BUSINESS ADMINISTRATION
BUSINESS ANALYTICS
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Question
[CLICK ON ANY CHOICE TO KNOW THE RIGHT ANSWER]
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Discover data anomalies and errors
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Ascertain symmetry and skewness
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Comes from your traditional relational database system
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Is any set of characters that is gathered and translated for some purpose, usually analysis.
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Identify possible outlier
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Detailed explanation-1: -Why is exploratory data analysis important in data science? The main purpose of EDA is to help look at data before making any assumptions. It can help identify obvious errors, as well as better understand patterns within the data, detect outliers or anomalous events, find interesting relations among the variables.
Detailed explanation-2: -The chapter on Exploratory Data Analysis (EDA) discusses assumptions and summarization of data in detail. Examination of the data for unusual observations that are far removed from the mass of data. These points are often referred to as outliers.
Detailed explanation-3: -Explanation: EDA is used to summarize main characteristic of data.
Detailed explanation-4: -Data collection is an essential part of exploratory data analysis. It refers to the process of finding and loading data into our system.
Detailed explanation-5: -There are different approaches such as replacing the outlier with the mean value, or median value or in some cases dropping the observation with the suspected outlier so as to avoid any bias in them. We tend to delete the outlier if they are due to data entry errors caused due to human error, data processing errors.