Sampling error is an important concern for researchers. What is the difference between systematic sampling error and random sampling error? What is the tool for calculating sampling error and what does it estimate? Define the term confidence intervals and confidence limits. How are confidence intervals affected by sample size?
What will be an ideal response?
Systematic sampling error refers to errors in the sampling design, whereas random sampling error is due purely to chance. The tool to calculate sampling error is inferential statistics which estimates how likely it is that a statistical result based on data from a random sample is representative of the population from which the sample is assumed to have been selected. Confidence intervals are the range defined by the confidence limits for a sample statistic. Confidence limits are the upper and lower bounds around an estimate of a population parameter based on a sample statistic. The confidence limits show how much confidence can be placed the confidence in the estimate. This wider the confidence interval, the less confident in this sample estimate. When we have really small samples, we will have less confidence in our findings.
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What will be an ideal response?
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