Category Statistics – Experimental Design & Data Analysis Using R

############view first six rows of dataset############### Output: Output:

Output: According to this petal length and petal width, sepal length and petal length , Sepal length, and petal width are highly correlated. This leads to multicollinearity. This issue can be reduce using PCA analysis. Now there is no correlation between multiple…

Multivariate analysis is a statistical methods that perform simultaneous analysis of multiple variables. identify the relationships among variables and identify the patterns and trends of the information. Types of multivariate analysis Factor Analysis Principal component analysis Cluster analysis Discriminant analysis…

Mainly there are four experimental design models. Completely Randomized Design (CRD) Random Completely Block Design (RCBD) Split Plot Design Latin Square Design (LSD) Completely Randomized Design (CRD) Experimental unit in the population has an equal equally treated with the treatments/randomly…

Most commonly used statistical sampling methods are shown below. Random sampling Stratified sampling Cluster sampling Systematic sampling Random sampling Each member in the population has equal chance to being selected. This can be used when the population is homogeneous. E.g.…

The Spearman correlation is a non-parametric alternative to the linear correlation coefficient. Assumptions of Spearman Correlation Random sampling Independent measurements Data should be measurements counts or ordinal Steps in Spearman Correlation

Mann Whitney U test is the alternative for the two independent sample t-test Assumption for Mann Whitney u test Random sampling Independent measurement Two population should same shape of distribution. Steps for Mann Whitney U test.

The sign test is used for hypothesis testing by concerning the value of the median for one population, and comparing the median differences for two variables for two dependent samples. Assumptions of the sign test. Random sampling Independent measurements Data…

Nonparametric statistics deals with median rather than mean, because mean can be easily influenced by the outliers or skewness of data, and data are not normally distributed. The main difference between parametric and nonparametric tests is that in parametric tests,…

Linear regression analysis describe the relation between two or more variables,and find the best fit line to the graph and equation of the straight line; that is used for make predictions. Assumption of Regression Analysis Random sampling independent measurements or…