In this note series, we had already covered a few of the different tools and techniques to measure the central tendency of data. Moreover, in the current note, we will understand the Mode and how it measures the central tendency of data. Mode in Descriptive Statistics Mode tells which observation has occurred or recorded a …
Descriptive Statistics – Measures of Central Tendency – Mode Read More »
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In the previous note, we have seen how to measure the central tendency using the Median. Mainly, it is a value in a frequency distribution that divides the total frequency into two equal parts. Now the question is why only two parts, why not three or four or more parts. In this section, we will try …
Descriptive Statistics – Measures of Central Tendency – Quantiles Read More »
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Median is one of the techniques to measure the central tendency of data. It divides the observations into two equal parts. At least fifty percent of the values are greater than or equal to the median, and the remaining values are less than or equal to the median. Median in Descriptive Statistics In simple words, …
Descriptive Statistics – Measures of Central Tendency – Median Read More »
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Mean is one of the techniques to measure the central tendency of data. Data is often described as ungrouped and grouped. The ungrouped data is data given as individual data points or, in other words, we can say, observations are collected from the discrete variable. Whereas the grouped data is data given in intervals, these data …
Descriptive Statistics – Measures of Central Tendency – Mean Read More »
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This note will cover Python Tuples and understand what operations we can perform on the tuples. And after completion of this note, we will be able to use Python Tuples smoothly. Python Tuples A tuple is very much similar to a list. However, one of the significant differences between Tuple and List is that List …
Python Fundamentals – Tuples Read More »
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A list is a generic sequence data structure in python consisting of an ordered collection of objects. The objects in a list are also known as elements or components. The elements or components of a list need not be the same type. It is quite possible that a list can consist of a numeric array, …
Python Fundamentals – Lists Read More »
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The datascience package was written for use in Berkeley’s Data8 course, and it contains useful functionality for investigating and graphically display of data. The most important functionality in the package is a Table, and its structure is used to represent columns of data. We will learn the Table structure and its functionalities. Along with this, we …
Data Science – Tables Read More »
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In the previous note, we have learned about data science and the different core activities to extract meaningful information from the data. In this note, we will learn how to read, understand and make relationships among the variables. An important part of a data scientist is to explain what they see in their data. It …
Data Science – Cause and Effect Read More »
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For doing any project work, we need to install many different packages. We usually see the problem of package conflicts or existing projects stops working because during the new project work setup, mistakenly, we update the existing old packages. Creating the Python Virtual Environment for individual project work is always beneficial to avoid all these …
Data Science – Setting up a virtual environment for Jupyter Notebook Read More »
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This note series will study the following exciting courses named Data 8 and COMPSCI C8 and prepare notes for future references. Mainly, we will see how computing and statistics are merging and interacting in new ways. This course has emphasized computational and programming skills along with inferential thinking. Data Science It is about taking large datasets …
Data Science – Introduction Read More »
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