Statistical Aid: A School of Statistics
Learn Statistics and Data Analysis Intuitively!
What is MANOVA (Multivariate Analysis of Variance)? MANOVA is an extension to univariate ANOVA that includes at least two dependent variables to analyze differences between multiple groups in the independent variable. In contrast to ANOVA, where we compare individual group means, MANOVA compares the vectors containing the group mean of each dependent variable. MANOVA uses omnibus Wilk’s Lambda, Pillai’s Trace … 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
A chi-square test is used to analyze nominal (sometimes known as categorical) data. It is pronounced kai and is frequently written as a χ2 test. It’s used to compare the observed frequencies in each sample’s response categories. The null hypothesis of a chi-square test is that the nominal variables have no relationship, that they are … Read more
Random Forest is a strong ensemble learning method that may be used to solve a wide range of prediction problems, including classification and regression. Because the method is based on an ensemble of decision trees, it offers all of the benefits of decision trees, such as high accuracy, ease of use, and the absence of … 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
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 Packages used Import data file Handling with missing values Scaling … Read more
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