There is a large body of literature devoted to sampling designs and statistical applications for estimating population parameters and their associated confidence levels. A major concern associated with these procedures is the accuracy and precision of the survey results.
So that you can have confidence in your survey. If you have too many or too few respondents, you will have type 1 or 2 errors, so it's important to ascertain the correct power and sample size. But to calculate sample size, you need to set your confidence level. Precision refers to how close estimates from different samples are to each other and you can use standard error as an estimate of this.
You want to be sure your results are going to be useable, so it is always best to plan ahead.
الدقة في المسح ضرورية جدا للوصول الى نتائج تمثل مجتمع البحث التي تقوم بدراسته
Accuracy closeness to the real situation. It refers to the magnitude of systematic errors or degree of bias associated with an estimation procedure. This affects how well the estimated value represents the true value. Systematic errors may or may not be measurable and can cause estimates to consistently under or over-estimate the true value.
Precision is a reprodusibility of the finding. It refers to the variability in estimates. High precision means that random variation associated with the collection procedure is minimized. Generally larger numbers of samples provide greater precision than small numbers.
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