Final answer:
The correct formula to calculate the Standard Error of the Mean (SEM) is B) SEM = (Standard Deviation) / (Square Root of Sample Size).
Step-by-step explanation:
The Standard Error of the Mean (SEM) is a measure of the variability of sample means around the population mean. It quantifies the precision of the sample mean as an estimate of the population mean. The formula to calculate SEM is derived from the standard deviation of the sample divided by the square root of the sample size.
This is represented as SEM = (Standard Deviation) / (√Sample Size). It is crucial to note that SEM decreases as the sample size increases, indicating a more precise estimate of the population mean with larger sample sizes.
The concept of SEM is pivotal in inferential statistics, especially when interpreting the reliability of sample means and drawing conclusions about the population. It helps in understanding the likely range within which the true population mean may lie. The smaller the SEM, the more reliable the sample mean estimation becomes, as it signifies less variability among sample means.
In summary, SEM is symbolically represented as B) SEM = (Standard Deviation) / (Square Root of Sample Size). It is a critical measure in statistical analysis, providing insights into the accuracy of sample means in reflecting the population mean.""
The correct formula to calculate the Standard Error of the Mean (SEM) is B) SEM = (Standard Deviation) / (Square Root of Sample Size).