First Part Conduct an investigation considering the following concepts: Parameter estimation Point estimator Sampling error Repeated sampling Sampling distribution Standard error of the mean Law of...

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First Part Conduct an investigation considering the following concepts: Parameter estimation Point estimator Sampling error Repeated sampling Sampling distribution Standard error of the mean Law of large numbers Central limit theorem Confidence interval of the population mean Confidence interval of a proportion of the population Guiding questions to answer in writing: Define sampling distribution and distinguish it from a distribution of raw scores from a population. How can you show that a statistic calculated on a single sample only provides an estimate of one parameter? For an interval or ratio variable, explain what the standard deviation and error measure dispersion and how the two statistics are mathematically related. Explain the law of large numbers. Under what circumstances does a sampling distribution of proportions fit the normal distribution? Explain and illustrate with formulas why the standard error of the means will always be less than the standard deviation of the variable under study. Second Part After studying and reviewing the concepts and practices from Workshop 2, answer all the questions provided about the concepts from Module # 2: Probability and Sampling Distributions. 1. Recent studies indicate that the average 50-year-old woman spends $ 350 annually on personal care products. The distribution of the amounts spent is governed by a normal distribution with a standard deviation of $ 45 per year. A random sample of 40 women is selected. The average amount that the sample spends is $ 335. What is the probability of finding a sample mean equal to or greater than that of the indicated population? 2. The mean age at which men marry in the United States for the first time is governed by the normal distribution with a mean of 24.8 years. The standard deviation of the distribution is 2.5 years. For a random sample of 60 men, what is the probability that the age at which they first married is less than 25.1 years? 3. Company XYZ conducts a survey with a sample of 60 companies to study the customer's healthcare costs. One of the elements that is studied is the annual deductible that employees must pay. The Department of Labor reports that the mean of this distribution is $ 502, with a standard deviation of $ 100. a. Find the standard error of the sample mean of XYZ. b. What is the probability that XYZ finds a sample mean between $ 477 and $ 527? c. Find the probability that the sample mean is between $ 492 and $ 512. d. What is the probability that the sample mean is greater than $ 550? 4. A research company conducted a survey to determine the average amount that smokers spend on cigarettes during a week. The company found that the distribution of amounts they spend per week tended to follow a normal distribution, with a standard deviation of $ 5. A sample of 49 smokers revealed that the median expense is $ 20. a. What is the point estimator of the population mean? Explain what it indicates. b. Using the 95% confidence level, determine the confidence interval of μ. Explain what it means. 5. The US dairy industry wants to calculate average milk consumption per year. A sample of 16 people reveals that the average annual consumption is 60 gallons, with a standard deviation of 20 gallons. a. What is the value of the population mean? What is the best estimator of this value? b. Explain why you need to use the t distribution. What assumptions do you need to make? c. What is the value of t in a 90% confidence interval? d. Construct the 90% confidence interval of the population mean. e. Is it reasonable to conclude that the population mean is 63 gallons? Explain 6. As a requirement to obtain employment, candidates from a company must pass a drug test. Of the last 220 applicants, 14 failed. Build the 99% confidence level of the proportion of applicants who fail the test. Is it reasonable to conclude that more than 10% of applicants do not pass it? Explain Consider the following when submitting your test: • Present your answers with the aspects learned so far about probability and sampling distributions. • Use the APA style manual when submitting your proof in MS Word document.
Answered 1 days AfterSep 02, 2021

Answer To: First Part Conduct an investigation considering the following concepts: Parameter estimation Point...

Suraj answered on Sep 03 2021
143 Votes
Part 1:
Parameter Estimation: Parameter is the entity of the population. We estimate various parameters of the population by using many methods. Like we estimate the population mean, population standard deviation etc.
Point Estimator: Let X follows normal distribution wi
th unknown parameters . Let be random sample taken on X. The point estimation is to pic a statistic T that best estimates the parameter . Numerical value is called estimate and statistic T is called the estimator of .
Sampling error: This error is defined as that type of error which arise when the sample taken from a population is not perfectly representing the population from which the sample is taken. Then we can say that the sampling error has occurred.
Repeated Sampling: In the repeated sampling the same subject is tested different times with different conditions. For example, the body weight of 50 males is measured. After that, they so some exercise and the weight of the same 50 males is measured again. Repeated samples are also known as paired samples or matched samples.
Sampling distribution: This is defined as the distribution of the sample. As we don’t know the parent population but if the sample size is large that is greater than 30. Then according to central limit theorem, the sampling distribution will be normal distribution with same mean and standard error .
Standard error of the mean: The standard error of the mean is given as follows:
, where is the standard deviation and n is the sample size. The standard error of the mean is always less than the standard deviation.
Law of large numbers: According to law of large number, if we perform the same experiment n time (n is very large). Then the expected value (mean) converges to the population mean.
For example, if we toss a coin n times. Then the expected value of the number of times head obtained becomes same to the theoretical expected value.
Central limit theorem: According to central limit theorem, if we don’t know the parent population but if the sample size is large that is greater than 30. Then according to central limit theorem, the sampling distribution will be normal distribution with same mean and standard error .

Confidence interval of population mean: In this we calculate the estimate about the population mean in terms of an interval. That is we use that interval to make estimation about the population mean.
Confidence interval of a proportion of population: The confidence interval of the proportion includes the interval about the proportion (p) of the population.
The sampling distribution is defined as when we don’t know the parent population of the random sample the according sampling distribution the distribution of any...
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