/*! 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 20 The article "Caffeinated Energy ... [FREE SOLUTION] | 91Ó°ÊÓ

91Ó°ÊÓ

The article "Caffeinated Energy Drinks-A Growing Problem" (Drug and Alcohol Dependence [2009]: 1-10) gave the accompanying data (on the next page) on caffeine concentration (mg/ounce) for eight top-selling energy drinks. a. What is the mean caffeine concentration for this set of energy drinks? b. Coca-Cola has 2.9 mg/ounce of caffeine and Pepsi Cola has \(3.2 \mathrm{mg} /\) ounce of caffeine. Write a sentence explaining how the caffeine concentration of top-selling energy drinks compares to that of these colas. $$ \begin{array}{|lc|} \hline \text { Energy Drink } & \begin{array}{c} \text { Caffeine Concentration } \\ \text { (mg/ounce) } \end{array} \\ \hline \text { Red Bull } & 9.6 \\ \text { Monster } & 10.0 \\ \text { Rockstar } & 10.0 \\ \text { Full Throttle } & 9.0 \\ \text { No Fear } & 10.9 \\ \text { Amp } & 8.9 \\ \text { SoBe Adrenaline Rush } & 9.5 \\ \text { Tab Energy } & 9.1 \\ \hline \end{array} $$

Short Answer

Expert verified
The mean caffeine concentration of the given set of top-selling energy drinks is 9.5 mg/ounce, which is significantly higher than the caffeine concentration of Coca-Cola (2.9 mg/ounce) and Pepsi Cola (3.2 mg/ounce).

Step by step solution

01

Organize the data

Given data of caffeine concentration (mg/ounce) for eight top-selling energy drinks: Red Bull - 9.6 Monster - 10.0 Rockstar - 10.0 Full Throttle - 9.0 No Fear - 10.9 Amp - 8.9 SoBe Adrenaline Rush - 9.5 Tab Energy - 9.1
02

Calculate the mean caffeine concentration of energy drinks

To calculate the mean of the caffeine concentration for the eight top-selling energy drinks, we need to add up all the caffeine concentrations and then divide the sum by the number of energy drinks. Mean = \(\frac{Sum \thinspace of \thinspace caffeine \thinspace concentrations}{Number \thinspace of \thinspace energy \thinspace drinks}\) Mean = \(\frac{9.6 + 10.0 + 10.0 + 9.0 + 10.9 + 8.9 + 9.5 + 9.1}{8}\) Mean = \(\frac{76}{8}\) Mean = 9.5 mg/ounce
03

Compare the caffeine concentration of energy drinks to Coca-Cola and Pepsi Cola

Now, let's compare the mean caffeine concentration of top-selling energy drinks (9.5 mg/ounce) to Coca-Cola (2.9 mg/ounce) and Pepsi Cola (3.2 mg/ounce). As we can see, the mean caffeine concentration of the top-selling energy drinks is significantly higher than that of Coca-Cola and Pepsi Cola. So, in conclusion: a. The mean caffeine concentration for this set of energy drinks is 9.5 mg/ounce. b. The caffeine concentration of top-selling energy drinks is significantly higher compared to that of Coca-Cola (2.9 mg/ounce) and Pepsi Cola (3.2 mg/ounce).

Unlock Step-by-Step Solutions & Ace Your Exams!

  • Full Textbook Solutions

    Get detailed explanations and key concepts

  • Unlimited Al creation

    Al flashcards, explanations, exams and more...

  • Ads-free access

    To over 500 millions flashcards

  • Money-back guarantee

    We refund you if you fail your exam.

Over 30 million students worldwide already upgrade their learning with 91Ó°ÊÓ!

Key Concepts

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

Mean Calculation
When tasked with understanding data from a sample set, calculating the mean provides valuable insights. The mean, often referred to as the average, is a measure that gives us the central value of a data set. To find the mean caffeine concentration of energy drinks, we need to conduct the following steps:
  • Add all the caffeine concentrations together.
  • Divide this sum by the number of measurements (in this case, the number of energy drinks).
Starting with the given values for caffeine concentrations: Red Bull (9.6), Monster (10.0), Rockstar (10.0), Full Throttle (9.0), No Fear (10.9), Amp (8.9), SoBe Adrenaline Rush (9.5), and Tab Energy (9.1), we first sum them up:
9.6 + 10.0 + 10.0 + 9.0 + 10.9 + 8.9 + 9.5 + 9.1 = 76.
Next, we divide this sum by the total number of drinks, which is 8, leading us to: \[ \text{Mean} = \frac{76}{8} = 9.5 \text{ mg/ounce} \]Thus, the average caffeine concentration across these drinks is 9.5 mg/ounce.
Data Organization
Data organization is crucial, particularly when dealing with numerous data points. It ensures clarity and facilitates accurate calculations. For the caffeine concentration exercise, organizing the data involves listing out each energy drink and its corresponding caffeine concentration. This methodical presentation aids in tracking the data easily and avoiding errors during calculation.
It's a straightforward step yet a foundational task that underpins further statistical analysis. When data is well-organized:
  • Each data point is visible and accessible.
  • Summation and other operations can happen smoothly.
  • It highlights any inconsistencies or errors to be addressed prior to further analysis.
In this exercise, writing down the caffeine concentrations in a simple list format, as shown above, facilitates the next step of calculating the mean confidently.
Comparative Analysis
Comparative analysis extends our understanding by placing data points or sets against each other. In this exercise, after finding the mean caffeine concentration for popular energy drinks, we compare this figure to the caffeine levels in regular colas like Coca-Cola and Pepsi.
The comparison reveals the energy drinks' caffeine concentration (9.5 mg/ounce) is substantially higher than Coca-Cola's (2.9 mg/ounce) and Pepsi's (3.2 mg/ounce). Comparative analysis tells us:
  • The relative strength of caffeine in energy drinks versus regular sodas.
  • It provides context that can guide consumer choices.
  • It assists producers in positioning their products in the market.
Such analysis not only helps in understanding current data standings but also supports decision-making processes based on comparative evidence.

One App. One Place for Learning.

All the tools & learning materials you need for study success - in one app.

Get started for free

Most popular questions from this chapter

Although bats are not known for their eyesight, they are able to locate prey (mainly insects) by emitting high-pitched sounds and listening for echoes. A paper appearing in Animal Behaviour ("The Echolocation of Flying Insects by Bats" [1960]: 141-154) gave the following distances (in centimeters) at which a bat first detected a nearby insect: $$ \begin{array}{lllllllllll} 62 & 23 & 27 & 56 & 52 & 34 & 42 & 40 & 68 & 45 & 83 \end{array} $$ a. Calculate and interpret the mean distance at which the bat first detects an insect. b. Calculate the sample variance and standard deviation for this data set. Interpret these values.

Suppose that your younger sister is applying to college and has taken the SAT exam. She scored at the 83 rd percentile on the verbal section of the test and at the 94 th percentile on the math section. Because you have been studying statistics, she asks you for an interpretation of these values. What would you tell her?

The report "Who Borrows Most? Bachelor's Degree Recipients with High Levels of Student Debt" (trends .collegeboard.org/content/who-borrows-most-bachelors -degree-recipients-high-levels-student-debt-april-2010, retrieved April 20,2017 ) included the following percentiles for the amount of student debt for students graduating with a bachelor's degree in 2010: $$ \begin{array}{ll} \text { 10th percentile } & =\$ 0 & \text { 25th percentile }=\$ 0 \\ \text { 50th percentile } & =\$ 11,000 & \text { 75th percentile }=\$ 24,600 \\\ \text { 90th percentile } & =\$ 39,300 & \end{array} $$ For each of these percentiles, write a sentence interpreting the value of the percentile. (Hint: See Example 3.20.)

The state of California defines family income groups in terms of median county income as follows: Extremely low income: below \(30 \%\) of county median income Very low income: between \(30 \%\) and \(50 \%\) of county median income Low income: between \(50 \%\) and \(80 \%\) of county median income Moderate income: between \(80 \%\) and \(120 \%\) of county median income For San Luis Obispo County, the median income as of May 24,2016 for single person households was $$\$ 53,950$$ (www.slocounty.ca.gov/Assets/PL/Housing/AHS/AHS.pdf, August \(1,2016,\) retrieved April 19,2017\()\). a. Interpret the value of the median income for a singleperson household in San Luis Obispo County. b. Each of the following statements is incorrect. For each statement, use the given information to explain why it is incorrect. Statement 1: \(30 \%\) of the single-person households in San Luis Obispo County would be classified as extremely low income. Statement 2: More than \(50 \%\) of the single-person households in San Luis Obispo County would be classified as extremely low income or very low income. Statement 3 : There cannot be any single-person households in San Luis Obispo County that would be classified as having an income that was greater than those in the moderate income category.

The article "The Wedding Industry's Pricey Little Secret \(^{n}\) (June \(12,2013,\) www.slate.com, retrieved April \(19,\) 2017 ) stated that the widely reported average wedding cost is grossly misleading. The article reports that in \(2012,\) the average wedding cost was $$\$ 27,427$$ and the median cost was $$\$ 18,086$$ a. What does the large difference between the mean cost and the median cost tell you about the distribution of wedding costs in \(2012 ?\) b. Do you agree that the average wedding cost is misleading? Explain why or why not. c. The article also states "the proportion of couples who spent the 'average' or more was actually a minority." Do you agree with this statement? Explain why or why not using the reported values of the mean and median wedding cost.

See all solutions

Recommended explanations on Math Textbooks

View all explanations

What do you think about this solution?

We value your feedback to improve our textbook solutions.

Study anywhere. Anytime. Across all devices.