introduction to math statistics

Module Four: Statistical Inference - Estimation (point estimators and confidence intervals): Estimating population parameters and margins of error Properties of point estimators, including unbiasedness and variability Logic of confidence intervals, meaning of confidence level and confiden..

Probability: Interpreting probability, including long-run relative frequency interpretation 'Law of Large Numbers' concept Addition rule, multiplication rule, conditional probability, and independence Discrete random variables and their probability distributions, including binomial and ..

Overview of methods of data collection: Census Sample survey Experiment Observational study Planning and conducting surveys: Characteristics of a well-designed and well-conducted survey Populations, samples, and random selection Sources of bias in sampling and surveys Samp..

Module One: Exploring Data - Constructing and interpreting graphical displays of distributions of univariate data: Dotplot, stemplot, histogram, cumulative frequency plot Center and spread Clusters and gaps Outliners and other unusual features Shape Summarizing distributions of univariate data: Mea..

Today graphics, tables, reasoning, estimation and prediction are playing a very important role in stating the facts in terms of figures. Statistics deals mainly in communicating facts and figures in terms of a method called statistical method. Collection, classificat..

Statistics is about collection of information and its presentation and about drawing inferences from these. We come across facts and figures in the newspapers, Television and the radio. The numerical figures are called "the data". If we have to draw good inferences from information ..

In our day to day life, we come across many uncertainty of events. We wake up in the morning and check the weather report. The statement could be 'there is 60% chance of rain today'. This statement infers that the chance of rain is more than that having a dry weather. We decide upon our breakfast f..

The mathematical models which tells to optimise (minimize or maximise) the objective function Z subject to certain condition on the variables is called a Linear programming problem (LPP). During World War II, the military managements in the U.K and the USA engaged a team of s..

Suppose the two events are not independent, that is the occurrence of one depends on the occurrence of other, then how do we compute This can be explained by conditional probability. Baye's theorem is named after the British mathematician Thomas Bayes who published it in a research pa..

We are already familiar with graphical reorientation of linear equations and inequations. This chapter describes the application of linear equations and inequations in solving different kinds of practical problems. Let us consider few examples to understand what we mean by linear programming proble..