10 Statistical Functions in Excel every Analytics Professional Should Know

Analytics Vidhya

Overview Microsoft Excel is an excellent tool for learning and executing statistical functions Here are 12 statistical functions in Excel that you should master. The post 10 Statistical Functions in Excel every Analytics Professional Should Know appeared first on Analytics Vidhya.

All about Statistical Modeling

Analytics Vidhya

What is a Statistical Model? The post All about Statistical Modeling appeared first on Analytics Vidhya. Beginner Statistics blogathon Hypothesis Testing statistical modelingThis article was published as a part of the Data Science Blogathon.

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Statistics for Beginners: Power of “Power Analysis”

Analytics Vidhya

Introduction How much data is enough to state statistical significance? The post Statistics for Beginners: Power of “Power Analysis” appeared first on Analytics Vidhya. Beginner Python Statistics blogathon Hypothesis Testing power analysis

Essential Statistical Concepts for Data Cognizance

Analytics Vidhya

The post Essential Statistical Concepts for Data Cognizance appeared first on Analytics Vidhya. Beginner Python Statistics Structured Data blogathon statistical conceptsArticleVideos This article was published as a part of the Data Science Blogathon.

Upgrading Data Security in a Crisis

Speaker: M.K. Palmore, VP Field CSO (Americas), Palo Alto Networks

In most cases, the COVID-19 crisis has sped up the desire to engage in digital transformation for medium-to-large scale enterprises. Roadmaps are rarely implemented without challenges. During this session, MK Palmore, the Field CSO (Americas) for Palo Alto Networks and a former public-sector executive, will walk through the difficulties of crisis planning execution in the midst of an organization's digital changes. He will use a combination of industry insights through statistical observations and direct customer feedback to emphasize the importance of adopting new technologies to battle an ever changing threat landscape.

Inferential Statistics – Sampling Distribution, Central Limit Theorem and Confidence Interval

Analytics Vidhya

Introduction The field of statistics consists of methods for describing and. The post Inferential Statistics – Sampling Distribution, Central Limit Theorem and Confidence Interval appeared first on Analytics Vidhya. Beginner Statistics Technique blogathon Inferential Statistics

Top 5 Statistical Concepts Every Data Scientist Should Know in 2020!

Analytics Vidhya

Must know Statistical concepts for the Data Science journey The main goal. The post Top 5 Statistical Concepts Every Data Scientist Should Know in 2020! Beginner Listicle Statistics accuracy Dimensionality Reduction Hypothesis Testing oversampling probability distribution undersamplin

Statistics for Analytics and Data Science: Hypothesis Testing and Z-Test vs. T-Test

Analytics Vidhya

Overview Hypothesis testing is a key concept in statistics, analytics, and data science Learn how hypothesis testing works, the difference between Z-test and t-test, The post Statistics for Analytics and Data Science: Hypothesis Testing and Z-Test vs. T-Test appeared first on Analytics Vidhya. Beginner Python Statistics Technique hypothesis building Hypothesis Testing statisticial tests statistics statistics for data science t-test z test

Statistics for Data Science: What is Skewness and Why is it Important?

Analytics Vidhya

Overview Skewness is a key statistics concept you must know in the data science and analytics fields Learn what is skewness, the formula for. The post Statistics for Data Science: What is Skewness and Why is it Important? Beginner Statistics Negative Skewness Normal Distribution outliers Positive Skewness Skewness statisticsappeared first on Analytics Vidhya.

Interpreting P-Value and R Squared Score on Real-Time Data – Statistical Data Exploration

Analytics Vidhya

The post Interpreting P-Value and R Squared Score on Real-Time Data – Statistical Data Exploration appeared first on Analytics Vidhya. Beginner Data Exploration Data Visualization Python Statistics Structured Data Tableau blogathon EDA Statistical Data Exploration

Run a Business, Not a Backlog

Speaker: John Mecke, Managing Director of DevelopmentCorporate, Jon Gatrell, Principal Partner at Market Driven Business

Numerical literacy is a key skill for effective product managers. The ability to express concepts in numerical, financial, or statistical terms is a critical but often overlooked discipline. Product managers need to be as competent in these domains as they are in customer problems and pain points.

Statistics for Data Science: What is Normal Distribution?

Analytics Vidhya

The post Statistics for Data Science: What is Normal Distribution? Beginner Machine Learning Maths Probability Python Statistics data science Density Plot Histograms Kurtosis Normal Distribution normalization Probability density function SkewnessIntroduction to the Normal Distribution Have you heard of the bell curve? It tends to be among the most discussed water-cooler topics among people. appeared first on Analytics Vidhya.

What is Bootstrap Sampling in Statistics and Machine Learning?

Analytics Vidhya

The post What is Bootstrap Sampling in Statistics and Machine Learning? Beginner Python Statistics Technique bootstrap sampling bootstrap sampling machine learning Bootstrapping sample SamplingIntroduction Have you ever struggled to improve your rank in a machine learning hackathon on DataHack or Kaggle? You’ve tried all your favorite hacks. appeared first on Analytics Vidhya.

Top 7 Statistical Concepts a Data Science Professional Must Know

DataFloq

In data science, statistics help predict events, trends, or any happenings. Simply said, statistics acts like it is the soul of data science. Sampling in StatisticsSampling is one of the major statistical procedures used for individual observation.

Introduction to ANOVA for Statistics and Data Science (with COVID-19 Case Study using Python)

Analytics Vidhya

The post Introduction to ANOVA for Statistics and Data Science (with COVID-19 Case Study using Python) appeared first on Analytics Vidhya. Beginner Healthcare Python Statistics Structured Data Technique Anova ANOVA COVID ANOVA statistics statsticsIntroduction “A fact is a simple statement that everyone believes. It’s innocent, unless found guilty. A Hypothesis is a novel suggestion that no one.

Quantifying a Culture of Innovation

Statistics for Data Science: Introduction to t-test and its Different Types (with Implementation in R)

Analytics Vidhya

Introduction “You can’t prove a hypothesis; you can only improve or disprove it.” – Christopher Monckton Every day we find ourselves testing new ideas, The post Statistics for Data Science: Introduction to t-test and its Different Types (with Implementation in R) appeared first on Analytics Vidhya. R Statistics Hypothesis Testing Inferential Statistics statistics t-test

Statistics 101: Introduction to the Central Limit Theorem (with implementation in R)

Analytics Vidhya

Introduction What is one of the most important and core concepts of statistics that enables us to do predictive modeling, and yet it often. The post Statistics 101: Introduction to the Central Limit Theorem (with implementation in R) appeared first on Analytics Vidhya. Probability R Statistics central limit theorem Normal Distribution probability statistics

A Quick Guide to Descriptive Statistical Analysis – The First Step in Exploring your Data

Analytics Vidhya

Introduction The first step in a data science project is to summarize, The post A Quick Guide to Descriptive Statistical Analysis – The First Step in Exploring your Data appeared first on Analytics Vidhya. This article was published as a part of the Data Science Blogathon.

Boxing and Unboxing of Statistical Models with Gaussian Learning

Analytics Vidhya

The post Boxing and Unboxing of Statistical Models with Gaussian Learning appeared first on Analytics Vidhya. This article was published as a part of the Data Science Blogathon. Values offer Focus amidst the Chaos” – Glenn C. Stewart Introduction Joseph.

Statistical Modelling vs Machine Learning

KDnuggets

At times it may seem Machine Learning can be done these days without a sound statistical background but those people are not really understanding the different nuances. 2019 Aug Opinions Uncategorized Advice Data Science Machine Learning StatisticsCode written to make it easier does not negate the need for an in-depth understanding of the problem.

5 Statistical Traps Data Scientists Should Avoid

KDnuggets

Here are five statistical fallacies — data traps — which data scientists should be aware of and definitely avoid. 2019 Oct Tutorials, Overviews Bias Fallacies Simpson's Paradox Statistics

Data Mining Vital Statistics Yields Fascinating Societal Insights

Smart Data Collective

Vital statistics can be great for identifying some of the biggest social trends influencing the country. Vital statistics is a form of data you may not have realized held an incredible amount of significance in society. You may also be wondering what exactly vital statistics are.

Descriptive Statistics in Python for Understanding Your Machine Learning Data

DataFloq

Statistics has its own significance in data science, but it’s not the only thing which data scientists have to deal with. Statistics are of two kinds – Bayesian and Classical. When people start talking about statistics, they are most often talking about classical statistics; but understanding both is beneficial. The method SCD has its grounding in matrix math and hardly need classical statistics. Traditional Methods for Statistics.

Statistical Methods and Machine Learning Algorithms for Data Scientists

DataFloq

There are statistical methods and machine learning algorithms for data scientists which help them provide training to computers to find information with minimum programming. The traditional software has a predictive and statistical analysis that helps in finding the patterns and getting the hidden information based on the perceived data. . The mining of useful data from big data sets is done by professional big data analysts.

Top 5 Statistical Techniques in Python

Sisense

A data scientist must be skilled in many arts: math and statistics, computer science, and domain knowledge. Statistics and programming go hand in hand. In this article, we will explain how to execute five statistical techniques using Python. Importance of statistical techniques.

How Machine Learning Models Fail to Deliver in Real-World Scenarios

Analytics Vidhya

Beginner Data Science Statistics Bayesian Statistics machine learning Machine Learning Models machine learning real world statisticsThis article was published as a part of the Data Science Blogathon. Introduction Yesterday, my brother broke an antique at home. I began to.

Basic Statistics Concepts for Data Scientists

Dataiku

Statistics can be tremendously beneficial for data scientists, both those that are new to the field and those who have been practicing for a number of years. Statistics, or the practice of using mathematics to analyze, interpret, and present data, allows us to leverage data — a critical element to any impactful machine learning model — in a deeper, more concrete way. In this blog post, we will cover three basic statistics concepts that will come in handy for any data scientist.

Machine Learning Vs. Statistical Learning

Perficient Data & Analytics

Most of the time as a data scientist I get asked the question, what is the difference between Machine Learning and Statistical Learning? To become a data scientist, you are quired to develop knowledge in multiple subjects such as Statistics, Programming, SQL, Linear Algebra and have the domain expertise. Hopefully, you will start your journey with Statistics, and most of the data scientists believe that this is the foundation in Data Science and I cannot disagree with them.

Descriptive Statistics and Data Visualization

TDAN

Turn Your Statistics Into Something More Interesting Data is quickly becoming a defining thing in the business world. A company which doesn’t pay attention to proper statistics can be at a serious disadvantage from companies who do, especially companies that […]. It is the lifeblood of every company decision and thus, it defines what companies do.

A Data Scientist’s Guide to 8 Types of Sampling Techniques

Analytics Vidhya

Overview Sampling is a popular statistical concept – learn how it works in this article We will also talk about eight different types of. Statistics Descriptive statistics different kinds of sampling Inferential Statistics random sampling Sampling statisticsThe post A Data Scientist’s Guide to 8 Types of Sampling Techniques appeared first on Analytics Vidhya.

What’s the difference between analytics and statistics?

KDnuggets

2019 Sep Opinions Analytics Explained StatisticsFrom asking the best questions about data to answering those questions with certainty, understanding the value of these two seemingly different professions is clarified when you see how they should work together.

Data Scientists: Level Up Your Projects With These Statistics Concepts

Dataiku

According to LinkedIn’s Emerging Jobs on the Rise report for 2021 , data scientist roles are still growing steadily, showing an average annual growth of 35%.

An Introduction to the Powerful Bayes’ Theorem for Data Science Professionals

Analytics Vidhya

Overview Bayes’ Theorem is one of the most powerful concepts in statistics – a must-know for data science professionals Get acquainted with Bayes’ Theorem, The post An Introduction to the Powerful Bayes’ Theorem for Data Science Professionals appeared first on Analytics Vidhya. Probability Statistics bayes theorem Bayesian Statistics conditional probability data science probability statistics statistics for data science

Statistics Changing Marketing Strategies

TDAN

When it comes to marketing, business owners need to be fast in adjusting their strategies to fit the continuous advancement in technologies. Today, nearly everyone has a mobile phone or another smart mobile device with them at all times. As the trend of doing everything over a mobile device grows, including tasks such as shopping […].

What is the Chi-Square Test and How Does it Work? An Intuitive Explanation with R Code

Analytics Vidhya

R Statistics Technique chi-square test statistical tests statistics statistics for data science statistics in ROverview What is the chi-square test? How does it work? Learn about the different types of Chi-Square tests and where and when you should. The post What is the Chi-Square Test and How Does it Work? An Intuitive Explanation with R Code appeared first on Analytics Vidhya.

Hypothesis Testing: A Way to Prove Your Claim Using p-value

Analytics Vidhya

Introduction One of the most basic concepts in statistics is hypothesis testing. Beginner Business Analytics Statistics Technique confidence interval confidence level Hypothesis Testing one tailed test p-value statistics statistics two tailed testNot just in Data Science, Hypothesis testing is important in every field. The post Hypothesis Testing: A Way to Prove Your Claim Using p-value appeared first on Analytics Vidhya.

A learning guide to IBM SPSS Statistics: Get the most out of your statistical analysis

IBM Big Data Hub

IBM SPSS Statistics provides a powerful suite of data analytics tools which allows you to quickly dig into your data with a simple point and click interface and enables you to extract critical insights with ease. Organizations of all kinds have relied on IBM SPSS Statistics for decades to help solve a wide range of business and research problems.

What is Multicollinearity? Here’s Everything You Need to Know

Analytics Vidhya

Beginner Python Regression Statistics Structured Data Technique linear regression multicollinearity multicollinearity machine learning multicollinearity statistics python statistics VIFIntroduction Multicollinearity might be a handful to pronounce but it’s a topic you should be aware of in the machine learning field. The post What is Multicollinearity? Here’s Everything You Need to Know appeared first on Analytics Vidhya.

Machine Learning 101: Decision Tree Algorithm for Classification

Analytics Vidhya

Beginner Statistics blogathon decision tree algorithmArticleVideo Book This article was published as a part of the Data Science Blogathon.