{"id":2826,"date":"2021-11-12T12:30:00","date_gmt":"2021-11-12T12:30:00","guid":{"rendered":"https:\/\/statanalytica.com\/blog\/?p=2826"},"modified":"2024-01-20T06:12:31","modified_gmt":"2024-01-20T06:12:31","slug":"data-science-techniques","status":"publish","type":"post","link":"https:\/\/statanalytica.com\/blog\/data-science-techniques\/","title":{"rendered":"10 Useful Data Science Techniques That a Data Scientist use"},"content":{"rendered":"\n<p>Nowadays, data is a valuable thing for any organization. And the adoption of data science technology for the industries is mushrooming day by day at a rapid pace. This technology is a blend of machine learning, mathematics, and statistics. That is required to solve complicated problems. The collection of data from a source is responsible for the result of a data science project.  When a tremendous amount of data is there. It becomes vital to know data science techniques to select feasible data.<\/p>\n\n\n\n<p>It includes processes, scientific methods, systems, and algorithms to collect data and work on it. Data scientists use a lot of techniques to solve problems. Moreover, these techniques focus on searching for credible and relevant information. And work on the weak links that make the model perform poorly. Before talking about data science techniques, it is essential to know about data science.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"what-is-data-science\"><\/span><strong>What is Data Science?<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2><div id=\"ez-toc-container\" class=\"ez-toc-v2_0_82_2 counter-hierarchy ez-toc-counter ez-toc-light-blue ez-toc-container-direction\">\n<p class=\"ez-toc-title\" style=\"cursor:inherit\">Table of Contents<\/p>\n<label for=\"ez-toc-cssicon-toggle-item-69f0756f1ee99\" class=\"ez-toc-cssicon-toggle-label\"><span class=\"\"><span class=\"eztoc-hide\" style=\"display:none;\">Toggle<\/span><span class=\"ez-toc-icon-toggle-span\"><svg style=\"fill: #ff5104;color:#ff5104\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" class=\"list-377408\" width=\"20px\" height=\"20px\" viewBox=\"0 0 24 24\" fill=\"none\"><path d=\"M6 6H4v2h2V6zm14 0H8v2h12V6zM4 11h2v2H4v-2zm16 0H8v2h12v-2zM4 16h2v2H4v-2zm16 0H8v2h12v-2z\" fill=\"currentColor\"><\/path><\/svg><svg style=\"fill: #ff5104;color:#ff5104\" class=\"arrow-unsorted-368013\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" width=\"10px\" height=\"10px\" viewBox=\"0 0 24 24\" version=\"1.2\" baseProfile=\"tiny\"><path d=\"M18.2 9.3l-6.2-6.3-6.2 6.3c-.2.2-.3.4-.3.7s.1.5.3.7c.2.2.4.3.7.3h11c.3 0 .5-.1.7-.3.2-.2.3-.5.3-.7s-.1-.5-.3-.7zM5.8 14.7l6.2 6.3 6.2-6.3c.2-.2.3-.5.3-.7s-.1-.5-.3-.7c-.2-.2-.4-.3-.7-.3h-11c-.3 0-.5.1-.7.3-.2.2-.3.5-.3.7s.1.5.3.7z\"\/><\/svg><\/span><\/span><\/label><input type=\"checkbox\"  id=\"ez-toc-cssicon-toggle-item-69f0756f1ee99\" checked aria-label=\"Toggle\" \/><nav><ul class='ez-toc-list ez-toc-list-level-1 ' ><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-1\" href=\"https:\/\/statanalytica.com\/blog\/data-science-techniques\/#what-is-data-science\" >What is Data Science?<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-2\" href=\"https:\/\/statanalytica.com\/blog\/data-science-techniques\/#what-does-a-data-scientist-do\" >What does a data scientist do?<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-3\" href=\"https:\/\/statanalytica.com\/blog\/data-science-techniques\/#data-science-techniques\" >Data Science Techniques<\/a><ul class='ez-toc-list-level-3' ><li class='ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-4\" href=\"https:\/\/statanalytica.com\/blog\/data-science-techniques\/#1-classification-analysis\" >1. Classification Analysis<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-5\" href=\"https:\/\/statanalytica.com\/blog\/data-science-techniques\/#2-regression-analysis\" >2. Regression Analysis<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-6\" href=\"https:\/\/statanalytica.com\/blog\/data-science-techniques\/#3-jackknife-regression\" >3. Jackknife Regression<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-7\" href=\"https:\/\/statanalytica.com\/blog\/data-science-techniques\/#4-linear-regression\" >4. Linear Regression<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-8\" href=\"https:\/\/statanalytica.com\/blog\/data-science-techniques\/#5-personalization\" >5. Personalization<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-9\" href=\"https:\/\/statanalytica.com\/blog\/data-science-techniques\/#6-anomaly-detection\" >6. Anomaly Detection<\/a><\/li><\/ul><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-10\" href=\"https:\/\/statanalytica.com\/blog\/data-science-techniques\/#also-read\" >Also Read<\/a><ul class='ez-toc-list-level-3' ><li class='ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-11\" href=\"https:\/\/statanalytica.com\/blog\/data-science-techniques\/#7-segmentation\" >7. Segmentation<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-12\" href=\"https:\/\/statanalytica.com\/blog\/data-science-techniques\/#8-clustering-analysis\" >8. Clustering Analysis<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-13\" href=\"https:\/\/statanalytica.com\/blog\/data-science-techniques\/#9-decision-tree\" >9. Decision Tree<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-14\" href=\"https:\/\/statanalytica.com\/blog\/data-science-techniques\/#10-game-theory\" >10. Game Theory<\/a><\/li><\/ul><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-15\" href=\"https:\/\/statanalytica.com\/blog\/data-science-techniques\/#conclusion\" >Conclusion<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-16\" href=\"https:\/\/statanalytica.com\/blog\/data-science-techniques\/#frequently-asked-questions\" >Frequently Asked Questions<\/a><ul class='ez-toc-list-level-3' ><li class='ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-17\" href=\"https:\/\/statanalytica.com\/blog\/data-science-techniques\/#what-is-the-purpose-of-data-science\" >What is the purpose of Data Science?<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-18\" href=\"https:\/\/statanalytica.com\/blog\/data-science-techniques\/#what-are-the-skills-required-to-be-a-data-scientist\" >What are the skills required to be a Data Scientist?<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-19\" href=\"https:\/\/statanalytica.com\/blog\/data-science-techniques\/#what-are-programming-languages-essential-in-data-science\" >What are programming languages essential in Data Science?<\/a><\/li><\/ul><\/li><\/ul><\/nav><\/div>\n\n\n\n\n<p>It is a booming field adopted by various disciplines. It involves different genres, scientific methods, algorithms, processes. And systems to collect data from all organizations to derive useful information. Moreover, this derived information through data science techniques. In contrast, it helps the organizations in decision-making for future objectives. Moreover, this field requires statistics, data analysis, and machine learning skills. In this data-driven world, data science is a valuable tool for us.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"what-does-a-data-scientist-do\"><\/span><strong>What does a data scientist do?<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<p>A data scientist uses the data of a particular organization and supports the business. Moreover, a data scientist performs the task of utilizing the data within the enterprise. And analyzes it to derive useful information. It will help them in the decision-making process.<br>The data scientist adds the essential data and develops a new result that helps solve the problems.<br>Data scientists use different methods<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>They create a theory or hypothesis\\<\/li>\n\n\n\n<li>Then attain the data to check the hypothesis.<\/li>\n\n\n\n<li>Analyze this data.<\/li>\n\n\n\n<li>Data is filtered from the analyzed data for further testing.<\/li>\n\n\n\n<li>Derive conclusion and make decisions.<\/li>\n<\/ul>\n\n\n\n<p>Data scientists use various techniques to fulfill these tasks. Here, we explain it in detail.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"data-science-techniques\"><\/span><strong>Data Science Techniques<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<p>Techniques are several methods that a data scientist uses to perform different tasks. Such as collecting, storing, filtering, classifying, validating, analyzing and processing for final outcome.<\/p>\n\n\n\n<p>Data scientists apply these procedures. It is one of the techniques on the data by special software (tools).<br>Let us explore the most important mathematical and statistical techniques that a data scientist needs to learn.<br>The data scientists and analysts generally work on the below techniques-<\/p>\n\n\n\n<h3 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"1-classification-analysis\"><\/span><strong>1. Classification Analysis<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<p>This type of analysis demands mathematical approaches. Likewise decision trees, linear programming, statistics, and neural networks. There is a need to identify and assign categories to the gathered data. For this purpose, we use classification analysis to analyze the data for a higher degree of precision. In contrast, classification algorithms are derived in the form of classes to attain target variables<\/p>\n\n\n\n<h3 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"2-regression-analysis\"><\/span><strong>2. Regression Analysis<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<p>We use regression analysis when we need to determine. That is how closely interrelated independent data variables depend on a dependent data variable. Similarly, it is a machine learning algorithm that helps to note down the changes of one of the values of a dependent variable. With respect to independent variables that vary with other fixed data. In contrast, this method is beneficial for predicting the average value of the dependent variables. This technique aims to build models on datasets for estimating the value of the dependent variables.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"3-jackknife-regression\"><\/span><strong>3. Jackknife Regression<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<p>This is an old resampling technique given by Quenouille and named by Tukey in 1949,1958 respectively. It may be used as a black box as it is powerful and parameter-free, working. Furthermore easy to break by non-statisticians used to predict the variance and bias of a huge population.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"4-linear-regression\"><\/span><strong>4. Linear Regression<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<p>Let us suppose a data scientist is required to design a model to predict the marks of students. If the number of study hours is given. In this situation, he will use linear regression that is a linear model. Furthermore to estimate a linear relationship between input variables and output variables. Here the input variable is taken as the independent variable &#8216;X,&#8217; and the output variable is the dependent variable &#8216;Y&#8217;. Here &#8216;Y&#8217; can be determined from a linear combination of input variables &#8216;X&#8217;.<br>If the number of students and their study hours with a grade is considered as the training data.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"5-personalization\"><\/span><strong>5. Personalization<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<p>Personalization is creating a system that makes recommendations on the basis of past decisions. However, by using technology like recommendation engines and hyper-personalization systems. Moreover, effective data science work allows websites, marketing deals. It also helps to make personalization to individuals&#8217; unique needs and desires<\/p>\n\n\n\n<h3 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"6-anomaly-detection\"><\/span><strong>6. Anomaly Detection<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<p>Anomaly detection is also called outlier detection. It is a stage in data mining where identifying data points, observations. And events derived from a dataset&#8217;s apparent behavior occur. In addition, it is helpful to avoid hacking, intrusion detection, monitoring, fraud detection in credit card transactions. And operating environment to detect the fault.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"also-read\"><\/span><strong>Also Read<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<ul class=\"wp-block-list\">\n<li><a href=\"https:\/\/statanalytica.com\/blog\/applications-of-data-science\/\">Applications of Data Science<\/a><\/li>\n\n\n\n<li><a href=\"https:\/\/statanalytica.com\/blog\/best-books-for-data-science\/\">Best Books For Data Science<\/a><\/li>\n\n\n\n<li><a href=\"https:\/\/statanalytica.com\/blog\/data-science-skills\/\">Data Science Skills<\/a><\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"7-segmentation\"><\/span><strong>7. Segmentation<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<p>It is one of the vital data science techniques of data science. In this data, scientists use data segmentation in marketing efforts to help you examine your customers. And make the advertising campaign results effective. In addition, segmented data in data science helps businesses transfer the most suitable message to the target audience. And each segment related to particular customer needs.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"8-clustering-analysis\"><\/span><strong>8. Clustering Analysis<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<p>This technique is referred to as the cluster technique. Data scientists use it to differentiate the whole dataset into segments. To make traits on one group data point similar. For instance, when you plan to scale the retail business. It is compulsory to examine how the fresh customers will react in a new area based on previous data you have. So it becomes very complicated to make a strategy for each individual in the crowd. In case, to avoid this complication, it is helpful to segregate this population into clusters for effectiveness.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"9-decision-tree\"><\/span><strong>9. Decision Tree<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<p>The decision tree is a map of the feasible outcomes of a sequence of interrelated choices to supervise the learning difficulties. Likewise classification and regression with the help of a decision tree algorithm. It enables individuals or organizations to take a feasible stand against one another. Similarly, it is based on their probabilities, benefits, and costs.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"10-game-theory\"><\/span><strong>10. Game Theory<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h3>\n\n\n\n<p>Game theory is a way to analyze competitive circumstances in an organized way used by data scientists. Moreover, it is an additional concept data scientists can learn to predict how logical people make decisions. Similarly, it will help them to make effective decisions based on strategic situations.<\/p>\n\n\n\n<p>Well, this is not the end of the list. If you possess mathematics and statistics skills. You know how the theories and techniques work. Especially when you&#8217;re a data scientist and have to conclude research on the data.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"conclusion\"><\/span><strong>Conclusion<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<p>In conclusion, we have discussed the various data science techniques. These techniques are the part of data scientists for numerous reasons. We also explored the definition of data science and the objectives of a data scientist. In contrast, you can understand the role of data science and techniques in an enterprise. I hope this blog will be helpful for you to understand the various methods used in data science. Despite this, you can get the best <a href=\"https:\/\/statanalytica.com\/data-science-assignment-help\">data science homework help<\/a> from the experts to clear all these techniques.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><span class=\"ez-toc-section\" id=\"frequently-asked-questions\"><\/span><strong>Frequently Asked Questions<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n<div id=\"rank-math-faq\" class=\"rank-math-block\">\n<div class=\"rank-math-list \">\n<div id=\"faq-question-611750f05ee1a\" class=\"rank-math-list-item\">\n<h3 class=\"rank-math-question \"><span class=\"ez-toc-section\" id=\"what-is-the-purpose-of-data-science\"><\/span><br \/><strong>What is the purpose of Data Science?<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h3>\n<div class=\"rank-math-answer \">\n\n<p>Data Science aims to investigate data and filter it to find out valuable information for the enterprise.<\/p>\n\n<\/div>\n<\/div>\n<div id=\"faq-question-611750f05ee1e\" class=\"rank-math-list-item\">\n<h3 class=\"rank-math-question \"><span class=\"ez-toc-section\" id=\"what-are-the-skills-required-to-be-a-data-scientist\"><\/span><strong>What are the skills required to be a Data Scientist?<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h3>\n<div class=\"rank-math-answer \">\n\n<p>Basics of data processing and computer science.<br \/>Knowledge of business<br \/>Math and statistics skills<\/p>\n\n<\/div>\n<\/div>\n<div id=\"faq-question-611750f05ee1f\" class=\"rank-math-list-item\">\n<h3 class=\"rank-math-question \"><span class=\"ez-toc-section\" id=\"what-are-programming-languages-essential-in-data-science\"><\/span><strong>What are programming languages essential in Data Science?<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h3>\n<div class=\"rank-math-answer \">\n\n<p>Three languages are needed in data science.<br \/>Python<br \/>R project<br \/>Scala\/Java<\/p>\n\n<\/div>\n<\/div>\n<\/div>\n<\/div>","protected":false},"excerpt":{"rendered":"<p>Nowadays, data is a valuable thing for any organization. And the adoption of data science technology for the industries is mushrooming day by day at a rapid pace. This technology is a blend of machine learning, mathematics, and statistics. That is required to solve complicated problems. The collection of data from a source is responsible [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":2829,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"site-sidebar-layout":"default","site-content-layout":"default","ast-site-content-layout":"default","site-content-style":"default","site-sidebar-style":"default","ast-global-header-display":"","ast-banner-title-visibility":"","ast-main-header-display":"","ast-hfb-above-header-display":"","ast-hfb-below-header-display":"","ast-hfb-mobile-header-display":"","site-post-title":"","ast-breadcrumbs-content":"","ast-featured-img":"","footer-sml-layout":"","ast-disable-related-posts":"","theme-transparent-header-meta":"default","adv-header-id-meta":"","stick-header-meta":"","header-above-stick-meta":"","header-main-stick-meta":"","header-below-stick-meta":"","astra-migrate-meta-layouts":"set","ast-page-background-enabled":"default","ast-page-background-meta":{"desktop":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}},"ast-content-background-meta":{"desktop":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}},"footnotes":""},"categories":[77],"tags":[5,545,546,172,170],"class_list":["post-2826","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-data-science","tag-data-science","tag-data-science-technique","tag-data-scientist","tag-mathematics","tag-statistics"],"amp_enabled":true,"_links":{"self":[{"href":"https:\/\/statanalytica.com\/blog\/wp-json\/wp\/v2\/posts\/2826","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/statanalytica.com\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/statanalytica.com\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/statanalytica.com\/blog\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/statanalytica.com\/blog\/wp-json\/wp\/v2\/comments?post=2826"}],"version-history":[{"count":0,"href":"https:\/\/statanalytica.com\/blog\/wp-json\/wp\/v2\/posts\/2826\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/statanalytica.com\/blog\/wp-json\/wp\/v2\/media\/2829"}],"wp:attachment":[{"href":"https:\/\/statanalytica.com\/blog\/wp-json\/wp\/v2\/media?parent=2826"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/statanalytica.com\/blog\/wp-json\/wp\/v2\/categories?post=2826"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/statanalytica.com\/blog\/wp-json\/wp\/v2\/tags?post=2826"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}