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Applications of Standard Error
Standard Error is used to test whether the difference between the sample statistic and the population parameter is significant or is due to sampling fluctuations.
Standard Error is used to find the precision of the sample estimate of a population parameter. If a statistic θ is used to estimate the parameter, then precision of θ =
It is used to find the interval estimate of a population parameter
A population consists of four numbers 3, 4, 2, 5. Consider all possible distinct samples of size two and verify that the population mean is equal to the mean of the sample means.
The population mean (μ) = (3 + 4 + 2 + 5) / 4 = 3.5
All possible distinct samples of size two and the corresponding sample means are shown in the following table.
Samples of Size Two and their Sample Means
Sample No.
Samples
Total of the sample values
Sample mean [Col. 3] ÷ 2
(1)
(2)
(3)
(4)
1
3,4
7
3.5
2
3,2
5
2.5
3
3,5
8
4.0
4
4,2
6
3.0
4,5
9
4.5
2,5
Total
...
21.0
[Sampling used in the above table is random sampling without replacement and the no. of samples = 4C2 = 6].
Mean of sample means = 21.0/6 = 3.5
Hence, the population mean = 3.5 = the mean of the sample means.
Circles or Pie Diagram: Circles or pie diagrams are alternative to squares. These are used for the same purpose i.e. when the values are differing widely in their magnitude
Analysis of variance allows us to test whether the differences among more than two sample means are significant or not. This technique overcomes the drawback of the method used in
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Examples of grouped, simple and frequency distribution data
Consider the sample of 60 package design ratings given in the table below. A Sample of Package Design Ratings (Composite S
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