Purchase Solution

Central Limit Theorem and single sample hypothesis test

Not what you're looking for?

Ask Custom Question

A medical research study showed that the average weight of a newborn twin in 1988 was 5.1 lb. To determine if this year's average exceeds the 1988 mean of 5.1 lb., we would test the hypothesis;

Ho (null hypothesis): mu = 5.1 lb.
Ha (alternative hypothesis): mu > 5.1 lb.

Where mu is the actual mean weight of newborn twins born this year.

Suppose you take a random sample of 36 newborn twins. Assuming that the null hypothesis is true, find the probability of getting a sample mean of 5.5 lb. or greater. (use 1.00 lb. as the population standard deviation)

Purchase this Solution
Solution Summary

In this problem, we use the central limit theorem to find the distribution of a sample mean. Then we use that distribution to find the probability that the sample mean from a random sample exceeds a particular value. The probability we find is converted into the p-value then used to test the hypothesis of interest.

Solution Preview

This problem deals with the distribution of the sample mean. I have attached a Word document explaining how the ...

Purchase this Solution
Free BrainMass Quizzes
Measures of Central Tendency

Tests knowledge of the three main measures of central tendency, including some simple calculation questions.

Know Your Statistical Concepts

Each question is a choice-summary multiple choice question that presents you with a statistical concept and then 4 numbered statements. You must decide which (if any) of the numbered statements is/are true as they relate to the statistical concept.

Terms and Definitions for Statistics

This quiz covers basic terms and definitions of statistics.

Measures of Central Tendency

This quiz evaluates the students understanding of the measures of central tendency seen in statistics. This quiz is specifically designed to incorporate the measures of central tendency as they relate to psychological research.

View More Free Quizzes
Related BrainMass Solutions

  • Central Limit Theorem and single sample hypothesis test

    14689 Central Limit Theorem and single sample hypothesis test,,. A spokesman for a popular television game show claims that contestants on the show win an average of $1200.

  • parametric and nonparametric hypothesis test

    b) If the sample size is big enough, then we can use both parametric and nonparametric statistics in the test, due to the central limit theorem. Explains the differernces and similarities between parametric and nonparametric statistics.

  • Sample Mean for a Normal Population

    In this case the Central Limit Theorem allows us to say that the sample mean will follow a normal distribution (for ANY sample size) with mean = 60 and standard error = , so, by finishing the rest of the hypothesis test we would be able to determine

  • Statistics: Definitions and Theory Questions

    342745 Defining statistics terms: Sampling error, estimators, central limit theorem, standard error Define (a) parameter, (b) estimator, (c) sampling error, and (d) sampling distribution. Explain the difference between sampling error and bias.

  • Central Limit Theorum

    The Central Limit Theorem is indeed a very important and useful concept in statistics and plays a role in evaluations of the confidence level or hypothesis testing.

  • Nonparametric Tests: Central Limit Theorem

    When the sample size is large, the central limit theorem kicks in and usually it is OK to use a parametric test even if the normal distribution assumption is questionable.

  • Hypothesis Testing And Central Limit Theorem

    Next, central limit theorem is well defined and explained in details.

  • Central limit theorem for population

    274294 Central limit theorem for population Sample sizes of 50 are selected from a normal population with a mean of 78.1 and standard deviation of 16.2.

  • Normal distribution probability - Central Limit Theorem

    Solution: The Central Limit Theorem helps us differentiate between how to handle X, a single observation taken from a distribution, and , the sample mean of n observations taken from that distribution.

View More Related Solutions