Yes it is.
Vishal
a large number of samples of size 50 were selected at random from a normal population with mean and variance.The mean and standard error of the sampling distribution of the sample mean were obtain 2500 and 4 respectivly.Find the mean and varince of the population?
There are two major alternative sampling plans:
sampling plans have nothing it is all a troll...
Standard error is random error, represented by a standard deviation. Sampling error is systematic error, represented by a bias in the mean.
IEC 60410 specifies guidelines for the sampling of bulk materials, focusing on the design of sampling systems and procedures. To load samples according to this standard, you first need to define the sampling plan based on the material's characteristics and the intended analysis. Then, implement a systematic approach to collect representative samples, ensuring that the sampling equipment is properly calibrated and that the samples are stored and transported in a manner that preserves their integrity. Finally, document the entire process for traceability and compliance with the standard.
The answer in standard form for 2.5 x 10^3 is 2500.
The standard deviation associated with a statistic and its sampling distribution.
NO
If the samples are drawn frm a normal population, when the population standard deviation is unknown and estimated by the sample standard deviation, the sampling distribution of the sample means follow a t-distribution.
The probability of a double sampling plan on the combined samples of two sampling plans depends on the acceptance criteria established for each plan and the characteristics of the population being sampled. In a double sampling plan, an initial sample is evaluated, and if the results are inconclusive, a second sample is taken. The overall acceptance probability will be a function of the probabilities of acceptance from both samples, typically calculated using statistical methods that consider the distribution of the data and the defined acceptance limits. Thus, the exact probability must be determined based on specific parameters of the sampling plans and the underlying population distribution.
You calculate the standard error using the data.
Thanks to the Central Limit Theorem, the sampling distribution of the mean is Gaussian (normal) whose mean is the population mean and whose standard deviation is the sample standard error.