{"id":41914,"date":"2022-01-31T04:31:50","date_gmt":"2022-01-31T04:31:50","guid":{"rendered":"https:\/\/www.proprofs.com\/c\/?p=41914"},"modified":"2025-10-22T10:24:42","modified_gmt":"2025-10-22T10:24:42","slug":"quantitative-data","status":"publish","type":"post","link":"https:\/\/www.proprofssurvey.com\/blog\/quantitative-data\/","title":{"rendered":"What Is Quantitative Data: Types With Examples"},"content":{"rendered":"<p style=\"text-align: justify;\"><img loading=\"lazy\" decoding=\"async\" class=\"alignnone size-full wp-image-41917\" src=\"https:\/\/www.proprofssurvey.com\/blog\/wp-content\/uploads\/2022\/01\/Quantitative-Data.jpg\" alt=\"Quantitative Data\" width=\"758\" height=\"335\"><\/p>\n<p style=\"text-align: justify;\"><span style=\"font-weight: 400;\">\u2018<\/span><span style=\"font-weight: 400;\">Quantitative data<\/span><span style=\"font-weight: 400;\">\u2019 can be understood as something that can be counted and measured. It is a simple concept that offers insight into the number of required variables.<\/span><\/p>\n<p style=\"text-align: justify;\"><span style=\"font-weight: 400;\">As a business, you have been using <a href=\"https:\/\/www.proprofssurvey.com\/blog\/qualitative-data\/\">qualitative data<\/a> for different purposes. Think of the time when you wished to know <\/span><b>how many<\/b><span style=\"font-weight: 400;\"> repeat customers you have or <\/span><b>what percentage<\/b><span style=\"font-weight: 400;\"> of customers buy items with a value exceeding $1000.&nbsp;<\/span><\/p>\n<p style=\"text-align: justify;\"><span style=\"font-weight: 400;\"><a href=\"https:\/\/www.proprofssurvey.com\/blog\/quantitative-research\/\">Quantitative research<\/a> can allow you to study a wider audience, get rich insights, and make data-backed decisions in a manner of minutes. So if you are still wondering \u201c<\/span><span style=\"font-weight: 400;\">what is quantitative data<\/span><span style=\"font-weight: 400;\">\u201d and wish to explore its various attributes, collection methods, advantages, or types, this blog is for you.&nbsp;<\/span><\/p>\n<p style=\"text-align: justify;\"><span style=\"font-weight: 400;\">But before we dive into deep waters, let us first start with the <\/span><span style=\"font-weight: 400;\">quantitative data definition<\/span><span style=\"font-weight: 400;\">.<\/span><\/p>\n<h2 style=\"text-align: justify;\"><span class=\"ez-toc-section\" id=\"What_is_Quantitative_Data\"><\/span><strong>What is Quantitative Data?<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p style=\"text-align: justify;\"><span style=\"font-weight: 400;\">Quantitative data<\/span><span style=\"font-weight: 400;\"> refers to data that can be expressed in numerical terms. Answers to questions like \u2018<\/span><b>How much<\/b><span style=\"font-weight: 400;\">\u2019, \u2018<\/span><b>How many<\/b><span style=\"font-weight: 400;\">\u2019, \u2018<\/span><b>What percentage<\/b><span style=\"font-weight: 400;\">\u2019, and \u2018<\/span><b>How often<\/b><span style=\"font-weight: 400;\">\u2019 are what constitutes <\/span><span style=\"font-weight: 400;\">quantitative data<\/span><span style=\"font-weight: 400;\">. Such data cannot be used for statistical analysis. However, you must try and identify relevant groups and descriptions to make sense of the data.<\/span><\/p>\n<p><b>Create a quantitative survey now<\/b><\/p>\n<div class=\"banner-btn newuishow\" style=\"text-align: left!important;\"><a class=\"round_btn try-btn\" href=\"https:\/\/www.proprofs.com\/survey\/register\/?_gl=1*1g46uxl*_ga*MTg0NzgzMTU5OC4xNjg1Njk3MzI4*_ga_P54MCCV7GP*MTcxNzA3Mjg4Mi42NjkuMS4xNzE3MDc0NTMzLjAuMC4w\">Get Started Free<\/a><\/div>\n<h2 style=\"text-align: justify;\"><span class=\"ez-toc-section\" id=\"Quantitative_Data_Types_with_Examples\"><\/span><strong>Quantitative Data Types with Examples<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p style=\"text-align: justify;\"><span style=\"font-weight: 400;\">There are two main <\/span><span style=\"font-weight: 400;\">types of quantitative data<\/span><span style=\"font-weight: 400;\">. They are:<\/span><\/p>\n<ul style=\"text-align: justify;\">\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">Discrete<\/span><\/li>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">Continuous<\/span><\/li>\n<\/ul>\n<p style=\"text-align: justify;\"><span style=\"font-weight: 400;\">In simple terms, Discrete data is countable and Continuous data is measurable. Let\u2019s explore the two types of data in detail.<\/span><\/p>\n<p style=\"text-align: justify;\"><span style=\"font-weight: 400;\">Discrete data is data that can be expressed in specific values. These values are typically counted in whole numbers and cannot be broken down into smaller units. Discrete data is also known as attribute data. Thus, you can easily identify <\/span><span style=\"font-weight: 400;\">discrete quantitative data<\/span><span style=\"font-weight: 400;\"> by questioning whether the given data can be counted or not. This type of data is usually represented using tally charts, bar charts, and pie charts.<\/span><\/p>\n<p style=\"text-align: justify;\"><span style=\"font-weight: 400;\">A few examples of discrete data include:<\/span><\/p>\n<ul style=\"text-align: justify;\">\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">Number of members in a team<\/span><\/li>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">Number of toffees in a packet<\/span><\/li>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">Number of questions in a test paper<\/span><\/li>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">Monthly profit of a business<\/span><\/li>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">Shoe size number<\/span><\/li>\n<\/ul>\n<p style=\"text-align: justify;\"><span style=\"font-weight: 400;\">On the other hand, continuous data is data that can take any value. This value has a tendency to fluctuate over time. Thus, the value will vary over a given period of time, depending on when you seek the data. This type of <\/span><span style=\"font-weight: 400;\">quantitative data<\/span><span style=\"font-weight: 400;\"> is usually represented using a line graph as a line graph aptly illustrates the data changes occurring over a period of time.<\/span><\/p>\n<p style=\"text-align: justify;\">Continuous data can be further divided into two types, namely, ratio data and interval data. Statistically, the geometric or harmonic mean is calculated in ratio data while the arithmetic mean is calculated in interval data.<\/p>\n<p style=\"text-align: justify;\"><span style=\"font-weight: 400;\">A few examples of continuous data include:<\/span><\/p>\n<ul style=\"text-align: justify;\">\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">The daily temperature of a place<\/span><\/li>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">Height of a baby<\/span><\/li>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">Weight of a child<\/span><\/li>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">Wind speed<\/span><\/li>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">Length of a leaf<\/span><\/li>\n<\/ul>\n<h2 style=\"text-align: justify;\"><span class=\"ez-toc-section\" id=\"Quantitative_Data_Collection_Methods\"><\/span><strong>Quantitative Data Collection Methods<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p style=\"text-align: justify;\"><span style=\"font-weight: 400;\">You can collect <\/span><span style=\"font-weight: 400;\">quantitative data<\/span><span style=\"font-weight: 400;\"> in many different ways. Let\u2019s have a look at a few of them.<\/span><\/p>\n<h3 style=\"text-align: justify;\"><strong>1.&nbsp;Probability Sampling<\/strong><\/h3>\n<p style=\"text-align: justify;\"><span style=\"font-weight: 400;\">Probability sampling is a great way to eliminate sampling bias. It allows you to reach out to your target population and collect data in the most effective way possible with a representative sample.<\/span><\/p>\n<p style=\"text-align: justify;\">Additionally, you can opt for any of the following sampling techniques as per your convenience and requirement.<\/p>\n<ul style=\"text-align: justify;\">\n<li><b>Simple random sampling<\/b><span style=\"font-weight: 400;\"> &#8211; In this, each member of the targeted population has an equal probability of being selected for sampling.<\/span><\/li>\n<li><b>Systematic random sampling<\/b><span style=\"font-weight: 400;\"> &#8211; In this, each member of the population is selected from a preset or ordered sampling frame. For example, you select the first target member for sampling randomly and then select the rest in a predetermined fashion thereafter, say every third member of the group or say, every fifth member of the population.<\/span><\/li>\n<li><b>Stratified random sampling<\/b><span style=\"font-weight: 400;\"> -In this method, you divide the population into smaller sub-groups called strata. These strata are made using a common attribute that defines that set of people, for example, income or occupation.<\/span><\/li>\n<\/ul>\n<h3 style=\"text-align: justify;\"><strong>2.&nbsp;Questionnaires and Surveys<\/strong><\/h3>\n<p style=\"text-align: justify;\"><span style=\"font-weight: 400;\">This is a great way to collect quantitative data as it involves quick and to-the-point questions and answers. It comprises surveys, checklists, and ratings. You must have often come across surveys asking you about how many times you buy a certain product or service. These surveys are commonly used to understand customer value and monitor their dependency on the product or service.&nbsp;<\/span><\/p>\n<ul style=\"text-align: justify;\">\n<li><b>Web-based questionnaires<\/b><span style=\"font-weight: 400;\"> often come in the form of a survey link in your mail and include some close-ended questions that aim to collect information about a specific topic. These surveys can be created using secure <\/span><a href=\"https:\/\/www.proprofssurvey.com\/blog\/best-online-survey-tools\/\"><span style=\"font-weight: 400;\">online survey tools<\/span><\/a><span style=\"font-weight: 400;\"> that are easy to collect and can be accessed anywhere and anytime.<\/span><\/li>\n<li><b>Mail questionnaires <\/b><span style=\"font-weight: 400;\">are sent out to the targeted population with a cover sheet that enlightens the audience about the topic. It allows the researcher to connect with a vast number of people, giving them time to get acquainted with the topic and respond to the questionnaire at their convenience. The researcher may also offer an incentive to people for responding to the mail with the complete survey.<\/span><\/li>\n<\/ul>\n<h3 style=\"text-align: justify;\"><strong>3.&nbsp;Interviews<\/strong><\/h3>\n<p style=\"text-align: justify;\"><span style=\"font-weight: 400;\">For interviews, the researcher asks a standard set of questions to the interviewee. The interview may be telephonic or face-to-face. In this, the interviewer prepares a set of questions and puts these in front of the interviewee to answer.&nbsp; The face-to-face is often the most preferred method of interviewing as it is more interactive and allows the interviewer to build rapport. The researcher can also extract insight into answers by observing the body language of the interviewee, etc.<\/span><\/p>\n<h3 style=\"text-align: justify;\"><strong>4.&nbsp;Open Source Datasets<\/strong><\/h3>\n<p style=\"text-align: justify;\"><span style=\"font-weight: 400;\">In the age of the internet, getting information on any topic is no more a hassle. Whether you\u2019re seeking information on finance, communication, dentistry, commerce, or the internet itself, there\u2019s an overflow of information that you can access 24&#215;7. You can easily access free and reliable information from a wide range of open datasets online.<\/span><\/p>\n<h3 style=\"text-align: justify;\"><strong>5.&nbsp;Experiments<\/strong><\/h3>\n<p style=\"text-align: justify;\"><span style=\"font-weight: 400;\">This data collection method involves making some changes to variables and then observing their effect on other variables. For this, you need to be vigilant and be prepared to fail as the success of this method is secured only after trials and errors. Thus, here, the researcher primarily aims to understand the cause and effect relationship of a specific situation.<\/span><\/p>\n<h2 style=\"text-align: justify;\"><span class=\"ez-toc-section\" id=\"Quantitative_Data_Analysis_Methods\"><\/span><strong>Quantitative Data Analysis Methods<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p style=\"text-align: justify;\"><span style=\"font-weight: 400;\">If you\u2019re still looking for an answer to <\/span><span style=\"font-weight: 400;\">how to analyze quantitative data<\/span><span style=\"font-weight: 400;\">, we\u2019re here to help. <\/span><span style=\"font-weight: 400;\">Analyzing quantitative data<\/span><span style=\"font-weight: 400;\"> is easy, provided you collect the right <\/span><span style=\"font-weight: 400;\">quantitative research data<\/span><span style=\"font-weight: 400;\"> and incorporate the right technique to analyze that data.<\/span><\/p>\n<p style=\"text-align: justify;\"><span style=\"font-weight: 400;\">Here, we will look at a few <\/span><span style=\"font-weight: 400;\">quantitative data analysis methods<\/span><span style=\"font-weight: 400;\"> that you can choose to analyze your next data research project effectively.<\/span><\/p>\n<h3 style=\"text-align: justify;\"><strong>1.&nbsp;Cross-Tabulation<\/strong><\/h3>\n<p style=\"text-align: justify;\"><span style=\"font-weight: 400;\">This method utilizes a basic tabular format to draw inferences between the collected data. It involves gathering multiple variables and understanding the correlation between them. This method is also known as contingency table or cross tabs and is apt for extracting relevant information from large data sets<\/span><\/p>\n<h3 style=\"text-align: justify;\"><strong>2.&nbsp;MaxDiff Analysis<\/strong><\/h3>\n<p style=\"text-align: justify;\"><span style=\"font-weight: 400;\">MaxDiff analysis, also called the \u2018best-worst\u2019 method, aims to gauge the preferences of the respondents. So whether you need to know which purchase was more fulfilling for the customer or what parameters the customer ranks more, this method is excellent to adopt in such a scenario.<\/span><\/p>\n<h3 style=\"text-align: justify;\"><strong>3.&nbsp;TURF Analysis<\/strong><\/h3>\n<p style=\"text-align: justify;\"><span style=\"font-weight: 400;\">TURF, an acronym for <\/span><span style=\"font-weight: 400;\">Total Unduplicated Reach and Frequency Analysis, aims to determine the market strategy for a business. It involves analyzing which platform offers the maximum reach so that you can direct your team efforts in the right direction<\/span><\/p>\n<h3 style=\"text-align: justify;\"><strong>4.&nbsp;Gap Analysis<\/strong><\/h3>\n<p style=\"text-align: justify;\"><span style=\"font-weight: 400;\">A gap analysis simply aims to identify gaps in attaining the desired results. It helps identify gaps and bottlenecks, paving the way for improved data and ultimately, better business performance.<\/span><\/p>\n<h3 style=\"text-align: justify;\"><strong>5.&nbsp;SWOT Analysis<\/strong><\/h3>\n<p style=\"text-align: justify;\"><span style=\"font-weight: 400;\">A SWOT analysis helps <\/span><span style=\"font-weight: 400;\">upi identify the various strengths, weaknesses, opportunities, and threats of a product, service, or organization. It helps you visualize the bigger picture and identify which areas need improvement and which areas can be leveraged to improve overall performance.<\/span><\/p>\n<h3 style=\"text-align: justify;\"><strong>6.&nbsp;Text Analysis<\/strong><\/h3>\n<p style=\"text-align: justify;\"><span style=\"font-weight: 400;\">Text analysis is apt for transforming and making sense of unstructured data. This process helps you extract valuable information from a large dataset, easing data collection and improving decision making.<\/span><\/p>\n<h2 style=\"text-align: justify;\"><span class=\"ez-toc-section\" id=\"Steps_to_Conduct_Quantitative_Data_Analysis\"><\/span><strong>Steps to Conduct Quantitative Data Analysis<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p style=\"text-align: justify;\"><span style=\"font-weight: 400;\">Now that you have become familiar with <\/span><span style=\"font-weight: 400;\">quantitative data definition<\/span><span style=\"font-weight: 400;\"> along with data collection and analysis methods, here is how you can conduct <\/span><span style=\"font-weight: 400;\">quantitative data analysis<\/span><span style=\"font-weight: 400;\"> in 5 simple steps.<\/span><\/p>\n<ol style=\"text-align: justify;\">\n<li><b>Validating Data<\/b><span style=\"font-weight: 400;\"> &#8211; The first step to conducting data analysis is to validate your data. Is the data relevant? Is it free of personal bias? These are common questions that you must ask yourself before you set out to analyze the data.<\/span><\/li>\n<li><b>Data Cleaning<\/b><span style=\"font-weight: 400;\"> &#8211; Now, once the data has been validated for accuracy and bias, you must edit the data for consistency and relevancy. For instance, a respondent may have omitted to answer all questions. This is a case for incomplete data that will not give the required details for complete data analysis.<\/span><\/li>\n<li><b>Analyze the Data<\/b><span style=\"font-weight: 400;\"> &#8211; Now is when you sit down to <a href=\"https:\/\/www.proprofssurvey.com\/blog\/how-to-analyze-survey-data\/\">analyze the data<\/a>. Look for descriptive statistics such as Mean, Median, and Percentage and establish a common pattern of evaluation.<\/span><\/li>\n<li><b>Interpret the Results<\/b><span style=\"font-weight: 400;\"> &#8211; In this stage, you transform the data so that it can be easily understood by key stakeholders. Determine a measurement scale and decide how you are going to represent the collected data.<\/span><\/li>\n<\/ol>\n<h2 style=\"text-align: justify;\"><span class=\"ez-toc-section\" id=\"Quantitative_Data_Examples\"><\/span><strong>Quantitative Data Examples<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p style=\"text-align: justify;\"><span style=\"font-weight: 400;\">Identifying <\/span><span style=\"font-weight: 400;\">quantitative data<\/span><span style=\"font-weight: 400;\"> is simple as there is a numerical value assigned to the data. Let\u2019s look at a few <\/span><span style=\"font-weight: 400;\">quantitative data examples<\/span><span style=\"font-weight: 400;\"> in order to grasp a better understanding of it.<\/span><\/p>\n<ul style=\"text-align: justify;\">\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">I grew by <\/span><b>2 inches<\/b><span style=\"font-weight: 400;\"> this year.<\/span><\/li>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">The <\/span><b>43 children<\/b><span style=\"font-weight: 400;\"> attended the event last night.<\/span><\/li>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">He lost <\/span><b>20 pounds<\/b><span style=\"font-weight: 400;\"> after the training.<\/span><\/li>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">We have availed <\/span><b>12 holidays<\/b><span style=\"font-weight: 400;\"> this year.<\/span><\/li>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">The smartphone costs <\/span><b>$1500<\/b><span style=\"font-weight: 400;\">.<\/span><\/li>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">About <\/span><b>34%<\/b><span style=\"font-weight: 400;\"> of people prefer staying in on weekends.<\/span><\/li>\n<li style=\"font-weight: 400;\"><span style=\"font-weight: 400;\">The jar holds <\/span><b>10 gallons<\/b><span style=\"font-weight: 400;\"> of water.<\/span><\/li>\n<li><span style=\"font-weight: 400;\">The room is <\/span><b>30 feet<\/b><span style=\"font-weight: 400;\"> in width.<\/span><\/li>\n<\/ul>\n<p style=\"text-align: justify;\"><span style=\"font-weight: 400;\">In all of the above examples, there is a numerical value in each data.<\/span><\/p>\n<h2 style=\"text-align: justify;\"><span class=\"ez-toc-section\" id=\"Advantages_of_Quantitative_Data\"><\/span><strong>Advantages of Quantitative Data<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p style=\"text-align: justify;\"><span style=\"font-weight: 400;\">The main advantages of <\/span><span style=\"font-weight: 400;\">quantitative data<\/span><span style=\"font-weight: 400;\"> are:<\/span><\/p>\n<ol style=\"text-align: justify;\">\n<li><b>For Extensive Research<\/b><span style=\"font-weight: 400;\"> &#8211; Statistical analysis comes easy with <\/span><span style=\"font-weight: 400;\">quantitative data<\/span><span style=\"font-weight: 400;\">. Such data offer a detailed and better understanding of the subject matter, allowing you to gain insight into the pertaining numerical pattern for further research.<\/span><\/li>\n<li><b>Remove Personal Bias<\/b><span style=\"font-weight: 400;\"> &#8211; Personal preferences influence the quality of respondents\u2019 information. It impacts the interpretation of data received. In the case of quantitative data, which is concrete, it eliminates any scope for personal bias, lending credibility to the data.<\/span><\/li>\n<li><b>Precise Outcome<\/b><span style=\"font-weight: 400;\"> &#8211; Quantifying the data provides specific, accurate, and reliable results. This data is free from incomplete descriptions, offering information that is easy to analyze and interpret.<\/span><\/li>\n<li><b>Summarises Data<\/b><span style=\"font-weight: 400;\"> &#8211; Summarized data in the form of <\/span><span style=\"font-weight: 400;\">quantitative data<\/span><span style=\"font-weight: 400;\"> helps interpret the data quickly, saving both time and effort. Thus, such data helps in extracting relevant and crisp information from a well-analyzed set of data effortlessly.<\/span><\/li>\n<\/ol>\n<h2 style=\"text-align: justify;\"><span class=\"ez-toc-section\" id=\"Disadvantages_of_Quantitative_Data\"><\/span><strong>Disadvantages of Quantitative Data<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p style=\"text-align: justify;\"><span style=\"font-weight: 400;\">Everything has its pros and cons. Similarly, <\/span><span style=\"font-weight: 400;\">quantitative data<\/span><span style=\"font-weight: 400;\"> too has its own share of disadvantages. Let\u2019s look at them below.<\/span><\/p>\n<ol style=\"text-align: justify;\">\n<li><b>Inadequate Data<\/b><span style=\"font-weight: 400;\"> &#8211; Since data is only in quantifiable terms, it is possible to omit the descriptive aspect of the final result.<\/span><\/li>\n<li><b>Misleading Results<\/b><span style=\"font-weight: 400;\"> &#8211; Results of assessing <\/span><span style=\"font-weight: 400;\">quantitative data<\/span><span style=\"font-weight: 400;\"> such as questionnaires and surveys can be misleading as there is a risk of bias creeping in due to prejudiced assumptions.<\/span><\/li>\n<\/ol>\n<h2 style=\"text-align: justify;\"><span class=\"ez-toc-section\" id=\"Difference_Between_Quantitative_Data_and_Qualitative_Data\"><\/span><strong>Difference Between Quantitative Data and Qualitative Data<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p style=\"text-align: justify;\"><span style=\"font-weight: 400;\">We can understand the difference between quantitative and qualitative data clearly with the below table:<\/span><\/p>\n<p style=\"text-align: justify;\"><img loading=\"lazy\" decoding=\"async\" class=\"alignnone size-full wp-image-41923\" src=\"https:\/\/www.proprofssurvey.com\/blog\/wp-content\/uploads\/2022\/01\/what-is-the-difference-between-quantitative-and-qualitative-data.jpg\" alt=\"what is the difference between quantitative and qualitative data\" width=\"758\" height=\"335\"><\/p>\n<h2 style=\"text-align: justify;\"><span class=\"ez-toc-section\" id=\"Ensure_Precision_with_Solid_Quantitative_Data_Collection\"><\/span><strong>Ensure Precision with Solid Quantitative Data Collection<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p style=\"text-align: justify;\"><span style=\"font-weight: 400;\">Data collection is an integral part of any research project. While you may find a particular data collection method convenient to use, the overall gist of collecting data to extract specific, relevant information will remain the same.<\/span><\/p>\n<p style=\"text-align: justify;\">Quantitative data collection offers you data in numerical terms, making it easier for you to support or reject an assumption and arrive at a conclusion. With proven quantitative data collection methods such as surveys, questionnaires, probability sampling, interviews, and experiments,&nbsp; you can get the most relevant answers that help move your research forward.<\/p>\n<p style=\"text-align: justify;\"><span style=\"font-weight: 400;\">Now that you are familiar with everything that encapsulates the collection and analysis of <\/span><span style=\"font-weight: 400;\">quantitative data<\/span><span style=\"font-weight: 400;\">, you can enhance the overall data collection and analysis efficiency with a secure and collaborative research solution &#8211; <\/span><a href=\"https:\/\/www.proprofssurvey.com\/\"><span style=\"font-weight: 400;\">ProProfs Survey Maker<\/span><\/a><span style=\"font-weight: 400;\">. Choose from hundreds of ready-to-use and professionally designed templates to get started with your next survey. You can even <a href=\"https:\/\/www.proprofssurvey.com\/create-a-survey\/\"><strong>create survey<\/strong><\/a>, forms, tests, and quizzes and share these with your respondents as a link, via social media, or even embed them on your website.<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"<p>\u2018Quantitative data\u2019 can be understood as something that can be counted and measured. It is a simple concept that offers insight into the number of required variables. As a business, you have been using qualitative data for different purposes. Think of the time when you wished to know how many repeat customers you have or&#8230;<\/p>\n","protected":false},"author":6,"featured_media":42224,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[9],"tags":[],"class_list":["post-41914","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-customer-satisfaction"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v26.8 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>What Is Quantitative Data: Types &amp; Examples<\/title>\n<meta name=\"description\" content=\"Learn what quantitative data is, with types, examples, collection methods, and analysis tips to run data-driven research.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" 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