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. To strengthen your understanding of qualitative and quantitative data, think of a few ways in your life where both can be applied. In this post, we’ll define both quantitative and qualitative data in more detail. Quantitative data is numerical information (numbers) Quantitative data can be Discrete or Continuous: 1. Qualitative data focuses on the voice of your customers, asking open-ended questions, and developing ideas. Whereas qualitative is open for exploration, quantitative data is much more concise and close-ended. Examples might be transactions per week, how many people clicked the blue button, and what percentage of users are from Germany. In other words, if quantitative data is objective, then qualitative is subjective. Qualitative data is not countable. 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. We’re often flipping backwards and forwards between letting feedback from a handful of customers drive all our product decisions or requiring everything to be backed up by statistically significant data. Quantitative data is all about ‘How much or how many’. Research data can be placed into two broad categories: quantitative or qualitative. Quantitative data is anything that can be counted or measured; it refers to numerical data. Qualitative data is the data in which the classification of objects is based on attributes and properties. Now that we got the differences out of the way, let’s dive into each type of data using real-world examples. Qualitative data is usually unstructured, which means it’s not ordered or grouped logically. The approach to inquiry in the case of qualitative data is subjective and holistic whereas quantitative data has an objective and focused approach. Qualitative data can be categorized based on traits and characteristics. Analysis of Quantitative data calculating measures of central tendency frequency tables graphical presentation using a bar chart measures of dispersion (range and standard deviation) Analysis of Qualitative data using thematic analysis Outside of work, he enjoys watching his beloved Cubs, playing baseball, and gaming. 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. It is data that can either be counted or compared on a numeric scale. This type of data is loosely formatted with very little structure. Quantitative data and research is used to study trends across large groups in a precise way. Quantitative data collection methods are much more structured than Qualitative data collection methods. French fries and ketchup. Hardware vs. Software: What’s the Difference. Interested in engaging with the team at G2? Qualitative data is descriptive information (it describes something) 2. Qualitative data consist of words and narratives. Quantitative data may be either discrete or continuous. the qualitative data to inform the analysis of the quantitative data (known as multi- stage research design). 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. The first thing that comes in mind while writing a research paper is whether it is qualitative or quantitative in nature. The other type of data is subjective, interpretive, and exploratory. Quantitative data is easier to handle and measure because … Both qualitative data and quantitative data are critical for understanding our target audience and the impact they have on our businesses. Expand your knowledge. Qualitative data can be categorized based on traits and characteristics. Quantitative vs. Qualitative Data. Scientific objectivity: Quantitative data can be interpreted with statistical analysis, and since statistics are based on the principles of mathematics, the quantitative approach is viewed as scientifically objective, and rational (Carr, 1994; Denscombe, 2010). Quantitative data is numerical information that can be measured or counted. Researchers often prefer to use quantitative data over qualitative data because it lends itself more easily to mathematical analysis. Start with yourself as an example. Qualitative data is descriptive information about characteristics that are difficult to define or measure or cannot be expressed numerically. Weakness Provides Explaination - Qualitative data along with quantitative data can explain the result of the survey and can measure the correction of the quantitative data. Conversely, the sample size is large in quantitative data drawn from the representative sample. Quantitative data will almost always be considered structured data. It can be used to ask the questions “how much” or “how many,” followed by conclusive information. This data isn’t necessarily measured using hard numbers used to develop graphs and charts. Your email address will not be published. Useful for testing and validating already constructed theories. Get started for free! Find and create gamified quizzes, lessons, presentations, and flashcards for students, employees, and everyone else. For example, one could apply metadata to describe an unstructured data file. Quantitative and qualitative research methods are two general approaches to gathering and reporting data. In qualitative data, there is an unstructured gathering of data. This type of data is formatted in a way so it can be quickly organized and searchable within relational databases. to provide insights and understanding. The main difference between qualitative and quantitative data is that qualitative data is descriptive while quantitative data is numerical. 1. 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. Contrary to qualitative data, quantitative data is statistical and is typically structured in nature – meaning it is more rigid and defined. Quantitative data can be counted as it’s numerical. Just like with qualitative data, the information derived here can be used to make decisions in a personal or business setting. As against this, data collection is structured in quantitative data. Qualitative versus quantitative data: we’ve all been involved in a conversation debating their respective merits at some point in our careers. Qualitative data reveals customer opinions, values, and beliefs. The data type, in which the classification of objects is based on attributes (quality) is called qualitative data. Rapid analysis: Sophisticated software removes much of the need for prolonged data analysis, especially with large volumes of data involved (Antonius, 2003). Qualitative data is descriptive, referring to things that can be observed but not measured—such as colors or emotions. Quantitative Data is the type of data which can be measured and expressed numerically. Qualitative data develops initial understanding, i.e. On the contrary, qualitative data asks ‘Why?’. Unlike quantitative data, which recommends the final course of action. For quantitative data, consider measurables like your height, weight, age, and shoe size. One type of data is objective, to-the-point, and conclusive. Qualitative data does not include numbers in its definition of traits, whereas quantitative data is all about numbers. 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. These two types of data are quite different, yet, they make up all of the data that will ever be analyzed. Deriving absolute meaning from such data is nearly impossible; hence, it is mostly used for exploratory research. Quantitative data can be counted, measured, and expressed using numbers. Check it out and get in touch! Use quantitative research if you want to confirm or test something(a theory or hypothesis) 2. 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. Qualitative data can be harder to analyse than quantitative data, as the data collected is not inherently objective, and thus can be open to multiple interpretations. 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. Qualitative and quantitative data research are the two main types of research design. it defines the problem. 0 Although different, they can be complementary of one another i.e., in mixed methods 2 Quantitative data is “hard data” borne out of analytics, surveys with statistically significant sample sizes, and other indisputable sources. Small number of non-representative samples. Unlike qualitative interviews, quantitative interviews usually contain closed-ended questions that are delivered in the same format and same order to every respondent. So, which is which? This data is necessary for calculations and further statistical analysis. (dirkcuys) There are two types of data. Better Identification of behavior patterns - Qualitative data can provide detailed information which can prove itself useful in identification of behaviorial patterns. Quantitative data can be counted, measured, and expressed using numbers. We’re always looking for experts to contribute to our Learning Hub in a variety of ways. Quantitative data can be generated through: Quantitative data can actually be broken into further sub-categories. Unlike quantitative data, they are generally not measurable, and are only gained mostly through observation. You can turn qualitative data into structured quantitative data through analysis methods like coding. A rule of thumb for deciding whether to use qualitative or quantitative data is: 1. An example of form analytics 2. Qualitative data analysis works a little differently from quantitative data, primarily because qualitative data is made up of words, observations, images, and even symbols. While qualitative data determines the depth of understanding, quantitative data ascertains the level of occurrence. Ways to gather quantitative data include conducting A/B testing, closed-question surveys, and web analytics. Continuous data is data that can be infinitely broken down into smaller parts or data that continuously fluctuates. Qualitative data will almost always be considered unstructured data or semi-structured. Qualitative vs Quantitative Data – What’s the Difference? Supervised vs Unsupervised Learning – What's the Difference? Examples include clinical trials or censuses. We have all the tools and downloadable guides you need to do your job faster and better - and it’s all free. Qualitative data is non-statistical and is typically unstructured or semi-structured in nature. With a firm grasp on qualitative and quantitative data, you can then begin making sense of the four types of data analytics. The two data analysis types work great together to help organizations build much more successful data driven decision making process. Quantitative Research. In short, quantitative data gives you the what, but qualitative data gives you the why, providing you with all you need to make an informed decision. Prior to G2, he helped scale early-stage startups out of Chicago's booming tech scene. Qualitative data can be used to ask the question “why.” It is investigative and is often open-ended until further research is conducted. Difference Between Syllabus and Curriculum, Difference Between Product Marketing and Service Marketing, Difference Between Micro and Macro Economics, Difference Between Developed Countries and Developing Countries, Difference Between Management and Administration, Difference Between Measurement and Evaluation, Difference Between Percentage and Percentile, Difference Between Journalism and Mass Communication, Difference Between Internationalization and Globalization, Difference Between Sale and Hire Purchase, Difference Between Complaint and Grievance, Difference Between Free Trade and Fair Trade. Learn more about the common types of quantitative data, quantitative data collection methods and quantitative data analysis methods with steps. But when we take a step back and attempt to simplify data analysis, we can quickly see it boils down to two things: qualitative and quantitative data. Peanut butter and jelly. Discrete data is just data that cannot be broken down into smaller parts. Which type you choose depends on, among other things, whether you’re taking an inductive vs. deductive research approach; your research question(s); w… Alt-text is a type of metadata applied to image files to assist search engines like Google, Bing, and Yahoo with indexing relevant images. Alternatively you can ‘triangulate’, or collect different types of data to check your While qualitative data determines the depth of understanding, quantitative data ascertains the level of occurrence. This data can help you define problems and areas for improvement. For example, qualitative data are gender, country, city, nationality, etc. Subscribe to keep your fingers on the tech pulse. Qualitative data is also context-specific, so it is not always possible to use the data to say something about situations outside of that context. Privacy, Difference Between Qualitative and Quantitative Research, Difference Between Discrete and Continuous Data, Difference Between Primary and Secondary Data, Difference Between Discrete and Continuous Variable, Difference Between Exploratory and Descriptive Research. Qualitative data is descriptive and conceptual. Devin is a former Content Marketing Specialist at G2, who wrote about data, analytics, and digital marketing. Both qualitative and quantitative data analysis have a vital place in statistics, data science, and market research. Data analysis is broad, exploratory, and downright complex. Quantitative data is all about ‘How much or how many’. Females have brown, black, blonde, and red hair (qualitative). On the other hand, quantitative data is conclusive in nature which aims at testing a specific hypothesis and examine the relationships. Introduction 0 Two main traditions 1 in research: Quantitative and Qualitative 0 Quantitative research = inferential research 0 Qualitative research = interpretive research 0 Both different in terms of goals, applications, sampling procedures, types of data, data analysis, etc. This type of data is measured using numbers and values, which makes it a more suitable candidate for data analysis. -100, 10, 100...) and is finite (meaning it reaches a limit). Both these methods have their advantages and disadvantages, and each of these research approaches is suitable for answering particular types of questions. The analysis of qualitative data can come in many forms including highlighting key words, extracting themes, and elaborating on concepts. Perhaps the most common example of structured data is numbers and values found in spreadsheets. Replication: Quantitative data is based … Before diving into data analytics, it’s important to understand the key differences between qualitative and quantitative data. Use qualitative research if you want to understand something(concepts, thoughts, experiences) For most research topics you can choose a qualitative, quantitative or mixed methods approach. Face-to-face interviews, qualitative questionnaires, focus groups, observation, longitudinal studies, and case studies are examples of qualitative data collection methods. Oil and parmesan cheese. Cut through the noise and dive deep on a specific topic with one of our curated content hubs. For example, it does not make sense to find an average hair color or blood type. It is used to quantify attitudes, opinions, behaviors, and other defined variables – and generalize results from a larger sample population. Data can be qualitative or quantitative. In qualitative data the sample size is small and that too is drawn from non-representative samples. Now that we got the differences out of the way, let’s dive into each type of data using real-world examples. When the data type is qualitative the analysis is non-statistical. Making sense of qualitative data can be time-consuming and expensive, although there are some methods of “structuring” this data. This type of data consists of integers (positive and negative numbers e.g. The type of data which can be counted and expressed in numbers and values is called quantitative data. Qualitative data collection methods rely on opinions, descriptive phrases, and researchers’ subjective conclusions. while quantitative data are length, width, height, weight, area, speed, age, etc. Qualitative data is a little more “touchy-feely” and anecdotal. The cake is orange, blue, and black in color (qualitative). Qualitative data and research is used to study individual cases and to find out how people think or feel in detail. For example, if data are collected on annual income (quantitative), occupation data (qualitative) could also be gathered to get more detail on the average annual income for each type of occupation. Quantitative Research uses measurable data to formulate facts and uncover patterns in research. Using qualitative elements is storytelling with data. It is a major feature of case studies. Like “love,” or “news.”. To acquire qualitative data, consider identifiers like the color of your clothes, type of hair, and nose shape. Discrete data can only take certain values (like whole numbers) 2. Continuous data can take any value (within a range) Put simply: Discrete data is counted, Continuous data is measured Quantitative data are made of numerical information, the analysis of which involves statistical techniques. Another important note is that discrete data can technically be categorical. Quantitative interview data are analyzed by assigning a numerical value to participants’ responses. The research methodology is exploratory in qualitative data, i.e. Qualitative data describes, while quantitative data is expressed using numbers. For example, the number of baseball players last year born in Mexico is whole and discrete. Whether you’re a beginner looking to define an industry term or an expert seeking strategic advice, there’s an article for everyone. It’s chunks of text, photos, videos, and so on. On the contrary, qualitative data asks ‘Why?’ In qualitative data the sample size is small and that too is drawn from non-representative samples. Generating this data from qualitative research is used for theorizations, interpretations, developing hypotheses, and initial understandings. Quantitative and qualitative data can be gathered from the same data unit depending on whether the variable of interest is numerical or categorical. Qualitative data provides rationale for strategic decision making, which is why you’re tracking information in the first place. 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. As opposed to quantitative data which uses statistical analysis. (he/him/his). Qualitative Research ? These categories are called discrete and continuous data. Discrete vs Continuous Data – What’s the Difference? Your time is valuable. Choosing between qualitative vs. quantitative research can be challenging, especially if you do not know their differences. This is an overgeneralization, but helps to differentiate the two. Because of this, qualitative data cannot be collected and analyzed using conventional methods. 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