Tag Archives: statistics

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 …

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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? …

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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 …

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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 …

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One Sample T-test: Formula & Examples

one sample t-test formula and 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 …

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Z-test MCQs with Answers: Interview Questions

Z-test MCQs with questions and answers

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 …

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

z-scores formula concepts and 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 …

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Two samples Z-test for Means: Formula & Examples

two sample z-test for means formula and 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 …

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Z-Score Explained with Ronaldo / Robert Example

In this post, you will learn the concepts of Z-Score with the help from examples including Christiano Ronaldo and Robert Lewandowski. You will learn about how to compare and call out whose performance was better in Champions League 2019-2020. As a data scientist, it will be extremely important to learn the concepts of Z-Scores, also called as Standard scores, as it would help you evaluate / compare a particular data set with past data set. Before getting into the example of Z-scores, lets understand some concepts of Z-scores. What’s Z-Score or Z-statistics? Z-score can be defined as number of standard deviations the data point is above or below the mean …

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Degree of Freedom in Statistics: Meaning & Examples

degrees of freedom in statistics - meaning and 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 …

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Level of Significance & Hypothesis Testing

level of significance and hypothesis testing

In hypothesis testing, the level of significance is a measure of how confident you can be about rejecting the null hypothesis. This blog post will explore what hypothesis testing is and why understanding significance levels are important for your data science projects. In addition, you will also get to test your knowledge of level of significance towards the end of the blog with the help of quiz. These questions can help you test your understanding and prepare for data science / statistics interviews. Before we look into what level of significance is, let’s quickly understand what is hypothesis testing. What is Hypothesis testing and how is it related to significance …

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P-Value & Hypothesis Testing: Examples

P-value explained with examples

Many describe p-value as the probability that the null hypothesis holds good. That is an incorrect definition. The concept of p-value is understood differently by different people and is considered as one of the most used & abused concepts in statistics, mostly in relation to hypothesis testing. In this blog post, you will learn the P-VALUE concepts with multiple different examples. It is extremely important to get a good understanding of P-value if you are starting to learn data science/machine learning as the concepts of P-value are key to hypothesis testing. Before getting into the description of p-value, let’s quickly go through the hypothesis testing concepts to get a good …

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Type I & Type II Errors in Hypothesis Testing: Examples

This article describes Type I and Type II errors made due to incorrect evaluation of the outcome of hypothesis testing, based on a couple of examples such as the person comitting a crime, the house on fire, and Covid-19. You may want to note that it is key to understand type I and type II errors as these concepts will show up when we are evaluating a hypothesis such as those related to machine learning algorithms (linear regression, logistic regression, etc). For example, in the case of linear regression models, the significance value is compared with the p-value and, the null hypothesis that the parameter/coefficient is equal to zero is …

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Survival Analysis Modeling for Customer Churn

survival analysis customer churn

Customer churn is a prevalent problem for many businesses. It can happen in several different ways, such as when customers stop using the product, or when they leave because of an issue with customer service. This blog post will explore survival analysis modeling and what it can do to help you better understand customer churn problems. First, we will discuss survival analysis itself and why it is beneficial for analyzing customer behavior. Then we will show some examples on how survival analysis has been used to analyze customer churn problems. As data scientists, it will be good to familiarize ourselves with survival analysis, as it is a popular modeling technique …

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Binomial Distribution Explained with Examples

binomial experiment coin tossing 100 experiments 50 trials

The binomial distribution is a probability distribution that applies to binomial experiments. It’s the number of successes in a specific number of tries. The binomial distribution may be imagined as the probability distribution of a number of heads that appear on a coin flip in a specific experiment comprising of a fixed number of coin flips. In this blog post, we will learn binomial distribution with the help of examples. If you are an aspiring data scientist looking forward to learning/understand the binomial distribution in a better manner, this post might be very helpful. What is a Binomial Distribution? The binomial distribution is a discrete probability distribution that represents the probabilities of binomial random …

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Poisson Distribution Explained with Python Examples

Poisson distribution is a probability distribution that can be used to model the number of events in a fixed interval. It is often referred to as “random poisson process” or “poisson process”. The poisson distribution describes how many occurrences of an event occur within a given time frame, for example, how many customers visit your store or restaurant every hour. In this post, you will learn about the concepts of Poisson probability distribution with Python examples. As a data scientist, you must get a good understanding of the concepts of probability distributions including normal, binomial, Poisson etc.  What is Poisson distribution? Poisson distribution is the discrete probability distribution which represents the …

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