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What is Data Science

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Learn Data Science - Introduction Introduction to Data Science History The field of data science has its roots in statistics and computer science and has evolved to encompass a wide range of techniques and tools for understanding and making predictions from data. The history of data science can be traced back to the early days of statistics when researchers first began using data to make inferences and predictions about the world. In the 1960s and 1970s, the advent of computers and the development of new algorithms and statistical methods led to a growth in the use of data to answer scientific and business questions. The term "data science" was first coined in the early 1960s by John W. Tukey, a statistician and computer scientist . In recent years, the field of data science has exploded in popularity, thanks in part to the increasing availability of data from a wide range of sources, as well as advances in computational power and machine learning. Today, data science is us...
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What is the Probability and Statistics

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Undrstand the Probability and Statistics in Data Science Contents of P robability and Statistics Probability Basics Random Variables and Probability Distributions Statistical Inference (Hypothesis Testing, Confidence Intervals) Regression Analysis Probability Basics Solution :  Sample Space = {H, T} (where H stands for Head and T stands for Tail) Solution :  The sample space is {1, 2, 3, 4, 5, 6}. Each outcome is equally likely, so the probability distribution is: Hypothesis testing involves making a decision about a population parameter based on sample data. The null hypothesis (H0) is the hypothesis that there is no significant difference between a set of population parameters and a set of observed sample data. The alternative hypothesis (Ha) is the hypothesis that there is a significant difference between a set of population parameters and a set of observed sample data. The hypothesis testing process involves the following steps: Formulate the null and al...
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What is Data Collection and Cleaning

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Know the Data Collection Methods and Cleaning Techniques Contents data collection and cleaning: Data Collection Methods Data Quality Assessment Data Cleaning Techniques Outlier Detection Data Collection Methods Data Collection is the process of gathering relevant data from various sources that can be used for analysis. The two primary categories of data collection techniques are:      Primary Data Collection :  Primary data collection involves collecting data directly from the source for a specific purpose. This method involves the use of surveys, interviews, observations, and experiments to collect data.      Secondary Data Collection :  Secondary data collection involves the use of data that has already been collected and is available for public use. This method involves the use of data obtained from books, journals, newspapers, and government publications. Data Quality Assessment Data Quality Assessment is the process of evaluating th...
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