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Statistical Concepts Necessary for Data Science

Data science is a rapidly growing field that combines statistics, computer science, and domain knowledge to extract insights from data. Statistical concepts play a fundamental role in data science, as they provide the tools and techniques for collecting, cleaning, analyzing, and interpreting data.

This article will provide an overview of the key statistical concepts that data scientists need to know. It will cover both descriptive statistics and inferential statistics, as well as some more advanced topics such as probability distributions, hypothesis testing, and regression.

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Role of Data Science and Analytics for Strategic Decisions

In today's data-driven world, organizations are turning to data science and analytics to gain a competitive edge and make informed, strategic decisions. Data-driven decision-making is no longer an option; it's a necessity. This article explores the pivotal role that data science and analytics play in shaping strategic choices and driving business success.

1. Getting to Know Data Science and Analytics

Let's define data science and analytics first before discussing their significance in strategic decisions.

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How To Create Interactive Reports in Power BI: A Step-By-Step Tutorial

In today's data-driven world, the ability to transform raw data into actionable insights is a valuable skill. Microsoft Power BI, a powerful business intelligence tool, empowers users to do just that. With Power BI, you can create interactive reports and dashboards that make data come alive, facilitating informed decision-making. In this step-by-step tutorial, we will guide you through the process of creating interactive reports in Power BI, allowing you to harness the full potential of your data.

Step 1: Install Power BI Desktop

Before we begin, make sure you have Power BI Desktop installed on your computer. You can download it from the official Power BI website. Once installed, launch the application.