1) Example, to survey how many employees living in hospital provided accommodation in the organization I used to work with in Saudi Arabia is often difficult because of approximately 3000 workers in the organization. It is frequently impractical or impossible to find the real value for a massive size of the population and too costly to survey each in the entire population (Bennett, Briggs & Triola, 2014, p. 279). The best is to estimate the population parameter, and this is when the sample statistic come in handy. 2) As the sample size increases, the margin of error decreases. According to Bennett, Briggs & Triola (2014) explained an excellent example how the size of a sample affecting the margin of error (p.293). To cut the margin of error by a factor of 5, you need 25 times as big of a sample. 3) Sample size = 60 E= 2s n = 2 12.5 60 sample mean= 27.5 sample standard deviation= 12.5 = 3.23 Upper bound = 27.5 + 3.23 = 30.73 Lower bound = 27.5 - 3.23 = 24.27 A 95% confidence interval extending approximately from 24.27 mean< 30.73. 4) Reference: Bennett, J., Briggs, W.L., & Triola, M. F. (2014). Statistical reasoning for everyday life (4th ed.). [VitalSource Bookshelf]. Retrieved from https://online.vitalsource.com