For each of the scenarios below, determine if the sample is a simple random samp
ID: 3341064 • Letter: F
Question
For each of the scenarios below, determine if the sample is a simple random sample from the population of interest, or if the sample has some form of bias. If there is a bias, describe the nature of the bias in a sentence or two. (a) You are interested in the average height of all freshmen on a college campus. You draw a simple random sample of freshmen in your statistics class. (b) You are interested in the range of the glaze thicknesses on mugs created in a factory. You sample every 5th mug o of the assembly line. (c) You are interested in the average IQ of 6th graders in Daze County public schools. You get your sample by using computer software to randomly select 100 6th grade student ID numbers from the Daze County public school database. (d) You work for a doctor's office and you are interested in estimating the proportion of patients that visited the office in the last month that feel they received satisfactory care. You randomly select names from the list of patients who have been to the office, and email them a survey. About 25% of the surveys are returned.
Explanation / Answer
a) it has a bias. because to estimate the average height of all freshmen on a college campus, we must take choose some students randomly from each of the department. The random sample of freshmen drawn only from statistics class would not be a good representative of the population. hence the estimate would be a faulty one.
b) it is a random sample. this type of sampling is called systematic sampling where first unit is drawn randomly and then every k-th unit is included in the sample. the randomness is associated in drawing the first unit.
c) it is arguably the most appropriate random sample. as the target population is 6th grade students in Daze County public schools so randomly selecting 100 6th grade students using simulation would give a proper random sample
d)it is a random sample but it has a bias of non response. getting only 25% response of the desired random sample would not produce an efficient sampl. so the estimation would be good. more the sample size better the estimate
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