statistics p value example

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..

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: Measurin..

From the following data, compute the value of standard deviations and variance..

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 colle..

Identify the corner point at which the value of the objective function is maximum (or minimum depending on the LPP) The co-ordinates of this vertex is the optimal solution and the value of Z is the optimal val..

A random variable which can assume all possible values between certain limits is called a continuous random variabl..

Quantities such as height, weight, age, amount can have several different values. Quantities which can assume different numerical values are called variables. Variables are of two types: (a) Continuous (b) Discre..

There can be several r.v's associated with an experiment. A random variable which can assume only a finite number of values or countably infinite values is called a discrete random variable. e.g., Consider a random experiment of tossing three coins simultaneously. Let X denote..