Hello Chegg, I need help with these questions. 1) When the sample size and sampl
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Question
Hello Chegg, I need help with these questions.
1) When the sample size and sample standard deviation remain the same, will 99 percent confidence interval for a population mean, , be narrower than the 95 percent confidence interval for or wider? Briefly explain.
Please explain if 99% CI for a population mean is narrower or wider than a 95% CI. Please explain why. Also, please be clear and detailed in your explanation. It will help me understand the problem more better.
2) You work as an analyst in the company XYZ. You have received an assignment to study drug usage among undergraduate students in Essex County, NJ.
a. Discuss the potential problems that you might encounter when you try to collect data.
b. Briefly outline the sampling procedure that would help you accomplish this data collection (define the population, sample frame, and briefly describe the type of sampling, its location and timing).
Please answer part a and part b of question 2. The more information you provide the better.
3) Identify the type (continuous or categorical) of the variables and what kind of distribution it is and explain why for each question.
a. The average number of cars arriving at a drive-through fast-food restaurant is three in 10 minutes. We want to know the probability of exactly four cars arriving in a 5-minute interval.
b. The variable Home Ownership that can take on one of two values. If the person living in a home owns the home and 0 if the person living in a home does not own the home.
c. The weight of the loaf of bread baked, where each outcome has the same probability.
d. The height of the individual in the USA.
Explanation / Answer
1) When the sample size and sample standard deviation remain the same, will 99 percent confidence interval for a population mean, , be narrower than the 95 percent confidence interval for or wider?
A: Very simply, a 99% CI needs to contain 99 out of 100 sample means, if you were to collect 100 sample means, as opposed to 95 out of 100 sample means for a 95% CI. So you would need a 99%CI to be wider to accomodate for more deviations. Note that in this case the sample size is same(100) and sd is same(same sample in either case - from the same population)
2) You work as an analyst in the company XYZ. You have received an assignment to study drug usage among undergraduate students in Essex County, NJ.
a. Discuss the potential problems that you might encounter when you try to collect data.
A: There is a situation of obtaining censored data or truncated data, due to dishonesty or unavailabilty of or vouching for a candidate by other candidates.
Censored data is when you know that there are values of a certain range, but what they are is not known exactly, like you know there are 6 students taking cetain class of drugs but not what they are specifically.
Truncated data is where you have no information regarding the range either.
b. Briefly outline the sampling procedure that would help you accomplish this data collection (define the population, sample frame, and briefly describe the type of sampling, its location and timing).
A: A balanced sample for all levels of undergrad size of atleast 15% of the total class size.
There is however no one fixed method that could be highlighted.
3) Identify the type (continuous or categorical) of the variables and what kind of distribution it is and explain why for each question.
a. The average number of cars arriving at a drive-through fast-food restaurant is three in 10 minutes. We want to know the probability of exactly four cars arriving in a 5-minute interval.
This may be poisson - discrete. Note key words rate/time-interval and exactly.
b. The variable Home Ownership that can take on one of two values. If the person living in a home owns the home and 0 if the person living in a home does not own the home.
A: categorical - can take on one of two values - two categories available for collection.
c. The weight of the loaf of bread baked, where each outcome has the same probability.
A: A Discrete uniform may work here. Note here even though we are measuring weight, it is generally segmented and within bounds. key for uniform is same probability.
d. The height of the individual in the USA.
A: This is purely continuous. A normal distribution should work nicely. Though it maked sense to talk in terms of average height, quantile heights and such when we talk of a population, and so individual random heights arise in case of drawn sample observations.
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