nce Intervals and Hypothesis Testing for the Difference of Population Means In this assignment you will be creating and interpreting a confidence interval for a difference of population means, and creating and completing a hypothesis test for the same variable. This is most similar to Take It Home 9.4.1. You will be using the data in the files FBODY 2.pdf and MBODY 2.pdf.From FBODY2.pdf and MBODY 2.pdf choose the same variable for males and females. The variables are described below. For example, you could choose the weight variable for each group, or the BMI, or the HDL variable. Tell me what you chose. 1.Hypothesis Testing for the Difference of Population Means a. Write, in both sentence form and symbolic form, null hypothesis and alternative hypothesis for deciding: is there a difference between males and females for the population means of the variable you selected? b. Is this a left-tailed, right-tailed, or two-tailed test? c. Explain why you believe the normality criteria are valid for your chosen data. d. Calculate the sample mean, , sample standard deviation, s, and the sample size, n, for the variable for both the females and for the males. (). e. Calculate the difference of sample means, , f. Calculate the standard error and the t-score for your difference from part e: . g. Calculate the p-value for your hypothesis test. To do this, select the correct df for the variable you chose using the degrees of freedom table below, and use the tcdf() function on the TI calculator. h. Choose a level of significance, say 0.05, 0.02, or 0.01. Should you reject or not reject the null hypothesis? i. Explain, in terms a non-statistics person would understand, your conclusion from part h, explaining what it tells us about the difference in population means for this variable for adult males and females

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Description: Confidence Intervals and Hypothesis Testing for the Difference of Population Means In this assignment you will be creating and interpreting a confidence interval for a difference of population means, and creating and completing a hypothesis test for

MATLAB: An Introduction with Applications

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ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

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Confidence Intervals and Hypothesis Testing for the Difference of Population Means In this assignment you will be creating and interpreting a confidence interval for a difference of population means, and creating and completing a hypothesis test for the same variable. This is most similar to Take It Home 9.4.1. You will be using the data in the files FBODY 2.pdf and MBODY 2.pdf. From FBODY2.pdf and MBODY 2.pdf choose the same variable for males and females. The variables are described below. For example, you could choose the weight variable for each group, or the BMI, or the HDL variable. Tell me what you chose. 1.Hypothesis Testing for the Difference of Population Means a. Write, in both sentence form and symbolic form, null hypothesis and alternative hypothesis for deciding: is there a difference between males and females for the population means of the variable you selected? b. Is this a left-tailed, right-tailed, or two-tailed test? c. Explain why you believe the normality criteria are valid for your chosen data. d. Calculate the sample mean, , sample standard deviation, s, and the sample size, n, for the variable for both the females and for the males. (). e. Calculate the difference of sample means, , f. Calculate the standard error and the t-score for your difference from part e: . g. Calculate the p-value for your hypothesis test. To do this, select the correct df for the variable you chose using the degrees of freedom table below, and use the tcdf() function on the TI calculator. h. Choose a level of significance, say 0.05, 0.02, or 0.01. Should you reject or not reject the null hypothesis? i. Explain, in terms a non-statistics person would understand, your conclusion from part h, explaining what it tells us about the difference in population means for this variable for adult males and females.

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Definition Definition Measure of central tendency that is the average of a given data set. The mean value is evaluated as the quotient of the sum of all observations by the sample size. The mean, in contrast to a median, is affected by extreme values. Very large or very small values can distract the mean from the center of the data. Arithmetic mean: The most common type of mean is the arithmetic mean. It is evaluated using the formula: μ = 1 N ∑ i = 1 N x i Other types of means are the geometric mean, logarithmic mean, and harmonic mean. Geometric mean: The nth root of the product of n observations from a data set is defined as the geometric mean of the set: G = x 1 x 2 ... x n n Logarithmic mean: The difference of the natural logarithms of the two numbers, divided by the difference between the numbers is the logarithmic mean of the two numbers. The logarithmic mean is used particularly in heat transfer and mass transfer. ln x 2 − ln x 1 x 2 − x 1 Harmonic mean: The inverse of the arithmetic mean of the inverses of all the numbers in a data set is the harmonic mean of the data. 1 1 x 1 + 1 x 2 + ...

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