Please read the below paragraph and explain what is meant by: non probability sampling may not be as accurate as probability sampling methods

When the analysis is a based on an entire group or in other words all of the members of the group under study then the population is in place. A sample is taken when this population is too large to measure each one of the members. Think about it from this perspective, if you were investigating McDonalds restaurants, all the McDonalds restaurants in the world would be your population but the sample would be those restaurants that you study.
Probability sampling is similar to pulling a number out of a hat. In the McDonalds scenario if data is needed from the restaurants, one way for obtaining the information would be to draw a sample for a survey based on the zip codes of the specific restaurants. This would be a probability sampling. However, in non-probability sampling the researcher could simply decide to drive to a specific McDonalds restaurant and obtain the information through the survey. Although non probability sampling is a convenient way to conduct a survey, it is not as accurate or rigorous as probability sampling methods.

Solution Preview

The statement that non probability sampling may not be as accurate as probability sampling methods is true because of several factors including the range the data cover and the size of the population.

For example, expanding upon the 'number in a hat' metaphor: let's imagine there were 1000 numbers in the hat ranging from a low of 40 to a high of 80 and with an average of 60. If you decide that it would take too long to draw all 1000 numbers and average them and you used non probability sampling and pulled one number from the hat (say a 53) you might draw the conclusion that the average number in the hat was at or near 53. You would be close to the truth, but not exact. What would happen if you drew a 40? You assumption that the average number was a 40 would be well off base and might lead you to faulty decisions that hinge upon the data. Of course, there is always the chance that you would draw a 60 and would make the right choice, but the conclusion ...

Solution Summary

The solution describes why non probability sampling isn't as accurate as probability sampling related to McDonalds.

For its validity, all hypothesis testing depends heavily on the assumption that the sample that is used was drawn using probabilitysampling techniques.
Why is this important?
What can you do if you just cannot use a probabilitysampling technique? (For example, suppose there is no good sampling frame available for the popul

Probability in a sampling of computer cases being defective, rate is usually 5%
In a sampling of 6 what is the probability of 0 being defective, and what is the probability of exactly one being defective
If 0 or 1 out 6 is defective, process is in control, if the true proportion of defective items is 0.15 what is the prob

What is the difference between probability and non-probabilitysampling? In the answer provide examples on the use of probabilitysampling and non-probabilitysampling on real life problems.

Identify the sampling technique being used. Every 20th patient that comes into the emergency room is given a satisfaction survey upon their discharge.
a. random sampling
b. cluster sampling
c. systematic sampling
d. stratified sampling
e. none of the above

This solution provides the learner with a real world example of a statistical sample and poplulation. The solution further compares and contrasts probabilitysampling with non probablilty sampling and provides a real world example of each.

Suppose the annual consumption of chicken mean is 20.84 pounds per person, and that the standard deviation for the consumption of chicken per person is 9.193 pounds. The mean weight of chicken consumed for a sample of 200 randomly selected people is one value of many that form the sampling distribution of sample means.
Descri

1) Why do you use sampling? Can you provide an example?
2) How many different types of sampling are there.
3) Why do we want to assume that our sample data represents a population distribution?
4) What are some conditions under which business decisions are made using subjective probability concepts? Could you please c

Seiko purchases watch stems in lots of 10,000. Seiko's sampling plan calls for checking 20 items,and if 3 or fewer are defective, the lot is accepted. Based upon their sampling plan, what is the probability that a lot of 10 percent defective will be accepted.

6.30
Given a population in which the proportion of items with a desired attribute is p=0.25, if a sample of 400 is taken:
a. What is the standard deviation of the sampling distribution of _
P?
b. What is the probability the propo