{"id":250509,"date":"2023-04-19T11:24:16","date_gmt":"2023-04-19T11:24:16","guid":{"rendered":"https:\/\/imarticus.org\/?p=250509"},"modified":"2023-11-29T06:02:09","modified_gmt":"2023-11-29T06:02:09","slug":"statistics-in-analytics-essential-statistical-techniques","status":"publish","type":"post","link":"https:\/\/imarticus.org\/blog\/statistics-in-analytics-essential-statistical-techniques\/","title":{"rendered":"Statistics in Analytics: Essential Statistical Techniques"},"content":{"rendered":"

In today’s data-driven world, businesses are increasingly relying on analytics to gain insights and make informed decisions. One of the fundamental pillars of analytics is statistics, which involves using mathematical methods to collect, analyse, and interpret data. From predictive modelling to hypothesis testing, statistics play a crucial role in uncovering meaningful patterns and trends in data. <\/span>
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\n<\/span>In addition to mathematical techniques,<\/span> data visualisation<\/span> is also a key component of statistical analysis, as it allows us to present complex data in a way that is easy to understand and visually appealing.<\/span>
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\n<\/span>Let us explore essential statistical techniques that are commonly used in analytics and how they can enhance our understanding and interpretation of statistical results.<\/span><\/p>\n

Essential Statistical Techniques Used in Analysis<\/strong><\/h2>\n

There are a plethora of statistical techniques you can employ in order to get valuable insights from the data you possess. Down below are listed a few of them with real-world examples for each:<\/span><\/p>\n

Descriptive Statistics<\/strong><\/h3>\n

Descriptive statistics as defined by the word itself \u2018describes\u2019 the essential features that one can gather from a dataset. Let\u2019s take a small example to understand it better.<\/span>
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\n<\/span>Imagine a hypothetical scenario where a business is tasked with analysing the sales data for a product over the past year. The dataset they have at their disposal includes a wide range of variables such as the number of units sold each month, the average price per unit, and the total revenue generated.<\/span><\/p>\n

To gain a more granular understanding of the data, the business could employ descriptive statistics techniques. This would allow them to summarise and describe key features of the dataset in a more intuitive manner.<\/span><\/p>\n

The main techniques employed in descriptive statistics:<\/strong><\/p>\n