Correlation and its application In previous articles we have seen that,   Variance is a parameter in statistics that measures variation of a single random variable.    In comparison, covariance ( co-variance ) measures how two independent random variables vary together.  Covariance measures directional relationship between two independent random variables.  In this article we shall discuss about 'Correlation'                                                             Two jute ropes with different strengths  Unlike Covariance, Correlation represents not only direction but also Strength of the relationship between two independent random variables. Formula Correla...

Covariance, its application and limitations Variance is a parameter in statistics that measures variation of a single random variable.  In comparison, covariance ( co-variance ) measures how two independent random variables vary together.  Covariance measures directional relationship between two independent random variables.  Examples:  Sale of ice cream with temperature of a place Effect of USA stock market on Indian stock market Effect of no. of working hours on production of a company Effect of hours of study on marks obtained in an examination All the above factors or 1st random variables (temperature of a place, USA stock market, no. of working hours and hours of study) may have either positive effect or negative effect or no effect on the results or 2nd random variable (Sale of ice cream, Indian stock market, production of a company, marks obtained in an examination).  Formula Sample covariance   Population covariance  x̄ = sample m...

Data analysis Part 10: Analysis of variance (ANOVA) test  ANOVA test i.e. Analysis of variance test is used to compare the means among three or more groups. In this test inferences about means are made by analyzing variance. Let us take three sets of data as follows (Actual weight of paracetamol tablets that are marketed as 500mg) Batch1 Batch2 Batch3 499.643 500.240 500.124 499.475 501.055 499.845 500.459 500.120 500.295 499.692 500.680 498.655 497.946 500.478 500.087 500.280 500.157 499.872 500.072 499.961 501.363 500.054 500.833 500.048 499.619 501.052 499.567 500.761 499.996 500.311 499.251 499.264 499.168 500.808 499.221 500.523 500.224 500.384 499.283 500.083 500.999 500.882 500.747 499.507 499.234 498.547 500.690 497.703 501.282 499.731 500.901 499.672 499.934 500.452 499.086 497.957 499.746 499.600 499.131 499.894 500.828 499.257 500.476 501.772 502.237 503.315 499.615 498.184 497.129 500.491 500.381 501.061 499.105 501....