Statistical Aid: A School of Statistics
Learn Statistics and Data Analysis Intuitively!
One Way Repeated Measures ANOVA analyzes data where the same subjects undergo multiple conditions or time points. This test helps researchers determine whether significant differences exist in the means of the dependent variable across different conditions. What is One-Way Repeated Measures ANOVA? A One-Way Repeated Measures ANOVA extends the traditional one-way ANOVA for correlated samples. … Read more
Two-way repeated measures ANOVA is a powerful statistical test used to analyze datasets where two within-subject factors (independent variables) are measured multiple times for each subject. This test helps determine if there are significant differences between groups over time or across different conditions while accounting for individual variability. In this guide, we will cover: Two … Read more
What is MANOVA (Multivariate Analysis of Variance)? Why MANOVA is useful? If there is only one dependent variable is of interest for quantifying the differences between groups, then MANOVA is not necessary. Assumptions of MANOVA MANOVA follows similar assumptions as in ANOVA for the independence of observations and homogeneity of variances In addition, MANOVA needs to meet … Read more
A general linear model (GLM) with at least one continuous and one categorical independent variable is known as ANCOVA (treatments). When the effect of treatments is essential and there is an additional continuous variable in the study, ANCOVA is effective. A covariate is an additional continuous independent variable in ANCOVA (also known as control, concomitant, … Read more
A one-sample t-test is used to see if the mean of a population from which a sample was taken differs statistically from a hypothesised value. The null hypothesis in a t-test is that the population mean is equal to the hypothesised value, while the alternative hypothesis is that it is not. A two-tailed t-test is … Read more
The Pearson correlation coefficient, sometimes known as Pearson’s r, is a statistic that determines how closely two variables are related. Its value ranges from -1 to +1, with 0 denoting no linear correlation, -1 denoting a perfect negative linear correlation, and +1 denoting a perfect positive linear correlation. A correlation between variables means that as … Read more
The Chi-Square Test widely examines relationships between categorical variables as a statistical method. Researchers and analysts apply it in hypothesis testing across various fields, including business, healthcare, and social sciences. This guide will explain the fundamentals, its types, applications, and how to interpret the results. What is the Chi-Square Test? The Chi-Square Test is a … Read more
Random Forest is one of the most widely used ensemble learning techniques in machine learning and statistics. It is a powerful algorithm that enhances prediction accuracy and minimizes overfitting. This article explores the fundamentals of Random Forest, how it works, and its applications in various domains. More precisely, Random Forest is a strong ensemble learning … Read more
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
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