Data Science Learnings

Introduction Descriptive statistics is one of the ways to describe the data. In data science, descriptive statistics are used to provide an overview of a huge data collection. It's used to see if the data is normally distributed or not. It is presented in the form of a chart, graphs, table, frequency distribution, and so on. It provides information on summary statistics that includes Mean, Standard Error, Median, Mode, Standard Deviation, Variance, Kurtosis, Skewness, Range, Minimum, Maximum, Sum, and Count. Two major information is provided by Descriptive Statistics regarding the data: The measure of Central Tendency The measure of Dispersion Descriptive Statistics Descriptive statistics answer the following questions: What is the value that best describes the data set? How much does a data set speads from its average value? What is the smallest and largest number in a data set? What are the outliers and how it affects the dataset? Measure of Central Tendency It describes a whole

What is Hypothesis Testing? Statistics is all about data. That huge amount of data will only be useful if we are going to analyze it or take out conclusions from it. To find out such important interpretations or conclusions we use hypothesis testing. Statistics Statistical Hypothesis testing is to test the assumption (hypothesis) made and draw a conclusion about the population. This is done by testing the sample representing the whole population and based on the results obtained; the hypothesis is either rejected or accepted. Pre-requisites: DSL | E1 Statistics Steps in Hypothesis Testing The three major steps are: Making an initial assumption. We will take the initial assumption as the null hypothesis, H0. Example: We want to know whether the defendant is guilty or innocent. Thus, we take H0 as Defendant not guilty. Collecting the data. This data will not only be the data but the shreds of evidence as well. Example: Fingerprints, DNA, etc. Gathering evidence to reject/accept the hypot

Introduction Statistics is one of the popularly regarded disciplines this is particularly centered on records collection, records organization, records analysis, records interpretation and records visualization. Earlier, facts become practiced through statisticians, economists, enterprise proprietors to calculate and constitute applicable records of their field. Nowadays, facts have taken a pivotal position in diverse fields like records technology, system learning, records analyst position, enterprise intelligence analyst position, pc technology position, and plenty more. Statistics is a type of mathematical analysis that uses quantified models and representations to analyze a set of experimental data or real-world research. The fundamental benefit of statistics is that information is provided in an easy-to-understand style. Statistical & Non-Statistical Analysis Statistical analysis is used to better understand a wider population by analyzing data from a sample. Statistical analy