Already have an account? Get multiple benefits of using own account!
Login in your account..!
Remember me
Don't have an account? Create your account in less than a minutes,
Forgot password? how can I recover my password now!
Enter right registered email to receive password!
Stratified Sampling
Stratified Sampling is generally used when the population is heterogeneous. In this case, the population is first subdivided into several parts (or small groups) called strata. According to some relevant characteristics so that each stratum is more or less homogeneous. Each stratum is called a sub-population. Then a small sample (called sub-sample) is selected from each stratum at random. All the sub-samples combined together form the Stratified Sample. This represents the population properly. The process of obtaining and examining a Stratified Sample with a view to estimate the characteristic of the population is known as Stratified Sampling.
Example
The retailer can use Stratified Sampling as explained below:
She would analyze the bill copies according to items purchased, viz. TVs, Stereos, VCRs, etc. Each product’s customers would form a strata. Hence, we would have the following strata:
TV buyers
Stereo buyers
VCR buyers
For each stratum, random sampling would be done.
You will recall the function pnorm() from lectures. Using this, or otherwise, Dteremine the probability of a standard Gaussian random variable exceeding 1.3. Using table(), or
(a) The Horton's initial infiltration capacity for a catchment is 204 mm/h and the constant infiltration value at saturation is 60 mm/h. For a rainfall in excess of 204 mm/h mainta
what are characteristics of a population for which it would be appropiate to use mean/median/mode
Consider an MBA program as a processing network where the flow unit consists of a student in the program. Suppose the organizations that hire and promote MBAs are considered to be
The Null Hypothesis - H0: The random errors will be normally distributed The Alternative Hypothesis - H1: The random errors are not normally distributed Reject H0: when P-v
This box plot displays the diversity wfood; the data ranges from 0.05710 being the minimum value and 0.78900 being the maximum value. The box plot is slightly positively skewed at
dasda
Factor analysis (FA) explains variability among observed random variables in terms of fewer unobserved random variables called factors. The observed variables are expressed in
A file on DocDepot in the assignments folder on doc-depot called bmi.mtp contains data on the Body Mass Index (BMI) of a population of Ottawa residents. The first column identifies
Chebychev inequality
Get guaranteed satisfaction & time on delivery in every assignment order you paid with us! We ensure premium quality solution document along with free turntin report!
whatsapp: +91-977-207-8620
Phone: +91-977-207-8620
Email: [email protected]
All rights reserved! Copyrights ©2019-2020 ExpertsMind IT Educational Pvt Ltd