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Data consistent with summary quantities in the article referenced in Exercise \(9.3\) on total calorie consumption on a particular day are given for a sample of children who did not eat fast food on that day and for a sample of children who did eat fast food on that day. Assume that it is reasonable to regard these samples as representative of the population of children in the United States. No Fast Food \(\begin{array}{llllllll}2331 & 1918 & 1009 & 1730 & 1469 & 2053 & 2143 & 1981 \\ 1852 & 1777 & 1765 & 1827 & 1648 & 1506 & 2669 & \\ \text { Fast Food } & & & & & & \\ 2523 & 1758 & 934 & 2328 & 2434 & 2267 & 2526 & 1195 \\ 890 & 1511 & 875 & 2207 & 1811 & 1250 & 2117 & \end{array}\) a. Use the given information to estimate the mean calorie intake for children in the United States on a day when no fast food is consumed. b. Use the given information to estimate the mean calorie intake for children in the United States on a day when fast food is consumed. c. Use the given information to estimate the produce estimates of the standard deviations of calorie intake for days when no fast food is consumed and for days when fast food is consumed.

Step by step solution

01

Calculate Mean (No Fast Food)

To calculate the mean calorie intake for days when no fast food is consumed, add up the numbers in the 'No Fast Food' array: \(2331 + 1918 + 1009 + 1730 + 1469 + 2053 + 2143 + 1981 + 1852 + 1777 + 1765 + 1827 + 1648 + 1506 + 2669 = 26914 \), then divide by the total number of values \(15\) to get the mean: \(26914 ÷ 15 = 1794.27\).

02

Calculate Mean (Fast Food)

Similarly, add up the numbers in the 'Fast Food' array and divide by the total number of values \(16\) to find the mean calorie intake for days when fast food is consumed: \(2523 + 1758 + 934 + 2328 + 2434 + 2267 + 2526 + 1195 + 890 + 1511 + 875 + 2207 + 1811 + 1250 + 2117 = 27027. \) The mean is \( \frac{27027}{16} = 1689.18\).

03

Calculate Standard Deviation (No Fast Food)

First, find the variance, which is the mean of the squared differences from the mean. For each number in the 'No Fast Food' array, subtract the mean \(1794.27\) and square the result, then add them together and divide by the number of values (\(15\)). The square root of the variance is the standard deviation. For better readability, this calculation could be performed by a calculator.

04

Calculate Standard Deviation (Fast Food)

Repeat the process in step 3 for the 'Fast Food' array, but using the mean \(1689.18\) for this array. Again, this can be done with the help of a calculator to get more accurate results.

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Key Concepts

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

Mean Calculation

The mean is a fundamental concept in statistics, often referred to as the average. To calculate the mean calorie intake, we sum all values and then divide by the count of values. This gives us a central point in our dataset and aids in understanding the overall tendency of the calorie consumption. For instance, if we have a list of total calories consumed by children not eating fast food, we sum those values and divide by the number of children to find the mean.

In the solved exercise, the mean for 'No Fast Food' was appropriately calculated by adding the given amounts and dividing by the total number of observations, which was 15. This yielded a mean intake of \(1794.27\) calories. Similarly, for 'Fast Food' consumers, totaling the intake and dividing by the 16 observations resulted in a mean of \(1689.18\) calories.

Understanding mean calculation is crucial as it often represents a typical value within a dataset, allowing for an initial glimpse into the eating habits of children in relation to fast food consumption.

Standard Deviation Estimation

Moving beyond the mean, the standard deviation is a measure of the amount of variation or dispersion in a set of values. It tells us how much the values in a dataset deviate from the mean on average. The lower the standard deviation, the closer the data points tend to be to the mean, and vice versa. It's calculated by determining the square root of the variance, where variance is the average of the squared differences from the mean.

To compute it as specified in the exercise solutions, subtract the mean from each observed value, square these differences, and calculate their mean; the square root of this result is the standard deviation. For the 'No Fast Food' group, the standard deviation gives us insight into the consistency of calorie intake among children that stay away from fast food, whereas for the 'Fast Food' group, it reflects the variability in calorie intake on days they do consume fast food.

Statistical Data Analysis

After computing the mean and standard deviation, statistical data analysis involves interpreting these measures to understand the dataset's behavior. In the context of the exercise, comparing the mean values for children's calorie intake on days with and without fast food can highlight the impact of fast food on dietary habits. Further, by examining the standard deviations, we assess the consistency of these habits.

Analyzing the calculated mean and standard deviation helps provide clarity on the overall dietary patterns and their implications. For example, we could discuss whether the observed mean calorie intakes align with dietary recommendations for children and explore the disparities between fast food and non-fast food consumption days. This kind of analysis is essential for educators, policymakers, and healthcare professionals when designing interventions or educational content to promote healthier eating behaviors among children.