Statistical Data Science is a field of study that can help us understand the world around us. It is an interdisciplinary field that aims to develop data-driven scientific theories and methods for analyzing complex systems. The fields of Statistics, Mathematics, Data Science, Computer Science, Engineering and Psychology are involved in this field of study.
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Moreover, statistical data science is an integral part of data-driven decision-making in a wide range of businesses. Rather than focusing on the raw numbers and calculations, this article will go over key concepts, terms, and aims of the statistical data science field. Some various online courses and certifications helps in understanding statistical data science and its importance.
Read on this article to know in detail about statistical data science, data science certification courses, statistics for data analytics, and importance of statistics for data science.
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Statistical data science is a branch of mathematics and statistics that seeks to extract value from data. It’s used in domains including research, business, marketing, law, and many others. The goal of statistical data science is to find insight into the data using scientific methods. In order to do this, we have to understand concepts such as sample size, skew, variance and outliers.
This article will introduce these concepts in an easy-to-understand way and provide you with some importance of statistics for data science you'll need for learning about this field.
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There are various online diploma courses and online certifications courses that helps in understanding the statistical data science and its importance. You can get online training or certification in Data Science, Business Analytics and Computer Science. Data Science certification courses are great for those who want to learn more about the field without having to go through a traditional education.
The first step is to obtain a professional degree in Statistics, Mathematics or Computer Science is by opting online degree courses. Next, you can enroll in a Data Science certification courses or online course for Business Analytics . The data science certification courses are available with employers and universities at affordable costs.
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Statistics for data analytics is a field of study that analyses statistics, probability, and other numerical or mathematical concepts. Statistics for data analytics is designed to help in understanding the world around us. The field of data science is typically a branch of statistics. This means that the statistical knowledge and tools you already have will help you in your data analytics career.
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A common term used in this field is p-values, which is a type of statistical test that helps determine if one set of data is different from another. Other tests are run to analyze the association between two sets of variables or to determine whether or not one variable has a linear relationship with another variable.
In any case, the goal for these tests is to make sure there is no significant difference between the two sets of data. A key concept in this field is the null hypothesis, which means that there are no significant differences between the two sets of data.
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Data science certifications courses are available online on platforms like Coursera, Udacity, and EdX by MIT Open Courseware.
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Statistics and data science is involved in analyzing complex systems. Statistics is a branch of mathematics that deals with data. It is used in all fields of science, technology, engineering and business. Statistics helps us to analyze data and understand the underlying mechanisms behind the processes.
The field of statistics is an integral part of data-driven decision-making in a wide range of businesses. There are various online courses and certifications that helps in understanding the importance of statistics for data science. For the ease of understanding, here are quick pointers stating importance of statistics for data science:
Data science is a broad field that focuses on analyzing data to help answer business questions. In contrast, statistical data science focuses on understanding how statistics can be used to analyze and understand data. The terms have been interchangeably used in recent years, but they are not the same and will never be the same.
A statistician collects, processes, analyzes, models or interprets numerical or categorical data to reveal relationships between variables or associations among events or policies for making decisions about future outcomes.
Statisticians study topics such as Probability Theory, Statistics, Data Analysis, Decision Theory etc., which is what makes this a very diverse field of study with different branches like Biostatistics, Econometrics etc.
Statistics is important in many fields including Economics and Corporate Finance; Machine Learning requires statistical knowledge to create models; Predictive Analytics requires statistical knowledge too; All of these fields heavily rely on statistics and understanding its application helps you get ahead in your career as well as understand statistics better yourself.
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