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All You Need To Know About Statistics And Probability

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All You Need To Know About Statistics And Probability Statistics And Probability What Is Data? Look around you, there is data everywhere. Each click on your phone generates more data than you know. This generated data provides insights for analysis and helps us make better business decisions. This is why data is so important. What Is Data – Statistics and Probability – Edureka Data refers to facts and statistics collected together for  reference or analysis.  Data can be collected, measured and analyzed. It can also be visualized by using statistical models and graphs. Categories Of Data Data can be categorized into two sub-categories: Qualitative Data Quantitative Data Refer the below figure to understand the different categories of data: Categories Of Data – Statistics and Probability – Edureka Qualitative Data:   Qualitative data deals with characteristics and descriptors that can’t be easily measured, but can be observed subjectively. Qualitative data is further divid...
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What are the Best Books for Data Science?

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What are the Best Books for Data Science? All of us have different takes on learning and gaining knowledge. Some like to watch  videos , some like listening to people, some like being guided, some love reading. If you are a reader and really love the field of  Machine Learning  and  Artificial Intelligence , you are at the right place to get more of what you love. (Links to the free books are mentioned when it is available) This article has the following sections: Overview of Data Science Books to begin with Data Science Books to help you Master Data Science So let’s start your journey and help you find the best books for learning Data Science :) Overview of Data Science So what exactly do we understand by Data Science?  Data Science is a blend of various tools, algorithms, and machine learning principles with the goal to discover hidden patterns from the raw data. That right there is the formal definition but let’s simplify it even more. Data Science is basical...
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The Power of Statistics in Data Analysis—Are You Using It Right?

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How to Create a Power BI Heatmap

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 How to Create a Power BI Heatmap Understand all the ins and outs of how to create Power BI heatmaps and their applications What are Data Visualization Heatmaps? Heatmaps were originally introduced by  Cormac Kinney  to graphically represent real-time financial information. They are used in data visualization to measure the intensity of given business values, encoded using different colors.  The following image is an example of the heatmap, shared by NASA on July 13th, 2022. It shows the surface air temperatures for many countries in the world. The hottest the area is, the darkest the color. Investly, the coldest, the color is more driven towards blue. Such information can be easily understood at a glance.  Data Scientists can use them to turn companies' information into easy-to-understand visualizations to help them make actionable smart decisions. As a Data Scientist, being able to provide businesses with a clear and concise visualization can help them grab ke...
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Basic Statistics Crash Course for data science

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Basic Statistics Crash Course for data science A solid understanding of statistics is crucial for anyone who wants to work with data in data science, economics, psychology, social sciences, business, sports, etc. But the terminology and calculations involved in statistics can be overwhelming for beginners. That’s why we created our Basic Statistics Crash Course that provides a simple example to help you understand fundamental statistical concepts. Our Basic Statistics Crash Course is perfect for preparing for university exams or enhancing your analytical skills. Soon, you’ll be well-equipped to tackle statistics questions during your data science interview or conduct analyses in your work or studies. What Is Statistics for data science? Statistics concerns the collection, analysis, interpretation, and representation of data. Statisticians gather data through surveys, experiments, and observations. They form hypotheses and use statistical methods and models to test them, draw conclusion...
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The 10 Most Important Packages in R for Data Science

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The 10 Most Important Packages in R for Data Science Learn about different packages in R used for data science. Including how to load them and different resources you can use to advance your skills with them. R is the most popular language for Data Science. There are many packages and libraries provided for doing different tasks. For example, there is  dplyr  and  data.table  for data manipulation, whereas libraries like  ggplot2  for data visualization and data cleaning library like  tidyr . Also, there is a library like 'Shiny' to create a Web application and  knitr  for the Report generation where finally  mlr3 ,  xgboost , and  caret  are used in Machine Learning. 1.  ggplot2 ggplot2  is based on the 'Grammar of Graphics", which is a popular data visualization library. Graphs with one variable, two variables, and three variables, along with both categorical and numerical data, can be built. Also, grouping can...
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