/*! This file is auto-generated */ .wp-block-button__link{color:#fff;background-color:#32373c;border-radius:9999px;box-shadow:none;text-decoration:none;padding:calc(.667em + 2px) calc(1.333em + 2px);font-size:1.125em}.wp-block-file__button{background:#32373c;color:#fff;text-decoration:none} Problem 30 In the study described in the pa... [FREE SOLUTION] | 91Ó°ÊÓ

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In the study described in the paper "Exposure to Diesel Exhaust Induces Changes in EEG in Human Volunteers" (Particle and Fibre Toxicology [2007]), 10 healthy men were exposed to diesel exhaust for 1 hour. A measure of brain activity (called median power frequency, or MPF) was recorded at two different locations in the brain both before and after the diesel exhaust exposure. The resulting data are given in the accompanying table. For purposes of this exercise, assume that it is reasonable to regard the sample of 10 men as representative of healthy adult males. $$ \begin{array}{ccccc} &{\mathrm{MPF}(\operatorname{In} \mathrm{Hz})} \\ { 2 - 5 } \text { Subject } & \begin{array}{c} \text { Location 1 } \\ \text { Before } \end{array} & \begin{array}{c} \text { Location 1 } \\ \text { After } \end{array} & \begin{array}{c} \text { Location 2 } \\ \text { Before } \end{array} & \begin{array}{c} \text { Location 2 } \\ \text { After } \end{array} \\ \hline 1 & 6.4 & 8.0 & 6.9 & 9.4 \\ 2 & 8.7 & 12.6 & 9.5 & 11.2 \\ 3 & 7.4 & 8.4 & 6.7 & 10.2 \\ 4 & 8.7 & 9.0 & 9.0 & 9.6 \\ 5 & 9.8 & 8.4 & 9.7 & 9.2 \\ 6 & 8.9 & 11.0 & 9.0 & 11.9 \\ 7 & 9.3 & 14.4 & 7.9 & 9.1 \\ 8 & 7.4 & 11.3 & 8.3 & 9.3 \\ 9 & 6.6 & 7.1 & 7.2 & 8.0 \\ 10 & 8.9 & 11.2 & 7.4 & 9.1 \end{array} $$ Do the data provide convincing evidence that the mean MPF at brain location 1 is higher after diesel exposure than before diesel exposure? Test the relevant hypotheses using a significance level of 0.05 .

Short Answer

Expert verified
To provide a specific answer, the data from the table needs to be put through the steps mentioned. If the t-statistic exceeds the critical value at 0.05 significance level, there would be convincing evidence that mean MPF at brain location 1 is higher after diesel exposure than before.

Step by step solution

01

Formulate the hypothesis

The null hypothesis (H0) is that there is no difference in the average MPF (Median Power Frequency) before and after diesel exposure at brain location 1. Or in other words, the mean difference is 0. The alternative hypothesis (HA) is that there is a difference in the average MPF before and after exposure, specifically that the mean MPF after exposure is higher than before.
02

Perform paired t-test

To test the hypothesis, use the paired t-test. This compares the means of two related groups to determine if there is statistical evidence that the associated population means are significantly different. When the sample size is smaller than 30, as in this case, a Student's t distribution is used in the test.
03

Calculate the mean difference

Calculate the mean difference between 'after' and 'before' values for each subject. Then, calculate the mean (often denoted as \(d\)) of these differences.
04

Calculate the standard deviation

Standard deviation (often denoted as \(sd\)) of these differences should be calculated. With \(d\) and \(sd\), calculate the test statistic \(t\) using the formula: \(t = \frac{d}{sd / \sqrt{n}}\), where \(n\) is the number of subjects.
05

Find the critical value

Using a t-distribution table, find the critical value for a one-tailed test with \(n - 1\) degrees of freedom at the 0.05 significance level.
06

Compare the t-statistic to the critical value

If the calculated t-statistic is greater than the critical value, reject the null hypothesis in favor of the alternative hypothesis.

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Key Concepts

These are the key concepts you need to understand to accurately answer the question.

Null Hypothesis
When conducting a paired t-test, as in the exercise involving the effect of diesel exhaust on median power frequency (MPF), we first need to define our null hypothesis (\(H_0\)). This hypothesis states that there is no effect—or more technically, no difference—in the variable we're measuring, before and after the treatment. In our case, the null hypothesis claims that the mean MPF at brain location 1 before and after diesel exposure is the same. Formulating a clear null hypothesis is critical because it gives us a specific claim to test against using statistical methods. It acts as a baseline assumption and the concept of 'innocence until proven guilty.' If our analysis shows that the data are highly unlikely if the null hypothesis were true, we then have grounds to reject the null hypothesis in favor of the alternative.
Alternative Hypothesis
Conversely, the alternative hypothesis (\(H_A\)) proposes that there is a change, impact, or difference. For our exercise, the alternative hypothesis suggests that the mean MPF at brain location 1 after diesel exposure is higher than before exposure. This hypothesis is what researchers are often hoping to support, as it indicates a potential effect or relation that may be of interest. It’s essentially what you would accept if you find sufficient evidence to reject the null hypothesis. In hypothesis testing, evidence is gathered via data and analysis to assess whether the null hypothesis can be rejected, thereby lending support to the alternative hypothesis.
Median Power Frequency (MPF)
The median power frequency (MPF) is a measure used in electroencephalography (EEG) to quantify the central frequency of a power spectrum. MPF is useful in determining shifts in brain activity, and as seen in our study, it was measured before and after the subjects were exposed to diesel exhaust. This type of data is critical when performing a paired t-test as it reflects two matched samples from the same subjects under different conditions. When the paired t-test is applied to the MPF data, it evaluates whether the central tendency of the brain's electrical activity changes significantly following an intervention—in this case, diesel exposure.
Statistical Significance
To determine whether the observed differences in the MPF after diesel exposure are due to a real effect rather than random chance, we assess statistical significance. This concept involves calculating a p-value, which reflects the probability that the observed data would occur if the null hypothesis were true. A common threshold is a p-value of 0.05 or 5%. If our analysis yields a p-value lower than this threshold, we conclude the results are statistically significant, which means it's very unlikely that the observed difference in MPF happened by chance. In the given exercise, if the statistical analysis produces a p-value below 0.05, we reject the null hypothesis that there's no difference in MPF before and after diesel exposure. This leads us to believe that diesel exposure has a statistically significant effect on the MPF at brain location 1.

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Most popular questions from this chapter

The press release titled "Keeping Score When It Counts: Graduation Rates and Academic Progress Rates" (The Institute for Diversity and Ethics in Sport, March 16,2009 ) gave the 2009 graduation rates for African American basketball players and for white basketball players at every NCAA Division I university with a basketball program. Explain why it is not necessary to use a paired- samples \(t\) test to determine if the 2009 mean graduation rate for African American basketball players differs from the 2009 mean graduation rate for white basketball players for NCAA Division I schools.

The article "Plugged In, but Tuned Out" (USA Today, January 20,2010 ) summarizes data from two surveys of kids ages 8 to 18 . One survey was conducted in 1999 and the other was conducted in \(2009 .\) Data on the number of hours per day spent using electronic media, consistent with summary quantities given in the article, are given in the following table (the actual sample sizes for the two surveys were much larger). For purposes of this exercise, assume that the two samples are representative of kids ages 8 to 18 in each of the 2 years the surveys were conducted. Construct and interpret a \(98 \%\) confidence interval estimate of the difference between the mean number of hours per day spent using electronic media in 2009 and \(1999 .\) $$ \begin{array}{llllllllllllllll} 2009 & 5 & 9 & 5 & 8 & 7 & 6 & 7 & 9 & 7 & 9 & 6 & 9 & 10 & 9 & 8 \\ 1999 & 4 & 5 & 7 & 7 & 5 & 7 & 5 & 6 & 5 & 6 & 7 & 8 & 5 & 6 & 6 \end{array} $$

For each of the following hypothesis testing scenarios, indicate whether or not the appropriate hypothesis test would be for a difference in population means. If not, explain why not. Scenario 1: A researcher at the Medical College of Virginia conducted a study of 60 randomly selected male soccer players and concluded that players who frequently "head" the ball in soccer have a lower mean IQ (USA Today, August 14,1995 ). The soccer players were divided into two samples, based on whether they averaged 10 or more headers per game, and IQ was measured for each player. You would like to determine if the data support the researcher's conclusion. Scenario 2: A credit bureau analysis of undergraduate students" credit records found that the mean number of credit cards in an undergraduate's wallet was 4.09 ("Undergraduate Students and Credit Cards in \(2004,{ }^{n}\) Nellie Mae, May 2005 ). It was also reported that in a random sample of 132 undergraduates, the mean number of credit cards that the students said they carried was 2.6. You would like to determine if there is convincing evidence that the mean number of credit cards that undergraduates report carrying is less than the credit bureau's figure of \(4.09 .\) Scenario 3: Some commercial airplanes recirculate approximately \(50 \%\) of the cabin air in order to increase fuel efficiency. The authors of the paper "Aircraft Cabin Air Recirculation and Symptoms of the Common Cold" (Journal of the American Medical Association \([2002]: 483-486)\) studied 1,100 airline passengers who flew from San Francisco to Denver. Some passengers traveled on airplanes that recirculated air, and others traveled on planes that did not. Of the 517 passengers who flew on planes that did not recirculate air,

The paper "Effects of Fast-Food Consumption on Energy Intake and Diet Quality Among Children in a National Household Survey" (Pediatrics [2004]: \(112-118\) ) investigated the effect of fast-food consumption on other dietary variables. For a representative sample of 663 teens who reported that they did not eat fast food during a typical day, the mean daily calorie intake was 2,258 and the sample standard deviation was \(1,519 .\) For a representative sample of 413 teens who reported that they did eat fast food on a typical day, the mean calorie intake was 2,637 and the standard deviation was \(1,138 .\) Use the given information and a \(95 \%\) confidence interval to estimate the difference in mean daily calorie intake for teens who do eat fast food on a typical day and those who do not.

The paper referenced in the previous exercise also gave information on calorie content. For the sample of Burger King meal purchases, the mean number of calories was 1,008 , and the standard deviation was \(483 .\) For the sample of McDonald's meal purchases, the mean number of calories was 908 , and the standard deviation was 624 . Based on these samples, is there convincing evidence that the mean number of calories in McDonald's meal purchases is less than the mean number of calories in Burger King meal purchases? Use \(\alpha=0.01\).

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