Because it's More than a Subject
1. Median for Individual Series In an individual series, data is ungrouped and needs to be arranged in ascending order. Steps: – Arrange the data in ascending order.– Let \(n\) be the total number of observations. Formula (if \(n\) is odd): \[\text{Median} = \text{Value of } \left( \frac{n + 1}{2} … read more
1. Arithmetic Average in Individual Series Direct Method \[\bar{X} = \frac{\sum X}{N}\] Where; = Arithmetic Mean \(\sum {X}\) = Sum of all values = Total number of observations Shortcut Method \[\bar{X} = A + \frac{\sum d}{N}\] Where; = Arithmetic Mean = Assumed Mean = Deviation of each value \(\sum {d}\) … read more
Statistics is one of the most crucial branches of knowledge in modern education and research. It is often said that we live in an age of statistics. This statement is not an exaggeration, given the ever-increasing significance of statistical methods in daily life, business, administration, and scientific inquiry. As undergraduate … read more
Following are the small and large sample properties of a Good Estimator Small Sample Properties 1. Unbiased Estimator: Biased means the difference between the parameter’s true value and the estimator’s value. When the difference becomes zero then it is called Unbiased estimator. = 2. Best Estimator: An estimator is called … read more
Chi-Square is an important non-parametric test and as such, rigid assumptions are necessary regarding the type of population we require only the degree of freedom for using this test. Non- parametric chi-square test can be used This test was developed by statistician “Karl Pearson”. As a test of goodness of … read more
The term probability has been interpreted in terms of four definitions : 1. Classical Definition of Probability: the classical definition states that if an experiment consists of ’’ outcomes that are mutually exclusive, exhaustive, and equally likely and of them ate the favorable outcomes of an event A then the … read more
Following are the assumptions underlying when we use method of Least Squares Assumption 1: Linear regression model The regression model is linear in the parameters i.e., Assumption 2: values are fixed in repeated sampling Values taken by the regressor are considered fixed in repeated samples. More technically, is assumed to … read more
The expected value, or mean, of a random variable is a measure of the central location for the random variable. The formula for the expected value of a discrete random variable X follows. The expected value of a discrete random variable X can be written as i.e., Properties of Mathematical … read more
Given the assumptions of the classical linear regression model, the least-squares estimators, in the class of unbiased linear estimators, have minimum variance, that is, they are BLUE. In other words, the Gauss-Markov theorem holds the properties of Best Linear Unbiased Estimators. Following are some of the assumptions that should be … read more