Question

1). _________are sample in which the probability of a population member being selected for the sample is not known?

1. Probability samples
2. Simple random samples
3. Cluster samples
4. Nonprobability samples

2). Identify the type of sampling for the following. Sixty percent of the students attending Shujin Academy are female. I construct a random sample that consists of 60% of females from the student population to ask what their opinions are of the Academy’s food service.

1. Simple random sampling
2. Systematic sampling
3. Cluster sampling
4. Stratified sampling

3). The Central Limit Theorem states that sample means, drawn from any population, will be normally distributed.

A. True

B. False

Choose one of the true/false statements above that you believe is FALSE. Enter the question label.  Either explain why the statement is false OR write the correct statement.  

4). A local gas station waits 4 days to receive a delivery of regular gasoline to replenish its inventory. The waiting period to receive inventory is known as the lead time. The demand during the lead-time period for regular gasoline, as measured in gallons, follows the normal distribution with a mean of 930 gallons and a standard deviation of 140 gallons.

What is the probability that, during the next lead time, the demand for regular gasoline will be less than 1,000 gallons?

Numeric Answer:

Your Answer

0.6915~69.15%

How would we interpret the probability calculated in the previous question?

Answer 1

1. In case of probability and simple random sampling the probability associated is previously known whereas in case of non probability sampling chances of being included in the sample is known but it is not equally likely . The only case is the cluster sampling where the sampling is done by choosing the cluster associated which does not contain any probability.

And -C i.e. Cluster sampling.

2. Here we have to include 60% of the sampling so the probability associated to it is 0.60 and hence out of all the four the simple random sampling can provide probability associated to all the four.

And -A.

3. The central limit theorem states that if we take samples from population then the sample mean asymptotically converges to normal distribution indicating as the sample size increases it will normally distributed .So it is a asymptotic property of sample not for all sample

And -False.

4. Let X be a random variable which denotes the demand during the lead time period expressed in gallon which follows normal distribution with mean 930 and standard deviation 140.

We have to obtain the probability of X<1000 we make use of standard normal table for calculating it.

Therefore the probability is 0.6915.

Interpretation-

The concept is that out of 10000 cases there is 6915 case that the demand for regular gasoline is less than 1000.