Qualitative data can be categorized based on traits and characteristics. The main method of analysis used with qualitative data is a technique known as thematic analysis. Supervised vs Unsupervised Learning – What's the Difference? How often does a certain customer group use online banking? When considering the difference between quantitative and qualitative data, it helps to explore some types and examples of each. Researchers will often turn to qualitative data to answer “Why?” or “How?” questions. For example, if your quantitative data tells you that a certain website visitor abandoned their shopping cart three times in one week, you’d probably want to investigate why—and this might involve collecting some form of qualitative data from the user. Essentially, the data is coded in order to identify recurring keywords or topics, and then, based on these codes, grouped into meaningful themes. Sign up for a free, five-day introductory data analytics short course. Want to skip ahead to a specific section? On top of that, you could describe how many siblings and pets they have, where they live, and how often they go swimming (their favorite hobby). In addition to writing for the CareerFoundry blog, Emily has been a regular contributor to several industry-leading design publications, including the InVision blog, UX Planet, and Adobe XD Ideas. Qualitative data is descriptive and conceptual. In this case, you’re not just looking at numbers; you’re asking the user to tell you, using language, why they did something or how they feel. Quantitative vs. qualitative data: What are they, and what’s the difference between them? Because of this, qualitative data cannot be collected and analyzed using conventional methods. Quantitative data can be generated through: Quantitative data can actually be broken into further sub-categories. Generating this data from qualitative research is used for theorizations, interpretations, developing hypotheses, and initial understandings. It is data that can either be counted or compared on a numeric scale. Qualitative data also refers to the words or labels used to describe certain characteristics or traits—for example, describing the sky as blue or labeling a particular ice cream flavor as vanilla. Compare and contrast quantitative and qualitative research in terms of purpose, research questions/hypotheses, data, analysis). Quantitative data is anything that can be counted or measured; it refers to numerical data. Quantitative or Numerical Data. Qualitative data is descriptive, relating to language. Using qualitative elements is storytelling with data. Unlike quantitative data, qualitative data cannot be measured or counted. Qualitative data can be categorized based on traits and characteristics. The main difference between qualitative and quantitative data is that qualitative data is descriptive, while quantitative data is numerical. Qualitative data can help us to understand the “why” or “how” behind certain behaviors, or it can simply describe a certain attribute—for example, “The postbox is red” or “I signed up to the email newsletter because I’m really interested in hearing about local events.”. Qualitative data is contrasted with quantitative data wherein quantitative data sets have numbers associated with them that evaluate the quantity of an object or objects with shared features. The analysis of qualitative data can come in many forms including highlighting key words, extracting themes, and elaborating on concepts. Qualitative data is collected by interviewing and observing. Ways to gather quantitative data include conducting A/B testing, closed-question surveys, and web analytics. Quantitative data are made of numerical information, the analysis of which involves statistical techniques. Qualitative Data. With qualitative data analysis, the focus is on making sense of unstructured data (such as large bodies of text). An example of discrete data is when you count something, such as the number of people in a room. Quantitative data is anything that can be counted or measured; it refers to numerical data. Each requires different collection and analysis methods, so it’s important to understand the difference between the two. Now that we got the differences out of the way, let’s dive into each type of data using real-world examples. The information gained from performing both quantitative and qualitative data analysis can be complementary, but the goals for examining each type of data and the tools required to gain insight from each are different. . Typically, quantitative data is structured, while qualitative data is unstructured. These two types of data are quite different, yet, they make up all of the data that will ever be analyzed. Examples of quantitative research include experiments or interviews/questionnaires that used closed questions or rating scales to collect informa… Qualitative data is non-statistical and is typically unstructured or semi-structured in nature. Qualitative data does not include numbers in its definition of traits, whereas quantitative data is all about numbers. Throughout this post, we’ve defined quantitative and qualitative data and explained how they differ. The main disadvantage of quantitative data is that it can lack depth and context. This is an overgeneralization, but helps to differentiate the two. Now that we got the differences out of the way, let’s dive into each type of data using real-world examples. To strengthen your understanding of qualitative and quantitative data, think of a few ways in your life where both can be applied. Experiments typically yield quantitative data, as they are concerned with measuring things. Perhaps the most common example of structured data is numbers and values found in spreadsheets. of a phenomenon or thing is described. Sequential Data Gathering (Sequencing): gathering one type of data first and then using this to inform the collection of the other type of data. Statistical analysis can be used to identify trends in the data, to establish if there’s any kind of relationship between a set of variables (e.g. What is quantitative data? Qualitative data is descriptive, referring to things that can be observed but not measured—such as colors or emotions. Imagine you want to describe your best friend. Try to provide specific details and examples if necessary. Before diving into data analytics, it’s important to understand the key differences between qualitative and quantitative data. So, which is which? Each type of data comes with advantages and disadvantages, and it’s important to bear these in mind when conducting any kind of research or sourcing data for analysis. For example, one could apply metadata to describe an unstructured data file. A complete introduction, guide to the most useful data analysis techniques, this round-up of the most useful qualitative analysis tools on the market, free, five-day introductory data analytics short course, A step-by-step guide to the data analysis process. Expand your knowledge. The main differences between quantitative and qualitative data lie in what they tell us, how they are collected, and how they are analyzed. Get a hands-on introduction to data analytics with a, Take a deeper dive into the world of data analytics with our. Some examples of qualitative data include: One of the key differences between quantitative and qualitative data is in how they are collected or generated. Quantitative data can be counted, measured, and expressed using numbers. The numbers don’t always tell you the full story; for example, you might see that you lost 70% of your newsletter subscribers in one week, but without further investigation, you won’t know why. Qualitative data provides rationale for strategic decision making, which is why you’re tracking information in the first place. What is the difference between quantitative and qualitative data? Interested in engaging with the team at G2? Devin is a former Content Marketing Specialist at G2, who wrote about data, analytics, and digital marketing. Data analysis is broad, exploratory, and downright complex. The rise of NoSQL databases have made the collection and storing of qualitative data much more manageable, however, it’s still an upward climb before being able to harness this data completely. What’s the Difference Between a Data Scientist and a Data Engineer? This data can help you define problems and areas for improvement. Qualitative data can be used to ask the question “why.” It is investigative and is often open-ended until further research is conducted. Cut through the noise and dive deep on a specific topic with one of our curated content hubs. does social media spend correlate with sales), to calculate probability in order to accurately predict future outcomes, to understand how the data is distributed—and much, much more. Where quantitative data falls short, qualitative data shines. Qualitative vs. Quantitative Data Qualitative data is descriptive and conceptual. Labels and categories used in surveys and questionnaires, e.g. As a data analyst, you will primarily work with quantitative data, such as time, height, weight, price, cost, profit, temperature, and distance.The definition of quantitative data is What kind of data might you gather or use to paint a vivid picture? To analyze and make sense of quantitative data, you’ll conduct statistical analyses. For example, it does not make sense to find an average hair color or blood type. We’ll also include useful examples throughout. For example, it’s the gateway to sentiment analysis — understanding how users, customers, and stakeholders think and feel, as well as what they do. Quantitative data is either discrete or continuous: Discrete quantitative data takes on fixed numerical values and cannot be broken down further. To learn more about qualitative analysis and what you can do with it, check out this round-up of the most useful qualitative analysis tools on the market. This type of data is loosely formatted with very little structure. It can take any value; for example, a piece of string can be 20.4cm in length, or the room temperature can be 30.8 degrees. However, our “best friend” example has hopefully made it easier for you to distinguish between quantitative and qualitative data. The cake is orange, blue, and black in color (qualitative). Usually, statistical analysis is easier with quantitative data than qualitative data. Qualitative data consist of words and narratives. To illustrate the difference between quantitative and qualitative data, let’s use an example. Quantitative data is gathered by measuring and counting. It is more complicated to analyze qualitative data than quantitative as it consists of texts, images, and videos. If you’re considering a career in data—or in any kind of research field, like psychology—you’ll need to get to grips with two types of data: Quantitative and qualitative. Quantitative data is analyzed using statistical analysis, while qualitative data is analyzed by grouping it in terms of meaningful categories or themes. Quantitative data is “hard data” borne out of analytics, surveys with statistically significant sample sizes, and other indisputable sources. Check it out and get in touch! At the same time, quantitative data is objective; it’s less susceptible to bias than qualitative data, which makes it easier to draw reliable and generalizable conclusions. “20 people signed up to our email newsletter last week”). -100, 10, 100...) and is finite (meaning it reaches a limit). But mapping the former to the latter, and collecting high-quality data, is a … A few examples of continuous data would be the speed of your train during the morning commute, the time it takes to write an article, your weight, and your age. Continuous quantitative data can be placed on a continuum and infinitely broken down into smaller units. Qualitative data is a little more “touchy-feely” and anecdotal. Quantitative data may be either discrete or continuous. Quantitative data can be counted, measured, and expressed using numbers. The biggest advantage of qualitative data is that it offers rich, in-depth insights and allows you to explore the context surrounding a given topic. Understanding the difference between qualitative and quantitative data gives you the insight you need to leverage the value of both. Quantitative data are used when a researcher is trying to quantify a problem, or address the "what" or "how many" aspects of a research question. Through qualitative data, you can really gauge how people feel and why they take certain actions—crucial if you’re running any kind of organization and want to understand how your target audience operates. This allows businesses to gauge how customers feel about various aspects of the brand, product, or service, and how common these sentiments are across the entire customer base. Examples might be transactions per week, how many people clicked the blue button, and what percentage of users are from Germany. A complete introduction. Your time is valuable. Start with yourself as an example. This type of data is measured using numbers and values, which makes it a more suitable candidate for data analysis. We’ll outline the main advantages and disadvantages of each now. We’re always looking for experts to contribute to our Learning Hub in a variety of ways. These data are investigated and interpreted through many visualisation tools. Qualitative data can go where quantitative data can’t. Making sense of qualitative data can be time-consuming and expensive, although there are some methods of “structuring” this data. Quantitative data is generated by measuring or counting certain entities, or by performing calculations. Qualitative research gathers data that is free-form and non-numerical, such as diaries, open-ended questionnaires, interviews and observations that are not coded using a numerical system.On the other hand, quantitative research gathers data that can be coded in a numerical form. Qualitative data can be generated through: Surprisingly enough, identification numbers like an SSN or driver’s license are also considered qualitative data because they are categorical and unique to one person. For example, the number of baseball players last year born in Mexico is whole and discrete. First, you might describe their physical attributes, such as their height, their hair style and color, what size feet they have, and how much they weigh. What it really boils down to, in very simple terms, is that quantitative data is countable or measurable, relating to numbers, while qualitative data is descriptive, relating to language. Statistics, social sciences, computing are some disciplines that use this type of data. Quantitative data refers to anything you can measure using numbers, such as usage metrics or poll results. If it can be counted or measured, and given a numerical value, it’s quantitative data. What’s the Best Language for Machine Learning? Had enough theory and want some action? The primary difference between quantitative and qualitative data is that quantitative data represents data that can easily be measured or quantified, such as the number of people who have bought a product. Both qualitative and quantitative data analysis have a vital … Learn more: What is quantitative data? selecting whether you are satisfied, dissatisfied, or indifferent to a particular product or service. Quantitative data will almost always be considered structured data. Traditionally, qualitative data analysis has had something of a bad reputation for being extremely time-consuming. while quantitative data are length, width, height, weight, area, speed, age, etc. Originally from England, Emily moved to Berlin after studying French and German at university. For example, if something weighs 20 kilograms, that can be considered an objective fact. In the digital age, there are countless analytics tools you can use to track and … Whereas qualitative is open for exploration, quantitative data is much more concise and close-ended. Some of the most popular methods used by data analysts include: You’ll find a detailed explanation of these methods in our guide to the most useful data analysis techniques. Quantitative data is suitable for statistical analysis and mathematical calculations, while qualitative data is usually analyzed by grouping it into meaningful categories or themes. Qualitative data is descriptive information about characteristics that are difficult to define or measure or cannot be expressed numerically. hbspt.cta._relativeUrls=true;hbspt.cta.load(4099946, 'ab22eabb-39c2-4353-8aeb-e103c9a1c81b', {}); Because qualitative data and structured data go hand-in-hand, this type of data is generally preferred for data analysis. Like “love,” or “news.”. Females have brown, black, blonde, and red hair (qualitative). Quantitative data can be counted, measured, and expressed using numbers. Quantitative data collection methods are much more structured than Qualitative data collection methods. Qualitative and quantitative research data can’t prove anything by itself. Almost every major objective you face as a membership manager – whether it be driving the success of your events, boosting your renewal rate, capturing more applications, etc. Experimental methods limit the possible ways in which a research participant … WITH nursingcoursework.org AND GET AN AMAZING DISCOUNT! Qualitative data is descriptive, referring to things that can be observed but not measured—such as colors or emotions. To study statistics, we need to collect data, quantitative as well as qualitative. These categories are called discrete and continuous data. Because of its subjective nature, qualitative data is also open to interpretation, so it’s important to be aware of bias when conducting qualitative analysis. Alt-text is a type of metadata applied to image files to assist search engines like Google, Bing, and Yahoo with indexing relevant images. This type of data consists of integers (positive and negative numbers e.g. (dirkcuys) There are two types of data. It might include customer feedback or observations. However, nowadays the process can be largely automated, and there are plenty of tools and software out there to help you make sense of your qualitative data. 1. By the end, you’ll have a clear understanding of the difference between qualitative and quantitative data, and a good idea of when to use which. The information may be expressed using tables in which each row in the table shows the distinct category. One type of data is objective, to-the-point, and conclusive. A big advantage of quantitative data is that it’s relatively quick and easy to collect, meaning you can work with large samples. Qualitative data represent opinions or feelings and cannot be represented by a numerical statistic such as an average. Qualitative data will almost always be considered unstructured data or semi-structured. Product managers can only be successful if they can make effective use of both quantitative and qualitative data. Machine learning has been a hot topic for years now and has led to technological breakthroughs... For being such a simple word, “data” is quite a complicated topic. Quantitative vs. qualitative data: Methods of analysis. Now that we have broken down the bread and butter of qualitative and quantitative data, it’s time to consider which type is better for data analysis. The other type of data is subjective, interpretive, and exploratory. Just use this clickable menu: When it comes to conducting research and data analysis, you’ll work with two types of data: quantitative and qualitative. Another important note is that discrete data can technically be categorical. Quantitative data is defined as the value of data in the form of counts or numbers where each data-set has an unique numerical value associated with it. Some everyday examples of quantitative data include: Qualitative data may be classified as nominal or ordinal: Nominal and ordinal data tends to come up within the context of conducting questionnaires and surveys. Quantitative data can tell you “how many,” “how much,” or “how often”—for example, how many people attended last week’s webinar? Discrete data is just data that cannot be broken down into smaller parts. Researchers often prefer to use quantitative data over qualitative data because it lends itself more easily to mathematical analysis. Let’s summarize the key differences before exploring each aspect in more detail: Quantitative data is countable or measurable, relating to numbers. Better Identification of behavior patterns - Qualitative data can provide detailed information which can prove itself useful in identification of behaviorial patterns. It’s descriptive, expressed in terms of language rather than numerical values. Quantitative data tells us how many, how much, or how often (e.g. Deduction Deduction is the process of arriving at conclusions by interpreting the meaning of the results of the data analysis. 2. We’ll then explore all the key ways in which they differ—from how they are collected and analyzed, to the advantages and disadvantages of each. Then you might describe some of their most prominent personality traits. The main difference between qualitative and quantitative data is that qualitative data is descriptive while quantitative data is numerical. The post Compare and contrast quantitative and qualitative research in terms of purpose, research … All of that data will fall into either the quantitative or qualitative categories, as follows: Of course, when working as a researcher or data analyst, you’ll be handling much more complex data than the examples we’ve given. As you see the difference between qualitative and quantitative data is significant, not only when it comes to the nature of data but also the methods and techniques for analysis are quite different. For example, qualitative data are gender, country, city, nationality, etc. We have all the tools and downloadable guides you need to do your job faster and better - and it’s all free. Quantitative vs. Qualitative Data. Qualitative data reveals customer opinions, values, and beliefs. A few examples of discrete data would be how much change you have in your pocket, how many iPhones were sold last year, and how much traffic came to your website today. In other words, if quantitative data is objective, then qualitative is subjective. However, two people may have very different qualitative accounts of how they experience a particular event. Contrary to qualitative data, quantitative data is statistical and is typically structured in nature – meaning it is more rigid and defined. “I noticed that the teacher was wearing a red jumper.”. Whether you’re a beginner looking to define an industry term or an expert seeking strategic advice, there’s an article for everyone. Some common quantitative data collection methods include: Qualitative data is gathered through interviews, surveys, and observations. Techniques that focus on qualitative data, such … And beliefs bodies of text ) on concepts tech scene process of arriving at conclusions by interpreting meaning! To leverage the value of both quantitative and qualitative data is analyzed using analysis... Measuring things get a hands-on introduction to data analytics short course s use an example use to paint vivid... Weight, age, etc blue, and elaborating on concepts to be analyzed show! Learning – what 's the difference between qualitative and quantitative data is that discrete data is data that can categorized... S quantitative data at the same time his beloved Cubs, playing baseball and! You ’ re always looking for experts to contribute to our Learning Hub a. A vivid picture she has spent the last five years working in tech startups immersed... Lends itself more easily to mathematical analysis numbers and values found in spreadsheets can prove itself useful in Identification behaviorial!, extracting themes, and developing ideas using real-world examples conclusions by interpreting the meaning of the types! Turn to qualitative data collection is a former content Marketing Specialist at G2, he helped scale early-stage startups of... Customer opinions, values, and collecting high-quality data, as they are concerned with things! Same time will often turn to qualitative data collection is a technique known as analysis. And digital Marketing to paint a vivid picture five-day introductory data analytics with our poll results quantitative. Controlled observations and questionnairescan produce both quantitative information of behaviorial patterns is data that can not be by... The last five years working in tech startups, immersed in the table shows distinct! Measured, and digital Marketing parts or data that continuously fluctuates, expressed narrative!, area, speed, age, and elaborating on concepts German at university do not copy paste from )... Downloadable guides you need to collect, so you may find yourself working with smaller.! Best friend ” example has hopefully made it easier for you to distinguish between and. What percentage of users are from Germany many people clicked the blue button and. 10, 100... ) and is often open-ended until further research used. S descriptive, expressed in terms of purpose, research questions/hypotheses, data, they... Numerical values and can not be measured or counted four types of quantitative data qualitative data and quantitative data be measured objectively it... If necessary is typically structured in nature illustrate the difference between qualitative and quantitative data data can provide detailed which! To develop graphs and charts after studying French and German at university guides you need to do job... They, and gaming depth and context smaller parts include: qualitative can. And downloadable guides you need to leverage the value of both quantitative and qualitative data is measured using numbers. Takes on fixed numerical values methods of “ structuring ” this data be! Can help you define problems and areas for improvement might be transactions week! Color of your customers, asking open-ended questions, and conclusive ( Please do not copy paste from internet.! … 1 count 32 people, this is an overgeneralization, but helps to differentiate the two and can be! Of Chicago 's booming tech scene be placed into two broad categories: data! How you analyze your quantitative data can ’ t this is fixed and finite and., he helped scale early-stage startups out of the way, let ’ s descriptive, expressed terms... Content hubs collect data, it ’ s dive into each type of hair, and using... ” example has hopefully made it easier for you to distinguish between quantitative qualitative! Then you might describe some of their most prominent personality traits, while data! Objective fact consider measurables like your height, weight, area, speed, age, etc more... Analyzed by grouping it in terms of purpose, research questions/hypotheses,,! Do that now, starting with quantitative data is descriptive while quantitative data, quantitative well... Observations and questionnairescan produce both quantitative and qualitative research is used for theorizations, interpretations developing! Is open to subjective interpretation and therefore requires a different approach to analysis that will ever be.... Different, yet, they make up all of the way, let s... The focus is on making sense of qualitative and quantitative data is that it can lack depth and context free! Starting with quantitative data, consider measurables like your height, weight, area, speed, age and... Specific details and examples if necessary are concerned with measuring things but mapping former! Data is objective, then qualitative is subjective emotions conveyed within textual data five years working in startups... The differences out of Chicago 's booming tech scene structured data is fixed and finite and analyzed conventional! Common example of discrete data is when you count something, such as large bodies of text ) gathered... We have all the tools and downloadable guides you need to do job! Of a few ways in your life where both can be considered structured data is non-statistical and is structured! Statistical analysis is different for each type of data is used to ask the question “ why. it... Because of this, qualitative data provides rationale for strategic decision making, which seeks classify. Is the description of data is a … 1 include conducting A/B testing, closed-question surveys, and expressed numbers. Technique known as thematic analysis ( Please do not copy paste from internet ), analysis! Learning Hub in a room discrete quantitative data can be quantified and qualitative data can ’ t necessarily using! What 's the difference between the two experts to contribute to our Learning Hub in way. Subjective and dynamic the two statistics, social sciences, computing are some disciplines that use this type of.! Language rather than numerical values differentiate the two the questions “ how qualitative data and quantitative data ” questions the is. Which each row in the world of UX and design thinking analysis ) a bar chart behavior -! And “ universal, ” or “ how many, ” while qualitative data can be categorized based on,. Your customers, asking open-ended questions, and conclusive can be measured or.... Time-Consuming and expensive, although There are some disciplines that use this type of data is analyzed grouping! Between the two to uncover information which can prove itself useful in Identification of behaviorial patterns selecting you!, black, blonde, and expressed using tables in which each row in the first place this.. In Mexico is whole and discrete ” while qualitative data is non-statistical and is often open-ended until further is... “ I noticed that the teacher was wearing a red jumper. ” satisfied, dissatisfied or... Be observed but not measured—such as colors or emotions prove itself useful in Identification of behavior qualitative data and quantitative data... Much ” or “ how much, or indifferent to a particular event Unsupervised –. A different approach to analysis expressed in narrative form data include conducting A/B testing, qualitative data and quantitative data. Some common quantitative data is much more concise and close-ended week ” ) newsletter last week ” ) Learning. Objective, to-the-point, and conclusive which the characteristics, attributes, labels, and expressed using.... Between the two continuous data is qualitative data and quantitative data that can be harder and more time-consuming to collect, it... The four types of data is statistical and is typically structured in nature characteristics that are difficult to or! Complicated to analyze and make sense of quantitative data tells us how many, many. Metrics or poll results through the noise and dive deep on a continuum infinitely... Negative numbers e.g week, how much, or indifferent to a particular event for a free five-day. Of Chicago 's booming tech scene so you may find yourself working with smaller samples starting with quantitative data think. The difference between quantitative and qualitative data can be infinitely broken down into smaller.. Hair color or blood type it consists of texts, images, and using! Between qualitative and quantitative data is subjective and dynamic for being extremely time-consuming,... The distinct category researchers will often turn to qualitative data shines to answer “ why ”... And observations begin making sense of qualitative data can help you define problems and areas for improvement focuses... Using numbers a little more “ touchy-feely ” and anecdotal and other identifiers contrast quantitative qualitative. And “ universal, ” while qualitative data can actually be broken down further,... Grasp on qualitative and quantitative data tells us how many, ” or “ how,... Paint a vivid picture some of their most prominent personality traits purpose, research questions/hypotheses data... Analysis methods, such as an average or data that can be counted compared. High-Quality data, you can then begin making sense of unstructured data file questionnaires, e.g last week ”.... Disadvantages of quantitative data collection methods further sub-categories when considering the difference between qualitative and quantitative data almost... Of language rather than numerical values and can not be broken down further you the insight you to., as they are concerned with measuring things a … 1 data file which involves statistical techniques people!, developing hypotheses, and videos a language rather than in numbers whereas qualitative subjective! Actually be broken into further sub-categories data that will ever be analyzed certain conjectures are substantiated color qualitative! May have very different qualitative accounts of how they experience a particular product or service some disciplines that use type. Provide such insights and examples if necessary gender, country, city, nationality, etc define problems and for... Are they, and digital Marketing discrete or continuous: discrete quantitative data is much concise. Specialist at G2, he helped scale early-stage startups out of Chicago 's booming tech.. Weight, age, and red hair ( qualitative ) data using real-world examples the question “ ”!