# Category Archives: Data Science

## Linear regression t-test: Formula, Example

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 …

## Most In-Demand Skills for Data Scientists in 2022

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 …

## Data Storytelling Explained with Examples

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 …

## 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 …

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

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 …

## Z-tests for Hypothesis testing: Formula & Examples

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? …

## One sample Z-test for proportion: Formula & Examples

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 …

## Two independent samples t-tests: Formula & Examples

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 …

## One Sample T-test: Formula & Examples

In statistics, the t-test is often used in research when the researcher wants to know if there is a significant difference between the mean of sample and the population, or whether there is a significant difference between the means of two different groups. There are two types of t-tests: the one sample t-test and the two samples t-test. As data scientists, it is important for us to understand the concepts of t-test and how to use it in our data analysis. In this blog post, we will focus on the one sample t-test and explain with formula and examples. What is one-sample T-test? One-sample T-test is a statistical hypothesis testing …

## Z-test MCQs with Answers: Interview Questions

In this blog post, you can test your knowledge about Z-test, Z-statistics and related concepts through multiple choice questions (MCQs) and answers. Getting a good understanding of Z-tests, Z-statistics and Z-distribution is of utmost importance for data scientists at large. The following are key concepts around which the MCQs are posted: Z-score or Z-statistics concepts Estimation of population mean and proportion 1-sample Z-test for mean and proportion 2-samples Z-test for mean and proportion Z-test Interview Questions Samples The following is a list of interview questions that you would want to learn: What is Z-score? Explain with an example and formula. What are different types of Z-tests? Explain with formula and …

## Z-score or Z-statistics: Concepts, Formula & Examples

Z-scores or Z-statistics represent a statistical technique of measuring the deviation of data from the mean. There are different formula used for Z-score or Z-statistics depending upon what is measured. Z-statistics is generally used with Z-test which is a hypothesis testing statistical technique. As a data scientist, it is of utmost importance to be well-versed with the z-score formula and its various applications. Having great clarity on the concept of Z-score and/or Z-statistics will help you use the correct formula for calculation in the appropriate cases. In this blog post, we will discuss the concept of Z-score, concepts, formula, and examples. Z-score / Z-statistics Concepts & Formula The Z-score formula …

## Two samples Z-test for Means: Formula & Examples

In statistics, a two-sample z-test for means is used to determine if the means of two populations are equal. This test is used when the population standard deviations are known. As data scientists, it is of utmost importance to be able to understand and conduct this test accurately. This blog post will provide a detailed explanation of the two-sample z-test for means, as well as examples to help illustrate how it is used. What is a two-sample Z-test for means? Two-sample Z-test for means is a statistical hypothesis testing technique that is used to determine if the difference between the two population means is not statistically significant. This test is …

## Reinforcement Learning Real-world examples

In this blog post, we’ll learn about some real-world / real-life examples of Reinforcement learning, one of the different approaches to machine learning where other approaches are supervised and unsupervised learning. Reinforcement learning is a type of machine learning that enables a computer system to learn how to make choices by being rewarded for its successes. This can be an extremely powerful tool for optimization and decision-making. It’s one of the most popular machine learning methods used today. Before looking into the real-world examples of Reinforcement learning, let’s quickly understand what is reinforcement learning. Introduction to Reinforcement Learning (RL) Reinforcement learning is an approach to machine learning in which the agents …

## Different Success / Evaluation Metrics for AI / ML Products

In this post, you will learn about some of the common success metrics that can be used for measuring the success of AI / ML (machine learning) / DS (data science) initiatives / projects / products. If you are one of the AI / ML stakeholders including product managers, you would want to get hold of these metrics in order to apply right metrics in right business use cases. Business leaders do want to know and maximise the return on investments (ROI) from AI / ML investments. Here is the list of success metrics for AI / DS / ML initiatives: Business value metrics / key performance indicators (KPIs): Business …

## Degree of Freedom in Statistics: Meaning & Examples

The degree of freedom (DOF) is a term that statisticians use to describe the degree of independence in statistical data. A degree of freedom can be thought of as the number of variables that are free to vary. When you have one degree, there is one variable that can be freely changed without affecting the value for any other variable. As a data scientist, it is important to understand the concept of degree of freedom, as it can help you better understand your data and how to analyze it. In this blog post, we’ll explore the degree of freedom concept in statistics and provide some examples. What is degree of …

## Null and Alternate hypothesis: Definition & Example

Hypothesis testing is a technique used to determine whether an assumption about the population is true. Null hypothesis and alternate hypothesis are two types of hypotheses that you may hear when conducting this type of test. Having a good understanding about null and alternate hypothesis will help you better design good hypothesis tests and understand their results in a nice manner. It is very important for data scientists to be able to distinguish between null and alternate hypothesis and design hypothesis tests. In this blog post, we will understand the definition and examples of the null and alternate hypothesis. What are different scenarios for hypothesis testing? The following are two …