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SIZE CORRECTLY!
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Sample Size Introduction:
Everything is present in an enormous quantity in the universe, however we blame
that we are living in scarcity. For instance human beings are uncountable and we
cannot meet each and everybody intuitively in short time. If we want to establish that
how many people like mango fruit or how many people like cricket game. To establish
this we have to take small number of people randomly. Obviously we have not time
and money to approach each and everybody for this, right! For another example we
usually check the rice by eating only small chunk and we can decide its taste, right!
Let take this if we want to check the bullet quality we do not have to fire each bullet
to establish that bullets are OK! 
Sample Size Significance:
Ideal thing is that we should have sample size equal to the population size, however
it is not always possible on practical grounds. Calculation of sample size is an art. It’s
very necessary to know the accurate number of sample size which can represent the
true population. So we have to determine it very precisely. Sample size and power of
the research has direct relation. Means if we increase our sample size the more will
be the accurate result or more will be the true representation of the population. Some
Index journals has the criteria of specific sample size if you want to publish your
research article. In short we have to make sure that our sample size is large enough
to be published and will determine true depiction of the population.
Sample Size Steps:
Fortunately, Eyedea Research Group has formulated the step by step simple
approach for calculating clear-cut sample required for the research.
Eyedea 7-STEPS
 Steps No. 1:
Idea Clarification: First of all we have to make clear our idea of the research,
which we are going to explore. Eyedea Research Group is ready to help for idea
amplification for youngsters. If we have clear mind regarding the idea we can
determine sample size easily. For instance our research area to check the consumer
behavior of customer for Mobile phone purchase. For this we have to search our
sample from the Mobile phone markets, however we can find our sample anywhere.
Because now everyone has the Mobile device so we have to make sure that we have
to collect the large number of samples to establish our results. For this we have to
give more resources and time but less efforts. Conversely, if we want to establish that
how many people have purchased mangoes by ordering online? For this we have to
give more resources, time and efforts also and obviously only small number of sample
we can find, right!
 Steps No. 2:
Population: After clarification we have to understand that what our overall
population size is. Our sample size should be as near as possible to the population
size and in ideal condition sample should be equal to the population size. For this we
have to see the demographics of our selected population. For example if we want to
know about school going children in Pakistan, our population size will be the total
number of school going children in Pakistan. Obviously, you should not take strain
because even government of Pakistan is not sure about this number.  So we have to
take approximation and for this we have to go for the sample size. Commonly,
population is to be unknown or estimated.
 Steps No. 3:
Margin of Error: It is also called Confidence Interval and written as CI.
Intuitively every sample may or may not be perfect, because we have to take only a
chunk from the population. For this reason we have to take decision to allow the
approximated error. The confidence interval defines how much lower or higher than
the population mean we are willing to let our sample mean to fall. If you have ever
seen a cricket match and you have to give answer online voluntarily that either
Pakistan win or lose today. There is usually mini poll survey on the news, you must
have seen a margin of error or confidence interval in it. For example 78% of voters
said “Yes” to win, with a margin of error of +/- 5%.”
 Steps No. 4:
Confidence Level: It is our confidence level which we want to decide that the actual
mean should fall within our confidence interval. It is denoted by CL. The most
common confidence intervals are 90% (usually taken for political polls), 95% (usually
taken for everyday research) and 99% (usually taken for quality and standard setting
research).
 Steps No. 5:
Find Z-Score: Now it’s time to take the corresponding Z-Score. Fortunately, it is a
constant value. So do not need to calculate or remember. For three confidence levels
mostly used Z-Score values are as below:
Z-Score for 90% Confidence Interval = 1.645
Z-Score for 95% Confidence Interval = 1.96
Z-Score for 99% Confidence Interval = 2.326
Note: If you have picked a different confidence level, use the Z-score table to catch
your Z-score.
 Steps No. 6:
Standard Deviation: It is our expectations that we consider for variance in our
responses. It is usually decided beforehand or before conducting the actual research
survey. Frequently the most précised and safe decision is to use 0.5 for our research.
It is the utmost lenient number. It guarantees that our sample size will be large
enough.
 Steps No. 7:
Calculation: Take a deep breath and relax  now we are ready to calculate our
sample size!
Formula:
Sample Size = (Z-score)² * SD*(1-SD) / (Margin of Error)²
Let’s Take:
Confidence Level=95%
Z-Score=1.96
Standard Deviation=0.45
Margin of Error= +/- 5%=0.05
By putting the values:
Sample Size= [(1.96)² x 0.45(0.5)] / (0.05)²
Sample Size= (3.8416 x 0.225) / 0.0025
Sample Size= 0.8643 / 0.0025
Sample Size= 345.744
Good Job! 
According to our calculation we need only
research.
346
participants as sample size for our
If you find your sample size is too large to handle, attempt to some extent by
decreasing your confidence level or increasing your margin of error. Obviously, the
chance for error will be increased in your sampling, but it can greatly decrease the
number of samples you needed.
Need help finding a qualified panel for your survey?
With our valuable Eyedea Research Group experts, we are ready to find your target
population, sample size solutions, in marginally low cost!
Best of Luck! 
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