratio measurement levels for further analysis<\/span>:<\/span><\/p>\n\n\n\n Data analysis using nominal, interval, and ratio data are generally transparent and straightforward. Ordinal data analyzes data, particularly in regards to Likert or other scales in the surveys. This is not a new research problem<\/a>. The effectiveness of handling ordinal data as interval data continues to be debatable in survey analysis of various applied fields. Some of the significant scale points to keep in mind are:<\/p>\n\n\n\n Researchers sometimes treat ordinal data as interval data because they claim that parametric statistical tests are more powerful than nonparametric alternatives. Moreover, inferences from parametric tests are easy to interpret and provide more information than non-parametric options.<\/span><\/p>\n\n\n\n However, the treatment of ordinal data as interval data without examining the values \u200b\u200bof the data set and the analysis’s objectives can mislead and misrepresent the results of a survey. To analyze scalar data more appropriately, researchers prefer to consider ordinal data as interval data and concentrate on Likert Scale<\/span>s.<\/span><\/p>\n\n\n\n A universal guideline suggests that the mean and the standard deviation are baseless parameters for detailed statistics when the data are on ordinal scales<\/a>, just like any parametric analysis based on normal distribution. The non-parametric test is done based on the appropriate median or range for inspecting data.<\/span><\/p>\n\n\n\n Because the Likert element data is discrete, ordinal, and limited in scope, there has been a long dispute over the most logical way to analyze Likert data. The first option is between parametric and non-parametric tests. The advantages and disadvantages of each type of analysis are generally described as the following:<\/span><\/p>\n\n\n\n Which is the best option? When deciding to analyze information received from a survey that uses Likert Scale questions, a researcher has to make a real decision.<\/span><\/p>\n\n\n\n There are many advantages of using this rating Scale in a survey for market research<\/a>. They are:<\/span><\/p>\n\n\n\n The Likert Scale is typically used to measure attitudes and opinions, but they have several disadvantages:<\/p>\n\n\n\n The Likert-scale survey<\/a> is a comprehensive technique for gauging feedback and information, making it significantly easy to understand and respond. This is a critical question to measure the opinion or attitude towards a specific topic.<\/span> So that it will be of great help in the next step of an investigation.<\/span><\/p>\n\n\n\n With QuestionPro, an organization can conduct an online survey using the Likert Scale<\/span>s. Start by <\/span>creating a free account<\/span><\/a> and start testing this type of question.<\/span><\/p>\n\n\n\n For more information or questions, please consult our online chat and tell us about your project. We’ll recommend the best research tool to suit your needs.<\/p>\n\n\n\n The Likert Scale helps measure attitudes, opinions, and perceptions in many areas, from research to business. Its simple design makes it a popular choice for collecting data, while its structure allows for precise and accurate analysis.<\/p>\n\n\n\n When used well, the Likert Scale improves data collection and helps make decisions by understanding group opinions better. When used effectively, the Likert Scale enhances data collection and facilitates informed decision-making based on a better understanding of collective sentiment.<\/p>\n\n\n\nTypes of Likert Scales<\/h2>\n\n\n\n
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1. Even Likert Scale<\/h4>\n\n\n\n
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![\"\"\/](\"https:\/\/www.questionpro.com\/blog\/wp-content\/uploads\/2024\/11\/4-Point-Likert-Scale.jpg\")
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![\"\"\/](\"https:\/\/www.questionpro.com\/blog\/wp-content\/uploads\/2024\/11\/8-Point-Likelihood.jpg\")
<\/figure>\n\n\n\n2. Odd Likert Scale<\/h4>\n\n\n\n
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![\"\"\/](\"https:\/\/www.questionpro.com\/blog\/wp-content\/uploads\/2024\/11\/5-point-Likert-scale.jpg\")
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![\"\"\/](\"https:\/\/www.questionpro.com\/blog\/wp-content\/uploads\/2024\/11\/7-point-Likert-scale.jpg\")
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![\"\"\/](\"https:\/\/www.questionpro.com\/blog\/wp-content\/uploads\/2024\/11\/9-point-Likert-scale.jpg\")
<\/figure>\n\n\n\nLikert scale questions<\/h2>\n\n\n\n
![\"Likert](\"https:\/\/www.questionpro.com\/blog\/wp-content\/uploads\/2018\/05\/Likert-Scale-Examples.jpg\")
<\/figure><\/div>\n\n\n1. Agreement<\/h3>\n\n\n\n
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2. Frequency<\/h3>\n\n\n\n
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3. Importance<\/h3>\n\n\n\n
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4. Interest<\/h3>\n\n\n\n
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Characteristics of Likert Scale<\/h2>\n\n\n\n
01. Related answers<\/h3>\n\n\n\n
02. Scale type<\/h3>\n\n\n\n
03. Number of answer options<\/h3>\n\n\n\n
04. Increasing reliability of the scale<\/h3>\n\n\n\n
05. Using wide scales<\/h3>\n\n\n\n
06. Lack of a neutral option<\/h3>\n\n\n\n
07. Intrinsic variable<\/h3>\n\n\n\n
Example of a Likert Scale<\/h2>\n\n\n\n
![\"Likert](\"https:\/\/www.questionpro.com\/blog\/wp-content\/uploads\/2018\/05\/Liker-Scale-Example_2.jpg\")
<\/h3>\n\n\n\nLikert Scale Data and Analysis<\/h2>\n\n\n\n
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1. Statistical tests<\/h4>\n\n\n\n
2. Concentration on Likert Scales<\/h4>\n\n\n\n
3. Median or range for inspecting data<\/h4>\n\n\n\n
Best Practices for Analyzing the Results<\/h2>\n\n\n\n
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Advantages of Likert scale<\/h2>\n\n\n\n
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Disadvantages of Likert Scale<\/h2>\n\n\n\n
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Want to Use the Likert Scale in a Survey? Do it with QuestionPro!<\/h2>\n\n\n\n
![\"\"\/](\"https:\/\/www.questionpro.com\/blog\/wp-content\/uploads\/2024\/07\/QuestionPro-Survey-2.jpg\")
<\/figure>\n\n\n\nConclusion<\/h2>\n\n\n\n