Blog

On National Statistics Day, we remember P. C. Mahalanobis and the enduring impact of his D² statistic and sample-survey methods on agricultural research.

The paired t-test is a statistical method used to compare the means of two related groups, such as measurements taken before and after a treatment.

The two-sample independent t-test is used to determine whether the means of two independent groups differ significantly.

The F-test is a statistical method used to compare the variances of two populations or samples to determine whether they are significantly different.

The one-sample t-test is used to determine whether a sample mean differs significantly from a known or hypothesized population mean.

Completely Randomized Design (CRD) is the simplest experimental design used in agricultural research, where homogeneous experimental units are randomly assigned to different treatments.

Randomized Complete Block Design (RCBD) is widely used to reduce experimental error by grouping similar experimental units into blocks and randomly assigning all treatments within each block.

The article explains the concept, structure, and applications of the split-plot design in factorial experiments, emphasizing its usefulness when factors require different plot sizes.

The blog explains the concept and application of Strip Plot Design (SPD) for two-factor experiments where precise estimation of interaction effects is required.

Pearson correlation, covering its theory, properties, formulas, and assumptions. It describes how correlation measures the strength and direction of a linear relationship between two continuous variables and how scatter diagrams help visualize these relationships.

This blog explains the concept of correlation as a measure of the strength and direction of the relationship between two variables. It differentiates between parametric correlation (Pearson’s correlation) and non-parametric correlation methods such as Spearman’s rank correlation and Kendall’s tau.

Latin Square Design is an experimental design that controls variability in two directions (rows and columns) by ensuring each treatment appears exactly once in every row and column.

This blog explains the concept and importance of genetic parameters in plant breeding, focusing on how traits are influenced by genetic and environmental factors.

This quiz is designed to test your understanding of the Completely Randomized Design (CRD) in experimental design.

This quiz is designed to test your knowledge and understanding of the Randomized Complete Block Design (RCBD) in experimental design.

This quiz is designed to test your knowledge and understanding of the Pearson Correlation Coefficient, a statistical measure that quantifies the strength and direction of the linear relationship between two continuous variables.

This quiz is designed to test your knowledge and understanding of the Split Plot Design, a statistical method used in experimental design to handle situations where certain factors are more difficult or expensive to change than others.

The blog post hosts a quiz on Latin Square Design, intended for students or researchers learning experimental design in agriculture and statistics.

This blog explains replication, one of the three basic principles of experimental design, as the repeated application of treatments to ensure reliable results.

This blog explains randomization, one of the three basic principles of experimental design, as the process of assigning treatments to experimental units in a way that reduces bias and ensures valid statistical inference.

This blog explains local control, one of the three basic principles of experimental design, as the process of reducing variability within experimental units by grouping similar units together.

Path analysis is the statistical procedure of inferring direct and indirect relationships among variables.