SWETA SAXENA
RESEARCH METHODOLOGY
LECTURE-31
IMPORTANT SAMPLING DISTRIBUTIONS
Some important sampling distributions, which are commonly used, are:
(1) sampling distribution of mean; (2) sampling distribution of proportion; (3)
student’s ‘t’ distribution; (4) F distribution; and (5) Chi-square distribution
STANDARD ERROR
The standard deviation of sampling distribution of a statistic is known as its
standard error (S.E) and is considered the key to sampling theory.
What is sample size and its determination?
Sample size determination is the act of choosing the number of observations or
replicates to include in a statistical sample. The sample size is an important
feature of any empirical study in which the goal is to make inferences about a
population from a sample.
What are the terms used around the sample size?
Before we jump into sample size determination, let’s take a look at the terms
you should know:
Population size: Population size is how many people fit your demographic. For
example, you want to get information on doctors residing in North America.
Your population size is the total number of doctors in North America. Don’t
worry! Your population size doesn’t always have to be that big. Smaller
population sizes can still give you accurate results as long as you know who
you’re trying to represent.
Confidence level: Confidence level tells you how sure you can be that your data
is accurate. It is expressed as a percentage and aligned to the confidence
interval. For example, if your confidence level is 90%, your results will most
likely be 90% accurate.
The margin of error (confidence interval): When it comes to surveys, there’s no
way to be 100% accurate. Confidence intervals tell you how far off from the
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population means you’re willing to allow your data to fall. A margin of error
describes how close you can reasonably expect a survey result to fall relative to
the real population value. Remember, if you need help with this information you
can use our margin of error calculator.
Standard deviation: Standard deviation is the measure of the dispersion of a
data set from its mean. It measures the absolute variability of a distribution. The
higher the dispersion or variability, the greater the standard deviation and the
greater the magnitude of the deviation. For example, you have already sent out
your survey. How much variance do you expect in your responses? That
variation in response is the standard of deviation.
