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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.
1. Use the concepts of sampling error and z-scores to explain the concept of distribution of sample means. 2. Describe the distribution of sample means shape for samples of n=36
Other Measures of Dispersion In this section, we look at relatively less used measures of dispersion like fractiles, deciles, percentiles, quartiles, interquartile range and f
description
Type of Variable in Regression Analysis There are two types of variable in regression analysis. These are: a. Dependent variable b. Independent variable
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