How to Analyze Likert Scale Data?

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In this blog, you will learn how to analyze Likert Scale Data. There is a hard way to get it done. And then there is a simple way.

Table of Contents

• What is a Likert Scale data?
• How to Analyze Likert Scale Data?
• Which Test is Better for Analyzing Likert Scale Data
• How to Interpret Likert Scale Data?
• Tips to Analyse Data from the Likert Scale
• Likert Scale Data Analysis Use Cases
• FAQs
• Wrap Up

Video Tutorial: How to Analyze Likert Scale Data?

Analyzing data obtained from surveys using the Likert Scale is very important so we will tell you the best way to create, interpret, and present Likert Scale data in the following video and the rest of the blog.

If you want to learn more about customizing this chart and setting properties, header, footer, and labels you can read our guide on How to Present Likert Scale Data.

What is a Likert Scale data?

Definition: A Likert scale is usually a bipolar scale. Which means that it consists of two opposing poles. It measures the intensity of feelings, opinions, and attitudes towards a subject matter.

It mostly asks how much a respondent agrees or disagrees with a particular statement. So, the Likert scale questionnaire collects the information from the respondents. The Likert Scale is mostly used by researchers, psychologists, sociologists, analysts, and marketers.

The scale assumes that the strength and intensity of the feelings are linear. That is it goes from a complete disagreement to a complete agreement. It is a one-way scale.

The questions in the Likert scale range from general to even more specific topics.

That is a long way to go.

However, there is something you need to realize.

As effective as the Likert Scale Survey may be, it could be made ineffective.

Since you are sampling human opinions, there are delicate things to be done to get perfect data.

Humans can change, have mood swings, and be deceptive, and untrue to their opinions.

Most of us sometimes don’t even know our thoughts.

This could cause a lot of irregularities in the data collected.

It is almost like another roadblock.

Here’s how to clear it up.

Performing Likert Scale Analysis

• Data Input: Input the collected responses, organizing them into rows and columns.
• Assign Values: Assign numerical values to the Likert scale responses for consistency.
• Descriptive Analysis: Use functions (e.g., AVERAGE, MEDIAN, STDEV) to calculate descriptive research analysis.
• Visual Representation: Create graphs or charts to visualize the distribution of responses.
• Comparative Analysis: Segment data based on demographics or variables for comparative insights.
• Correlation and Regression: Use tools to explore relationships among variables.

How is the Likert Scale used in Data Analysis?

Surveys are generally used by businesses and researchers to measure and analyze product quality.

It can also be used to measure the quality of services.

The respondents are asked to provide their opinions from better to worse using different levels of measurement.

The measurement maybe two, three, four, five, or seven-point.

According to researchers and auditors, collected data is usually grouped into levels.

There is a hierarchy of four fundamental measurement levels into which data can be grouped.

The levels include Nominal, Ordinal, Interval, and Ratio measurement levels.

By understanding and classifying your data into these levels, you will better understand how to use them.

• Nominal data

Nominal data cannot be quantified or ordered. Each element of a nominal data set stands alone.

We cannot identify which is greater in number than the other. We cannot also identify which comes before the other. That is simply what nominal data is.

• Ordinal data

In ordinal data, the data can be sorted and classified. The data can also be ordered.

That means that you can recognize which comes before the other. And which is less than the other.

However, you cannot measure the distance between the variables. It is not possible to know how much A is greater than B. Likert scale data is usually classified as ordinal data.

• Interval data

In interval data, it is possible to know how much A is greater than B. You can also order them accordingly.

• Ratio Data

The ratio data is very similar to interval data. However, the intervals in ratio data are equal and definitive.

That is, the difference between ‘A and B’ is equal to the difference between ‘B and C’.

Also in ratio data, there is an absolute zero as the point of origin and the reference point.

Next up is how then to analyze ordinal data like the Likert Scale.

How to Analyze Likert Scale Data?

Analyzing Likert scale data involves several key steps to derive meaningful insights. Begin by entering the responses into a spreadsheet, assigning numerical values to each Likert scale option for easier computation.

Next, calculate descriptive statistics such as mean, median, and mode to understand the central tendency of responses.

Visualize the data using bar charts or histograms to grasp the distribution and frequency of various responses. Conducting inferential statistical tests, like t-tests or ANOVA, can help determine significant differences between groups if applicable.

Utilize functions and pivot tables to streamline analysis and generate comprehensive reports, enabling a deeper understanding of the data’s nuances and implications.

Let us see the steps on how to create and analyze Likert scale data with ChartExpo.

First, open your Excel application and worksheet.

Then, click on the ‘Insert’ menu, click on My Apps, and click on ‘See all’.

If you have the plug-in installed, then you will see your ChartExpo on the add-in page.

Click on the add-in and click ‘insert’ at the bottom of the page.

The add-in will be added to your interface.

You can log in with an existing Microsoft account or create a new one.

You can do this by clicking the ‘create new’ button.

You would only be required to log in once.

Upon subsequent usage, you will not be asked to log in.

If you do not have the ChartExpo plugin installed, download it and follow the same steps to get started.

To create a Likert chart on ChartExpo, click the ‘Likert Scale chart’.

You will see a chart displayed on the screen.

You can explore the sample data of the chart by clicking on the ‘Add Sample Chart + Data’.

Let us see an example of how Curtis visualized his Likert scale data.

Curtis runs a software company.

Curtis wanted to get a satisfaction report from his customers.

He, therefore, created a survey and drew up questions for his customers.

These are some of his questions.

1. The software I wanted was easy to find.
2. The checkout process was easy.
3. The software solved my needs.
4. I am happy with my purchase.

After administering the questionnaire, he collated his results and arranged them into his spreadsheet.

He then selected ‘Create Chart from sheet data’ on his opened ChartExpo ™ plugin.

This was his chart.

From this chart, Curtis was able to know where his product stood with his customers.

Most of the customers recorded that they were happy with their purchase.

The insights produced by this chart will therefore help Curtis to hone his strengths and work on his weaknesses.

Core Elements to Analyze Likert Scale Data

Analyzing Likert scale data is a critical process for extracting meaningful insights from surveys or questionnaires. Understanding the core elements involved in this analysis empowers businesses and researchers to make informed decisions based on the gathered data.

Utilizing as a tool for this analysis provides a structured and manageable approach, allowing for precise assessment and interpretation of the collected responses.

Which Test is Better for Analyzing Likert Scale Data

While analyzing Likert scale data, the decision to test relies upon the idea of the data and the research question. For parametric analysis, the t-test or ANOVA is appropriate if the information meets the presumptions of ordinariness and equivalent changes.

Non-parametric tests like the Mann-Whitney U test or the Kruskal-Wallis test are better for ordinal data or when assumptions are not met. For looking at connections, Spearman’s position relationship can be helpful.

Choosing the right test ensures an accurate and meaningful interpretation of the data.

How to Interpret Likert Scale Data?

The analysis of nominal, interval, and ratio data is generally straightforward and transparent.

We have said before that ordinal data analyze data such as the Likert Scale data.

There is still a huge debate amongst analysts and researchers about handling Likert Scale data as interval data.

These are some things to know and keep in mind when trying to analyze Likert scale data.

• Define the Focus

Before you begin data analysis, you need to identify what your aim is.

You need to know what the purpose of your survey is.

This will also guide the survey questions and make them one-dimensional.

That is, it will be principally focused on one topic.

• Generate the Likert Scale items

The Likert Scale items should agree with the Likert Scale questions. That is you should pick a scale that corresponds with your questions.

When the scale does not correspond with the questions, the audience may get confused and leave you with undesirable responses.

• Rate the Likert items

This is done to ascertain the quality of the scales chosen in step 2 above. After generating the Likert scale items, have your selection reviewed. Rate the items as either favorable or unfavorable to your focus.

Then, weed out items that are not favorable to your survey focus.

• Group the scale items

In cases where there were diverse options for the respondents, they may be all too much to analyze at once.

Therefore, you can group them into related categories for ease of analysis.

Positive opinions can be grouped. Negative opinions can also be grouped to simplify analysis.

At this point, we want to see next when you should use Likert scale analysis.

Tips to Analyse Data from the Likert Scale

• Clearly define the objectives of your analysis to ensure focused results.
• Calculate descriptive statistics such as mean and mode to understand central tendencies.
• Use visualizations like bar charts or heat maps to display distribution patterns.
• Employ statistical tests like t-tests or ANOVA for comparing groups.
• Ensure data reliability and validity through consistency checks and validation techniques.

Likert Scale Analysis Use Cases

• Likert scale analysis performs great in many surveys.
• It might be a survey for employee opinion about a new development.
• It might be a survey for quality room service at a hotel.
• For either of these situations, a Likert scale analysis will get the desired results.

Let us break it down.

  i. Customer Satisfaction

This is one of the most common surveys that gets conducted.

For typical satisfaction surveys, an ordinal scale like the Likert scale is used to measure the opinions of customers and clients.

For example, a typical 5-point scale will ask how much a customer agrees with a statement.

The customer will then go ahead to pick an opinion from the most positive response to the otherwise.

In many cases, the customer may opt for the neutral midpoint.

Likert scales for customer satisfaction may not only be scales of agreement.

It is flexible in that different scales can be used as it relates to the Likert question or statement.

Another example is when customers are asked how often they use the hotel’s Wi-Fi.

In this case, a scale of frequency will be used.

An example of a frequency scale would be never, rarely, sometimes, often, and always.

Here is another typical example of a Likert scale to measure customer satisfaction.

Q: How satisfied were you with the complimentary breakfast at the hotel?

Scale:

• Very Satisfied
• Satisfied
• Undecided
• Unsatisfied
• Very Unsatisfied

This is one way to use Likert scale analysis.

Let’s see another.

  ii. Employee Engagement

Just like for customer satisfaction, Likert scales can be used in an employee survey.

The same 5-point scale will also work well in sampling opinions among employees.

You can use the Likert Scale to know how familiar the employees are with new technology and policies.

It can also gauge general feelings about new developments in the company.

It can also measure opinions about employee services and benefits.

An example of a Likert scale for employee engagement is this.

Q: You are satisfied with the investment of the company in education.

Scale:

• Strongly Agree
• Agree
• Neither agree nor disagree
• Disagree
• Strongly Disagree

Let us take a look at one more scenario where you can use Likert scale analysis.

  iii. Professional Event feedback

You just completed an event for professionals in a field.

It could have been business owners, academic lecturers, engineers, consultants, or technology enthusiasts.

• You can use the 5-point Likert scale to collect information on the perceived success of the event.
• You can use it to evaluate the full experience of the audience at the event.
• You can use it to find out their chances of signing up and attending the next event of that sort.

An example of a Likert survey for a professional event is this.

Q: How helpful was the content presented at the event?

Scale:

• Extremely helpful
• Slightly helpful
• Neutral
• Slightly unhelpful
• Extremely unhelpful

Do you remember we talked about a way out of stressful analysis at the beginning?

We’re getting to it right now.

FAQs

How do you summarize Likert scale data?

Summarizing Likert scale data involves entering the responses, calculating frequencies using COUNTIF or similar functions, computing means or averages, and potentially visualizing the data through charts or graphs for easier interpretation.

What is the importance of visualizing Likert Scale data?

Visualizing Likert Scale data helps to quickly identify patterns, trends, and outliers, making the data easier to interpret and communicate.

Wrap Up

Let us guess that you’re not like our friend. Our friend loves to do excruciating work before she feels fulfilled.

We respect her. We just believe on the other hand that things can be and should be simpler.

Data analysis can prove to be excruciating work. What about Likert scale data? Even more excruciating.

From setting up the survey to getting insights from the data, Likert scale analysis can be difficult.

However, following the processes outlined in this article will make it smooth sailing for you.

First, you use the guidelines for setting up effective survey questions.

Then you use ChartExpo to visualize and understand your data.

With ChartExpo, it was easy for Wendy and Curtis. Now, it has become easy for you.

It is time to go on that voyage.

Gear up, Captain!

We’re rooting for you.