The paper "Is the Larger Sample Changing Anything? " is a worthy example of a statistics assignment. The sample size is extremely essential in the process of sampling as it helps to compare a specific sample comprising of certain characteristics with another sample. Moreover, in the case of a larger sample, finding a specific difference is quite easy and error-free as compared to a smaller sample. Besides, the sample size helps to analyze the specific difference in means, which is extremely essential in evaluating a sample population. It can be calculated by summing up all the numbers and then dividing it with the total numbers.
Therefore, in the case of larger samples, the chance of significance is extremely high as compared to smaller samples. In addition, the sample size also helps to analyze varied types of expected effects. For example, if a generalized finding or result is required then a small sample is effective but in case an accurate result or analysis is essential, then a larger sample may prove effective. But on the other hand, larger sample sizes are quite costly as compared to smaller samples.
In spite of the cost, in maximum cases, larger sample sizes are used in order to attain accurate results rather than generalized outcomes (Mann, 2010). Is your mean increasing or decreasing? The mean of the sample also gets changed due to variation in sample size. This means, in case of larger sample size, the mean of the sample is big or increasing but in case of small sample size, the mean is small. Moreover, larger samples are required in order to evaluate accurate sample mean or population means but in the case of smaller samples, such accuracy may not be possible.
However, due to such type of small samples, varied types of sampling or random variation errors occurs. Therefore, in order to reduce the errors of sampling, in maximum cases, larger samples are used. In addition, if the sample size is large, then the mean might also be accurate and the value of standard deviation may also be exact. Thus, this is also another important reason that depicts that the mean value of the population differs widely due to change in the size of the samples and varied types of errors might also arise due to standard errors in the mean values of the populations. Do you think the current sample you have is enough to paint an accurate picture, or do you need a much larger sample? The current sample of five days of phone calls received is appropriate in order to an accurate sampling mean and an error-free standard deviation.
But, the sampling means and the best sample might be obtained only through a large sample. Therefore, if the sample size might be increased from five to ten, then it might be more accurate and effective for the process of sampling (Mann, 2010). In addition, larger samples reduce the chance of random variation errors or sampling errors rather than smaller samples.
Thus, due to these causes, if the current sample is larger then, it might present error-free results at the process of sampling.