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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 should be measurement, counts or scores. Sign test for one population in Excel Step 1: … Read More “Sign Test” »
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, data are normally distributed, whereas in nonparametric tests, data are not normally distributed. Assumptions of … Read More “Nonparametric Statistics.” »
Homology Vs Homoplasy Homology is similarity between trait share from common ancestor, most of the homologous characters are recently derived shared characters. Homoplasy is the similarity that are most likely superficially similar (identical on the surface but there is no genetic relation) due to independent evolution and cause misleading of the phylogenetic inferences. The reasons … Read More “Descriptive statistics for phylogenetic trees” »
Evolutionary Trees Important terminologies Rooted trees – this tree type shows evolutionary relationships, direction of evolution and the ancestral state Unrooted trees – this tree type only shows the Phylogenetic relationships. Common ancestor – Simply to choose a point (hypothetical point) on the tree as representing the earliest time in the evolutionary history of the sequence data. … Read More “Summarizing Evolutionary Trees” »
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 observations. Dependent variable should be normally distributed equal variance. R2 = Coefficient of Determination/ Linear … Read More “Linear Regression Analysis Using R” »
Pearson’s correlation (r) check the relationships between two or more variables; there are three types of correlations: simple correlations, multiple correlations, and partial correlations. The correlation between two variables is known as simple correlation. Multiple correlation is the correlation between three or more variables. Partial correlation – Two or more variables are involved, check the … Read More “Pearson’s correlation (r)” »
There are two types of statistical errors. Type 1 error Type 2 error Type 1 error Reject the null hypothesis when null hypothesis is true Type 2 error Fail to reject the null hypothesis when null hypothesis is false Type 1 errors are more dangerous than type 2 errors.
Analysis of variance An ANOVA test is used to compare means between more than two groups. One-way ANOVA uses one independent variable, and two-way ANOVA uses two independent variables.(two factors that are being tested simultaneously) Two main aim of ANOVA tests To explain the relative contribution of the different factors or combination of different factors … Read More “ANOVA test” »
Assumption of Z-test samples are randomly selected from the population Population is normally distributed population variance is known Assumption of T-test samples are randomly selected from the population population is normally distributed populations variance is unknown sample data are continuous Z-test VS T-test Z test can be only apply when the population variance is known … Read More “Z – test & T – Test in R” »
