Measuring Attitudes and Opinions

Likert Scale Survey Questions and Examples – Measuring Attitudes and Opinions

A Likert scale is a commonly used method for measuring people’s attitudes and opinions toward a particular subject or statement. It consists of a series of questions or statements that respondents must rate on a scale of agreement or disagreement.

The scale usually ranges from 1 to 5 or 1 to 7, with 1 representing “strongly disagree” and 5 or 7 representing “strongly agree.”

Here are some examples of Likert scale survey questions:

  1. On a scale of 1 to 5, how strongly do you agree with the following statement: “I feel satisfied with my job.”
  2. Please rate your level of agreement with the following statement: “I believe that technology is making our lives better.”
  3. How much do you agree with the following statement: “I prefer to work alone rather than in a team.”
  4. To what extent do you agree with the following statement: “I believe that climate change is a serious threat.”
  5. How strongly do you agree with the following statement: “I enjoy spending time with my family and friends.”
  6. Please rate your level of agreement with the following statement: “I feel confident in my ability to handle difficult situations.”
  7. To what extent do you agree with the following statement: “I feel financially secure.”
  8. How much do you agree with the following statement: “I believe that the government should do more to address social inequality.”
  9. On a scale of 1 to 7, how strongly do you agree with the following statement: “I enjoy trying new things.”
  10. Please rate your level of agreement with the following statement: “I feel comfortable expressing my opinions in a group setting.”

5 Point and Even Likert Scale Questions

A 5-point Likert scale question would typically have the following response options:

  1. Strongly disagree
  2. Disagree
  3. Neither agree nor disagree
  4. Agree
  5. Strongly agree

Examples of 5-point Likert scale questions are:

  1. To what extent do you agree with the statement, “I enjoy spending time outdoors?”
  2. How satisfied are you with the service you received at our restaurant today?
  3. How likely are you to recommend our product to a friend or colleague?

An even Likert scale question is one with an even number of response options. The midpoint or neutral option is sometimes removed to force respondents to choose a side.

Examples of even Likert scale questions are:

  1. On a scale of 1 to 6, how likely are you to purchase our product in the next month? (Here, the neutral option is removed to force respondents to choose between 1-3 or 4-6).
  2. To what extent do you agree with the statement, “I am comfortable using technology to complete tasks?” (Here, a 4-point scale may be used, with the neutral option removed to force respondents to choose between agree and disagree).

Response Options

Agreement

  • Strongly Agree
  • Agree
  • Undecided
  • Disagree
  • Strongly Disagree
  • Agree Strongly
  • Agree Moderately
  • Agree Slightly
  • Disagree Slightly
  • Disagree Moderately
  • Disagree Strongly
  • Agree
  • Disagree or
  • Agree
  • Undecided
  • Disagree
  • Agree Very Strongly
  • Agree Strongly
  • Agree
  • Disagree
  • Disagree Strongly
  • Disagree Very Strongly
  • Completely Agree
  • Mostly Agree
  • Slightly Agree
  • Slightly Disagree
  • Mostly Disagree
  • Completely Disagree
  • Disagree Strongly
  • Disagree
  • Slightly Disagree
  • Slightly Agree
  • Agree
  • Agree Strongly

Value

High
Moderate
Low
None

Relevance

Excellent
Somewhat
Poor

Frequency

likert scale frequency

  • Very Frequently
  • Frequently
  • Occasionally
  • Rarely
  • Very Rarely
  • Never
  • Always
  • Very Frequently
  • Occasionally
  • Rarely
  • Very Rarely
  • Never
  • Always
  • Usually
  • About Half the Time
  • Seldom
  • Never
  • Always
  • Very Often
  • Sometimes
  • Rarely
  • Never
  • A Great Deal
  • Much
  • Often
  • Sometimes
  • Almost Always
  • To a Considerable Degree
  • Somewhat
  • Little
  • Never
  • Seldom
  • Never
  • Occasionally
  • Seldom

Importance

  • Very Important
  • Important
  • Moderately Important
  • Slightly Important
  • Not Important
  • Very Important
  • Moderately Important
  • Not Important
0 = Not Important At All

1 = Of Little Importance

2 = Of Average Importance

3 = Very Important

4 = Absolutely Essential

Quality

likert scale quality

  • Very Good
  • Good
  • Acceptable
  • Poor
  • Very Poor
  • Very Poor
  • Below Average
  • Average
  • Above Average
  • Excellent
  • Good
  • Fair
  • Poor

Likelihood

  • Like Me
  • Not Like Me
  • To a Great Extent
  • Somewhat
  • Very Little
  • Not at All
  • True
  • False
  • Definitely
  • Very Probably
  • Probably
  • Possibly
  • Probably Not
  • Definitely Not
  • Almost Always True
  • Usually True
  • Often True
  • Occasionally True
  • Rarely True
  • Usually Not True
  • Almost Never True
  • Not likely
  • Somewhat likely
  • Very likely

Dichotomous Scales:

  • Fair
  • Unfair
  • Agree
  • Disagree
  • True
  • False
  • Yes
  • No

Three-Point Scales:

  • More than I would like
  • About right
  • Less than I would like
  • Too Harsh
  • About right
  • Too Lenient
  • Too Strict
  • About right Too Lenient
  • Too heavy About Right
  • Too light
  • Too much
  • About right
  • Too little
  • Extremely
  • Moderately
  • Not at all

Four-Point Scales:

  • Most of the time
  • Some of the time Seldom
  • Never
  • Strongly Agree
  • Agree
  • Disagree
  • Strongly Disagree
  • Definitely won’t
  • Probably won’t
  • Probably will
  • Definitely will

Five-Point Scales:

  • Much better
  • Somewhat better
  • Stayed the same
  • Somewhat worse
  • Much worse
  • Strongly Agree
  • Agree
  • Undecided Disagree
  • Strongly Disagree
  • Very High
  • Above Average
  • Average
  • Below Average
  • Very Low
  • Excellent
  • Above Average
  • Average
  • Below Average
  • Very Poor
  • Very good
  • Good
  • Fair Poor
  • Very poor
  • Much higher
  • Higher
  • About the same
  • Lower
  • Much lower
  • Almost always
  • Often
  • Sometimes
  • Seldom
  • Never
  • Extremely
  • Very Moderately
  • Slightly
  • Not at all
  • Very satisfied
  • Satisfied
  • Neither
  • Dissatisfied
  • Very dissatisfied
  • Very important
  • Important
  • Fairly important
  • Slightly important
  • Not important

Seven-Point Scales:

Seven-Point Scales

  • very dissatisfied
  • moderately dissatisfied
  • slightly dissatisfied
  • neutral
  • slightly satisfied
  • moderately satisfied
  • very satisfied
  • far below
  • moderately below
  • slightly below
  • met expectations
  • slightly above
  • moderately
    above
  • far above
  • very poor
  • poor fair
  • good
  • very good
  • excellent
  • exceptional

What is a 5-point rating scale example?

A 5 point rating scale is a common way to measure opinions, attitudes or experiences. This type of scale typically ranges from 1 to 5, with 1 indicating the lowest level of agreement or satisfaction, and 5 indicating the highest.

Here are some examples of a 5 point rating scale:

  1. Very Poor – Poor – Fair – Good – Very Good
  2. Strongly Disagree – Disagree – Neutral – Agree – Strongly Agree
  3. Never – Rarely – Sometimes – Often – Always
  4. Not at all likely – Slightly likely – Moderately likely – Very likely – Extremely likely
  5. Not satisfied at all – Slightly satisfied – Moderately satisfied – Very satisfied – Extremely satisfied
  6. Strongly Negative – Somewhat Negative – Neutral – Somewhat Positive – Strongly Positive
  7. Very Difficult – Difficult – Neutral – Easy – Very Easy
  8. Highly Ineffective – Ineffective – Somewhat Effective – Effective – Highly Effective
  9. Not important at all – Slightly important – Moderately important – Very important – Extremely important
  10. Strongly Discouraged – Discouraged – Neutral – Encouraged – Strongly Encouraged.

Examples

How satisfied were you with your in-store experience today?

  • So delighted
  • I’m Satisfied
  • Not satisfied at all / totally frustrated

[My Brand / organization] invests time and money to keep employees updated with technology.

  • Strongly agree
  • Agree
  • Disagree
  • Strongly disagree

What was your level of satisfaction with our product(s) ?

  • Very satisfied
  • Satisfied
  • Slightly dissatisfied
  • Not satisfied at all / Frustrated

What is the best scale for a survey?

The best scale for a survey depends on the type of questions being asked and the purpose of the survey. Some common types of scales used in surveys include:

Likert Scale:

This is the most commonly used scale in surveys. It consists of a series of statements or questions and respondents indicate their level of agreement or disagreement with each statement using a scale (e.g. 1 to 5, 1 to 7).

Semantic Differential Scale:

This scale uses bipolar adjectives at the two ends of the scale to measure the respondent’s attitudes or opinions. For example, the scale may range from “cold” to “hot,” “friendly” to “unfriendly,” or “expensive” to “inexpensive.”

Multiple-Choice Scale:

This scale provides respondents with a fixed set of responses to choose from. For example, a question may ask “Which of the following best describes your age range?” with responses such as “18-24,” “25-34,” “35-44,” etc.

Numerical Scale:

This scale uses numerical values to measure respondents’ attitudes or opinions. For example, a respondent may be asked to rate their level of satisfaction on a scale of 1 to 10.

Ultimately, the best scale for a survey depends on the research question, the purpose of the survey, and the characteristics of the population being surveyed. It is important to carefully consider the type of scale to use and the phrasing of questions to ensure that respondents fully understand the questions and can provide accurate responses.

What statistical tool is best for the Likert scale?

When analyzing data from a Likert scale, one of the most commonly used statistical tools is mean. The mean provides an average score of the responses to a Likert scale item, and it can help to identify the overall attitude or opinion of the respondents.

Another commonly used statistical tool is the standard deviation. The standard deviation measures the spread of the data around the mean and can provide information about the variability of the responses to a particular item. A high standard deviation indicates that the responses are widely spread out, while a low standard deviation indicates that the responses are clustered around the mean.

Other statistical tools that can be useful for analyzing Likert scale data include:

  1. Frequency distribution: This tool can be used to identify the number of respondents who chose each response option, and can help to identify the most common response.
  2. Mode: The mode is the most frequently occurring response to a Likert scale item, and can help to identify the most common response.
  3. Chi-squared test: This chi-squared test can be used to determine whether there is a significant difference between the responses of different groups (e.g. males and females).
  4. Factor analysis: This technique can be used to identify underlying factors or dimensions in a set of Likert scale items, and can help to identify patterns in the data.

Ultimately, the choice of statistical tool will depend on the specific research question and the nature of the data being analyzed.

How do you use the Likert scale in quantitative research?

This scale is e a commonly used tool in quantitative research to measure attitudes, opinions, and perceptions. Here are some steps to use a Likert scale in quantitative research:

  1. Develop Likert scale items: The first step in using a Likert scale in quantitative research is to develop a set of Likert scale items that are relevant to the research question or hypothesis. These items should be designed to measure the construct or variable of interest and should be clear and unambiguous.
  2. Define the scale range: The range should be defined, typically ranging from 1 to 5, 1 to 7, or 0 to 10, depending on the number of response options and the precision required for the study.
  3. Administer the survey: The survey should be administered to the target population, and the Likert scale items should be presented in a clear and understandable way. It’s important to make sure the respondents understand the instructions and the response options.
  4. Collect and code the data: After the survey has been completed, the responses should be collected and coded according to the Likert scale. Each response should be assigned a numerical value corresponding to the response option (e.g. 1 for “Strongly Disagree,” 5 for “Strongly Agree”).
  5. Analyze the data: The data can be analyzed using a variety of statistical tools, such as the mean, standard deviation, and frequency distribution. These analyses can provide information about the central tendency, variability, and distribution of the responses to the Likert scale items.
  6. Interpret the results: The results of the Likert scale analysis should be interpreted in the context of the research question or hypothesis. The interpretation should take into account the statistical significance of the findings and any limitations of the study.

Overall, the use of Likert scales in quantitative research can provide valuable insights into attitudes, opinions, and perceptions, and can be an effective tool for measuring complex constructs.

Is my scale ordinal or interval?

Likert scale is an ordinal scale

The answer to this question depends on how you use the Likert scale and the specific context of your research.

Technically, a Likert scale is an ordinal scale, which means that the response options have a natural order but the distance between the options is not necessarily equal. In a Likert scale, the response options are usually anchored by descriptive phrases (such as “strongly disagree,” “disagree,” “neutral,” “agree,” and “strongly agree”), which suggest an order of preference, but the distance between each response option is not necessarily equal. For example, the distance between “strongly disagree” and “disagree” is not necessarily the same as the distance between “agree” and “strongly agree.”

However, in some cases, researchers treat Likert scales as interval scales, which assume that the distance between the response options is equal. This is sometimes done by assigning numerical values to the response options and treating those values as if they represent equal intervals. For example, if a Likert scale is coded from 1 to 5, with 1 representing “strongly disagree” and 5 representing “strongly agree,” some researchers might assume that the distance between each response option is equal and use statistical tests that are appropriate for interval scales.

It’s important to note that treating a Likert scale as an interval scale is controversial and may not be appropriate in all situations. The decision of whether to treat a Likert scale as an ordinal or interval scale should be based on the specific research question and context, as well as the assumptions of the statistical tests being used.

In what situations would you use a Likert Scale questionnaire?

A Likert scale questionnaire can be used in many different situations, as it is a versatile tool for measuring attitudes, opinions, perceptions, and other subjective factors. Here are some situations where a Likert scale questionnaire might be used:

  1. Market research: A Likert scale questionnaire can be used to measure consumer preferences and perceptions of products or services, as well as the effectiveness of marketing campaigns.
  2. Customer satisfaction surveys: A Likert scale questionnaire can be used to measure customer satisfaction with a product or service, by asking respondents to rate their satisfaction on a range of factors.
  3. Employee surveys: A Likert scale questionnaire can be used to measure employee satisfaction with various aspects of their job, such as compensation, benefits, work environment, and management.
  4. Health and medical research: A Likert scale questionnaire can be used to measure patient satisfaction with healthcare services, as well as to assess attitudes and beliefs about health-related behaviors and treatments.
  5. Educational research: A Likert scale questionnaire can be used to measure student attitudes and perceptions of educational programs, teaching methods, and classroom environment.
  6. Social and psychological research: A Likert scale questionnaire can be used to measure attitudes and beliefs about social and psychological constructs, such as personality traits, self-esteem, social support, and mental health.

Overall, a Likert scale questionnaire can be useful in any situation where there is a need to measure subjective factors that cannot be easily quantified using objective measures. It is a flexible and widely used tool in survey research that can provide valuable insights into a variety of domains.

How to Analyse Results?

Analyzing Likert scale surveys typically involves summarizing and interpreting the data obtained from respondents. Here are some steps you can follow to analyze Likert scale surveys:

  1. Calculate descriptive statistics: Compute the mean, median, and mode for each Likert scale question to understand the central tendency of the data. You can also calculate the standard deviation and range to assess the variability in responses.
  2. Look at response distributions: Create a frequency distribution table or histogram to visualize the distribution of responses for each Likert scale question. This will help you identify the most common response and outliers, as well as the shape of the distribution.
  3. Identify patterns: Look for patterns or trends in the responses across different groups of respondents. For example, you may want to compare the responses of males versus females or people of different age groups.
  4. Perform statistical tests: If you want to test for differences in responses between groups, you can perform statistical tests such as a t-test or ANOVA. These tests will help you determine whether any observed differences are statistically significant.
  5. Consider open-ended responses: In addition to the Likert scale questions, you may have included open-ended questions in your survey. Take the time to read and categorize these responses to gain additional insights into the attitudes and opinions of your respondents.
  6. Interpret the results: Finally, use your analysis to draw meaningful conclusions about the attitudes, opinions, and perceptions of your respondents. Be sure to consider the limitations of your survey and any potential biases that may have influenced the responses.
What is the difference between Likert Scale survey questions and other question types?
 Likert scale survey questions

The Likert scale survey questions differ from other question types in several ways. Here are some key differences:

  1. Likert scale questions provide a range of response options: Unlike yes/no questions, open-ended questions, or multiple-choice questions, Likert scale questions offer a range of response options that capture the full range of attitudes or opinions. Respondents are typically asked to rate their agreement or disagreement with a statement on a scale, which can range from 3 to 10 options.
  2. Likert scale questions provide more nuanced responses: Likert scale questions offer more nuanced responses than other question types. By providing a range of response options, Likert scales enable respondents to express a wider range of opinions, from strongly disagree to strongly agree, which can provide a more accurate and nuanced representation of their attitudes.
  3. Likert scale questions capture ordinal data: The response options in a Likert scale survey are typically coded with numbers, which can be used to analyze the data as ordinal data. Ordinal data is data that can be ranked in order, but the differences between each level are not necessarily equal.
  4. Likert scale questions can be used to measure a range of constructs: Likert scales are widely used to measure attitudes, opinions, perceptions, and other subjective constructs that cannot be easily measured using objective measures. They can be used to measure a wide range of constructs in various domains, including psychology, healthcare, education, and social sciences.
  5. Likert scale questions are subject to certain limitations: Likert scale questions are not without limitations. For example, they can be influenced by social desirability bias, where respondents may give answers that they believe are socially acceptable. Additionally, the ordinal data captured by Likert scales is not as precise as interval data and may not be appropriate for certain statistical analyses.

In summary, Likert scale questions are a unique type of survey question that can provide a more nuanced understanding of attitudes and opinions than other question types. They are widely used in research and can measure a range of subjective constructs, but they are subject to certain limitations.

5 Extra Tips on How to Use It

Tips on How to Use Likert Scale

  1. Be clear and concise: It is important to be clear and concise when writing Likert scale questions. Use simple, straightforward language and avoid using jargon or technical terms. Also, keep the statements short and to the point, as longer statements can confuse respondents.
  2. Balance the scales: It is important to balance the scales when creating Likert scale questions. Use an equal number of positive and negative statements to avoid response bias. This will ensure that the scale is unbiased and that the results are more accurate.
  3. Use a clear scale range: Use a clear and consistent range for your Likert scale questions. This range should be clearly defined and easy to understand for respondents. It is also a good practice to use an odd number of response options to enable respondents to express a neutral opinion.
  4. Test the questions: It is important to test your Likert scale questions before using them in a survey. Testing the questions will help you identify any issues with the questions, such as ambiguities or confusing language. This will ensure that the survey results are accurate and reliable.
  5. Analyze the data carefully: Analyzing Likert scale data requires careful attention to detail. It is important to understand the strengths and limitations of using ordinal data and to use appropriate statistical tests to analyze the data. It is also important to consider the context of the questions and to avoid making assumptions based solely on the responses to the Likert scale questions.

In summary, using the Likert scale requires careful attention to detail and clear communication. By balancing the scales, using a clear range, testing the questions, and analyzing the data carefully, you can ensure that your survey results are accurate and reliable.

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