ANCOVA (analysis of covariance) is a useful statistical method because it enables the inclusion of covariates in the analysis, which may assist adjust for auxiliary variables and increase the precision of group comparisons. These additional factors, or covariates, may be incorporated into the study using ANCOVA. In order to be sure that any observed differences between the groups are caused by the therapy or intervention under study and not by unrelated factors, ANCOVA can be used to adjust for the impact of the covariates on the group means. This can make the comparisons between the groups more accurate and give ... Read More

Obtaining a p−value from a z−score is a typical statistical procedure. The number of standard deviations a value is from the mean of a normal distribution is expressed as a z−score, sometimes referred to as a standard score. The z-score can be used to assess the probability that a specific value will appear in a normal distribution. The probability of getting a test statistic at least as severe as the one that was observed is the p-value, assuming that the null hypothesis is true. Because the z−score is typically the test statistic, determining the p-value from the z−score allows one ... Read More

Studentized residuals are typically used in regression analysis to identify potential outliers in the data. An outlier is a point that is significantly different from the overall trend of the data, and it can have a significant influence on the fitted model. By identifying and analyzing outliers, you can better understand the underlying patterns in your data and improve the accuracy of your model. In this post, we will be closely looking at Studentized Residuals and how you can implement it in python. What are Studentized Residuals? The term "studentized residuals" refers to a particular class of residuals that have ... Read More

Dunn's test is a statistical technique for comparing the means of several samples. When it's required to compare the means of numerous samples to identify which ones are noticeably different from one another, Dunn's test is frequently employed in a range of disciplines, including biology, psychology, and education. We shall examine Dunn's test in−depth in this article, along with a python implementation. What is Dunn’s Test? Dunn's test is a statistical analysis used to compare the means of numerous samples. It is a form of multiple comparison test used to compare the means of more than two samples to identify ... Read More

Many statistical tests and procedures presume that the data is normal and has equal variances. These criteria frequently determine whether a researcher can apply a parametric or non-parametric test, frame hypotheses in specific ways, and so on. Bartlett's test is a prominent inferential statistics test that deals with data from a normal distribution. This post will show you how to run Bartlett's test in python. What is Bartlett’s test?  Bartlett's test is a statistical test that determines whether or not samples have equal variances. It is a hypothesis test that analyzes the variances of two or more samples to see ... Read More

Introduction As the name implies, machine learning is the practice of creating computer algorithms that can learn from various types of data. In a broader definition, Arthur Samuel states that "machine learning is the scientific field which offers computers the power to learn and without being expressly taught." They are frequently used to deal with a variety of everyday difficulties. The algorithms, mathematical equations, and statistical calculations used in the past to perform Machine Learning tasks were all manually coded. As a result, the procedure was time-consuming, challenging, and ineffective. But because of a number of libraries, frameworks, and modules, ... Read More

In this article, we will learn Why is Python such a common beginner's language. The following are the various reasons for it. Why is Python a better first language for beginners? There are other excellent programming languages available, but Python is one of the finest for beginners. It has a simple syntax and straightforward(clear) instructions, making it simple to read and write. Python is also intended for beginners, so you won't have to spend time reading complicated manuals or tutorials. Python is popular due to its ease of learning and teaching. Another reason why people like Python is that it ... Read More

In this article, we will learn the best Python 2.7 modules for data mining. The following are some of the best Python 2.7 modules for data mining − NLTK Beautiful Soup Matplotlib mrjob NumPy pybrain mlpy Scrapy NLTK Natural Language Processing (NLP) is the process of using software or a machine to manipulate or understand text or speech. Humans interact and understand each other's points of view and then respond appropriately. This interaction, understanding, and response are made by a machine rather than a human in NLP. NLTK(Natural Language Toolkit) is a standard Python library that includes ... Read More

In this article, we will learn some underrated Python libraries. The following is a list of some of the underrated libraries in Python − Emmett Jam.py Missingo Emot Shogun Blaze Bamboolib Swifter Caffe Myia Featuretools Altair AutoViz Emmett The Emmett web framework is the first package that is severely underrated and underestimated. The Emmett web framework is flexible and may be used for many various applications in web development. Another advantage is that the Emmett web framework is relatively simple to utilize. It uses Flask−like syntax, making it relatively simple to learn if you are already familiar with ... Read More

In this article, we will look at some of the things that most people dislike about Python. Using Indentation Instead of Curly Braces Many people complain that Python fully relies on indentation to build code blocks. In Python, as you may know, indentation is not optional. The complaints vary, but they frequently include one or more of the following. It is Difficult to Tell Where a Function Ends That is true when writing large Python functions. However, it would be advantageous if you avoided writing large functions altogether. This is true for any language, not just Python. A function should ... Read More