Data science statistics

Do you need a clear-cut explanation of data science? The What-Where-Who infographic defines all key processes and roles in data science. Check it out!

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Effective decision-making and problem-solving processes are dependent on useful data. The fields of data science and statistics play roles in extracting

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📊🔍 Unlocking the Power of Data Science 🧬🔮: Statistics and Exploratory Data Analysis (EDA) are the secret sauce behind every successful data-driven...

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In the last DIY, we introduced the concept of Exploratory Data Analysis (EDA). This is a fundamental step in Data Science. One of the key components of the EDA is finding out about the data distribution. Let’s inspect this in more depth!

Statistical tests are used in hypothesis testing. They can be used to: determine whether a predictor variable has a statistically significant relationship

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Learn how to create advanced charts like Donut, Pareto and Waterfall in Tableau and to integrate R programming in Tableau to create dynamic visualisations

Numbers aren't just for calculators—they’re the backbone of what data scientists do every day. 🔢 Explore the essential mathematics that power data…

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The foundations of Data Science and machine learning algorithms are in mathematics and statistics. To be the best Data Scientists you can be, your skills in statistical understanding should be well-established. The more you appreciate statistics, the better you will understand how machine learning performs its apparent magic.