Tag Archives: Data Science

Difference between Data Science & Data Analytics

data science vs data analytics

What’s the difference between data science and data analytics? Many people use these terms interchangeably, but there is a big distinction between the two fields. Data science is more focused on understanding and deriving insights from data, while data analytics is more focused on using pre-determined algorithms to make decisions or take action. In this blog post, we’ll explore the differences between data science and data analytics in greater detail, with examples of each. The following are key topics in relation to the difference between data science and data analytics: Different forms / purposes Different techniques Different Skillsets Different tools Different forms: Data Science & Data analytics Data science is …

Continue reading

Posted in Data analytics, Data Science. Tagged with , .

Business Analytics Team Structure: Roles/ Responsibilities

business analytics value chain

Business analytics is a business function that has been around for years, but it’s only recently gained traction as one of the most important business functions. Organizations are now realizing how business analytics can help them increase revenue and improve business operations. But before you bring on a business analytics team, you need to determine if your company needs full-time or part-time team members or both. It might seem logical to hire full-time staff members just because they’re in demand, but this isn’t always necessary. If your business operates without any external data sets and doesn’t have complex reporting and advanced analytics needs then it may be more cost-effective to …

Continue reading

Posted in Data analytics, Data Science, Machine Learning, Product Management. Tagged with , , .

Linear Regression Interview Questions for Data Scientists

linear regression questions

This page lists down 40 regression (linear/univariate, multiple/multilinear/multivariate) interview questions  (in form of objective questions) which may prove to be helpful for Data Scientists / Machine Learning enthusiasts. Those appearing for interviews for machine learning/data scientist freshers/intern/beginners positions would also find these questions very helpful and handy enough to quickly brush up / check your knowledge and prepare accordingly. Practice Tests on Regression Analysis These interview questions are split into four different practice tests with questions and answers which can be found on following page: Linear, Multiple regression interview questions and answers – Set 1 Linear, Multiple regression interview questions and answers – Set 2 Linear, Multiple regression interview questions …

Continue reading

Posted in Data Science, Interview questions, Machine Learning. Tagged with , , .

Ordinary Least Squares Method: Concepts & Examples

ordinary least squares method

Ordinary least squares (OLS) is a linear regression technique used to find the best-fitting line for a set of data points. It is a popular method because it is easy to use and produces decent results. In this blog post, we will discuss the basics of OLS and provide some examples to help you understand how it works. As data scientists, it is very important to learn the concepts of OLS before using it in the regression model. What is the ordinary least squares (OLS) method? The ordinary least squares (OLS) method can be defined as a linear regression technique that is used to estimate the unknown parameters in a …

Continue reading

Posted in Data Science, Machine Learning. Tagged with , .

R-squared & Adjusted R-squared: Differences, Examples

r-squared vs adjusted r-squared

There are two measures of the strength of linear regression models: adjusted r-squared and r-squared. While they are both important, they measure different aspects of model fit. In this blog post, we will discuss the differences between adjusted r-squared and r-squared, as well as provide some examples to help illustrate their meanings. As a data scientist, it is of utmost importance to understand the differences between adjusted r-squared and r-squared in order to select the most appropriate linear regression model out of different regression models. What is R-squared? R-squared is a measure of what proportion of the variance in the value of the dependent or response variable is explained by …

Continue reading

Posted in Data Science, Machine Learning. Tagged with , .

R-squared, R2 in Linear Regression: Concepts, Examples

R-squared formula linear regression model

In linear regression, R-squared (R2) is a measure of how close the data points are to the fitted line. It is also known as the coefficient of determination. In this post, you will learn about the concept of R-Squared in relation to assessing the performance of multilinear regression machine learning model with the help of some real-world examples explained in a simple manner. Before doing a deep dive, you may want to access some of the following blog posts in relation to concepts of linear regression: Linear regression explained with real-world examples Linear regression hypothesis testing: concepts, examples Linear regression t-test: formula, examples Interpreting f-statistics in linear regression: formula, examples What …

Continue reading

Posted in AI, Data Science, Machine Learning. Tagged with , , .

Interpreting f-statistics in linear regression: Formula, Examples

linear regression R-squared concepts

In this blog post, we will take a look at the concepts and formula of f-statistics in linear regression models and understand with the help of examples. F-test and F-statistics are very important concepts to understand if you want to be able to properly interpret the summary results of training linear regression machine learning models. We will start by discussing the importance of f-statistics in building linear regression models and understand how they are calculated based on the formula of f-statistics. We will, then, understand the concept with some real-world examples. As data scientists, it is very important to understand both the f-statistics and t-statistics and how they help in …

Continue reading

Posted in Data Science, Machine Learning, statistics. Tagged with , , .

One-way ANOVA test: Concepts, Formula & Examples

One way ANOVA table example

An ANalysis Of VAriance (ANOVA) test, also known as a one-way ANOVA test, is a hypothesis test used to determine whether there is a significant difference between the means of three or more groups. In other words, it can be used to answer the question of whether the averages of three or more populations are equal. If there is a need to compare the means of two populations (independent or pairwise), t-tests can be used. One-way ANOVA test or single-factor Anova test is often used in experiments with only one independent variable. As data scientists, it is of utmost importance to understand the ANOVA test as it is an important …

Continue reading

Posted in Data Science, statistics. Tagged with , .

Linear regression t-test: Formula, Example

Linear regression line slope 0

In linear regression, the t-test is a statistical hypothesis testing technique that is used to test the linearity of the relationship between the response variable and different predictor variables. In other words, it is used to determine whether or not there is a linear correlation between the response and predictor variables. The t-test helps to determine if this linear relationship is statistically significant. As data scientists, it is of utmost importance to understand why t-statistics is used to determine the coefficients of the linear regression model. In this blog, we will discuss linear regression and t-test and related formulas and examples. What is linear regression? Linear regression is defined as …

Continue reading

Posted in Data Science, statistics. Tagged with , .

Most In-Demand Skills for Data Scientists in 2022

most in-demand data science skills

The data science field is growing rapidly and data scientists are in high demand. If you want to enter this field, it’s important that you have the right skills. In this blog post, we’ll explore the most in-demand skills of data scientist employers are looking for the most and how to develop these skills so that you can find a job as a data scientist. Strong knowledge and experience with Statistical/ML methods: Strong familiarity with statistical concepts such as probability distributions (e.g., normal distribution), concepts of hypothesis testing, regression analysis, etc is essential for becoming a great data scientist. One of the most important ask for a data scientist is …

Continue reading

Posted in Career Planning, Data Science, Interview questions. Tagged with , .

Data Storytelling Explained with Examples

MS Dhoni - Former Captain of Indian Cricket Team

Have you ever told a story to someone, but they just didn’t seem to understand it? They might have been confused about the plot or why the characters acted in certain ways. If this has happened to you before, then you are not alone. Many people struggle with data storytelling because they do not know how to communicate their data effectively.  In this blog post, you will learn about some of the key concepts in relation to data storytelling and why data scientists / data analyst should acquire this skill. Data storytelling is one of the key skills which data scientists would need to acquire in order to do a …

Continue reading

Posted in Data Science. Tagged with .

When to Use Z-test vs T-test: Differences, Examples

When it comes to statistical tests, z-test and t-test are two of the most commonly used. But what is the difference between z-test and t-test? And when should you use Z-test vs T-test? In this blog post, we will answer all these questions and more! We will start by explaining the difference between z-test and t-test in terms of their formulas. Then we will go over some examples so that you can see how each test is used in practice. As data scientists, it is important to understand the difference between z-test and t-test so that you can choose the right test for your data. Let’s get started! Difference between …

Continue reading

Posted in Data Science, statistics. Tagged with , .

One-sample Z-test for Means: Formula & Examples

z-test one-tailed or two-tailed tests

One sample Z-test for means is one of the statistical techniques used for testing hypothesis related to whether the sample belongs to a population. As a data scientist, you must get a good understanding of the z-test and its applications to test the hypothesis for your statistical models. In this blog post, we will discuss the one sample z-test for means and its concepts with an example. You may want to check my post on hypothesis testing titled – Hypothesis testing explained with examples What is One-sample Z-test for Means? Z-test is usually referred to as a 1-sample Z-test for means that is used to test the hypothesis about the …

Continue reading

Posted in Data Science, statistics. Tagged with , .

Z-tests for Hypothesis testing: Formula & Examples

Different types of Z-test - One sample and two samples

Z-tests are statistical hypothesis testing techniques that are used to determine whether the null hypothesis relating to comparing sample means or proportions with that of population at a given significance level can be rejected or otherwise based on the z-statistics or z-score. As a data scientist, you must get a good understanding of the z-tests and its applications to test the hypothesis for your statistical models. In this blog post, we will discuss an overview of different types of z-tests and related concepts with the help of examples. You may want to check my post on hypothesis testing titled – Hypothesis testing explained with examples What are Z-tests & Z-statistics? …

Continue reading

Posted in Data Science, statistics. Tagged with , .

One sample Z-test for proportion: Formula & Examples

one sample proportion z-test

One proportion z-test or one-sample Z-test for proportion is one of the most popular statistical hypothesis tests dealing with one sample proportion. It is used to determine whether or not a hypothesized mean difference between the sample and the population can be rejected by drawing conclusions from sample data. As a data scientist, it is important to be proficient in this type of Z-test and understand how it works. In this blog post, we will learn about how one proportion z-test works with the help of formula and examples. What is one sample Z-test for proportion? A one proportion Z-test is a hypothesis testing technique which is used for testing …

Continue reading

Posted in Data Science, statistics. Tagged with , .

Two independent samples t-tests: Formula & Examples

pooled t-statistics

In statistics, the two sample t-test for independent samples is a type of hypothesis test that can be used to determine whether the means of two populations are statistically different given the two samples are independent and have normal distributions. As data scientists, it is important to understand how to use the two sample t-test for independent samples so that you can correctly analyze your data. In this blog post, we will discuss the two sample t-test for independent samples in detail, including the formula and examples. What is two-sample T-test? A two-sample T-test is defined as statistical hypothesis testing technique in which two independent samples are compared to determine …

Continue reading

Posted in Data Science, statistics. Tagged with , .