Tag Archives: statistics
Statistics – Random Variables, Types & Python Examples
Random variables are one of the most important concepts in statistics. In this blog post, we will discuss what they are, their different types, and how they are related to the probability distribution. We will also provide examples so that you can better understand this concept. As a data scientist, it is of utmost importance that you have a strong understanding of random variables and how to work with them. What is a random variable and what are some examples? A random variable is a variable that can take on random values. The key difference between a variable and a random variable is that the value of the random variable …
Two sample Z-test for Proportions: Formula & Examples
In statistics, a two-sample z-test for proportions is a method used to determine whether two samples are drawn from the same population. This test is used when the population proportion is unknown and there is not enough information to use the chi-squared distribution. The test uses the standard normal distribution to calculate the test statistic. As data scientists, it is important to know how to conduct this test in order to determine whether two proportions are equal. In this blog post, we will discuss the formula and examples of the two-proportion Z-test. What is two proportion Z-test? A two-proportion Z-test is a statistical hypothesis test used to determine whether two …
Linear regression hypothesis testing: Concepts, Examples
In relation to machine learning, linear regression is defined as a predictive modeling technique that allows us to build a model which can help predict continuous response variables as a function of a linear combination of explanatory or predictor variables. While training linear regression models, we need to rely on hypothesis testing in relation to determining the relationship between the response and predictor variables. In the case of the linear regression model, two types of hypothesis testing are done. They are T-tests and F-tests. In other words, there are two types of statistics that are used to assess whether linear regression models exist representing response and predictor variables. They are …
Interpreting f-statistics in linear regression: Formula, Examples
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 …
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 …
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 …
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 …
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 …
Level of Significance & 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 …
P-Value & Hypothesis Testing: 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 …
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 …
