Statistical Aid: A School of Statistics
Learn Statistics and Data Analysis Intuitively!
MD TOUHIDUL ISLAM
The paired sample t-test, sometimes called the dependent sample t-test, is a statistical procedure used to determine whether the mean difference between two sets of observations is zero. In a paired sample t-test, each subject or entity is measured twice, resulting in pairs of observations. The steps involved in paired sample t-test are following: Introduction Formulation … Read more
The one-way analysis of variance (ANOVA) is used to determine whether there are any statistically significant differences between the means of three or more independent (unrelated) groups. This guide will provide a brief introduction to the one-way ANOVA, including the assumptions of the test and when you should use this test. One-way ANOVA contains the … Read more
A two-way ANOVA test is a statistical test used to determine the effect of two nominal predictor variables on a continuous outcome variable. A two-way ANOVA tests the effect of two independent variables on a dependent variable. This blog post contains the following steps of two-way ANOVA in r: Introduction Repeated measures Randomized blocks Import data … Read more
Cluster analysis is a statistical technique that groups similar observations into clusters based on their characteristics. It is a statistical method of processing data. A good cluster analysis produces high-quality clusters with high inter-class correlation. This blogpost contains the following steps of cluster analysis: Introduction to cluster analysis Clustering is the task of dividing the … Read more
PCA means Principal Component Analysis. Principal Component Analysis (PCA) is a powerful dimensionality reduction technique widely used in statistics, machine learning, and data analysis. In simpler terms, it’s a way to simplify complex data by reducing the number of variables while retaining the most important information. PCA is a multivariate technique that is used to … Read more
Multicollinearity, a term that often sends shivers down the spines of statisticians and data scientists, is a phenomenon encountered in regression analysis where two or more predictor variables in a multiple regression model are highly correlated. While correlation itself isn’t inherently bad, high multicollinearity can wreak havoc on your model’s interpretation and performance, leading to … Read more
ICA means Independent Component Analysis. It is the most powerful and widely used statistical technique which is used to separate independent sources from their mixture. It is also known as a blind source separation technique. More precisely, Independent Component Analysis plays a crucial role in signal processing and data analysis. Researchers and engineers use ICA … Read more
Stata is a general-purpose statistical software package developed by Stata Corp for data manipulation, visualization, statistics, and automated reporting. It is used by researchers in many fields, including economics, sociology, political science, biomedicine, and epidemiology. Developer’s Description Stata Corp is a leading developer in statistical software, primarily through its flagship product Stata. Used by professional … Read more
SPSS means statistical package for social science. SPSS is the most famous data analytics tool which is used to clean, manage, and analyze data. There are two window in SPSS. They are data view and variable view. By using variable view, we can easily insert any variable name with its types (nominal, ordinal, interval and … Read more
Logistic Regression is a fundamental statistical method widely used in machine learning, data science, and various fields of research. Despite its simplicity, it remains a powerful tool for binary classification problems and has numerous real-world applications ranging from medical diagnoses to customer churn prediction. More precisely, It is a statistical technique to find the association … Read more
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