/*! 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 6 Give the correct notation for th... [FREE SOLUTION] | 91Ó°ÊÓ

91Ó°ÊÓ

Give the correct notation for the quantity described and give its value. Proportion of families in the US who were homeless in 2010 . The number of homeless families \(^{5}\) in 2010 was about 170,000 while the total number of families is given in the 2010 Census as 78 million.

Short Answer

Expert verified
The notation for the quantity described is \(P = \frac{170000}{78000000}\) and its value is approximately 0.00218.

Step by step solution

01

Understanding the definition of proportion

Proportion is a type of ratio that compares a part to a whole. It is a relational value that shows how the number of specific instances (in this case, the number of homeless families) relates to the total number of instances (total number of families). In mathematical terms, the proportion can be expressed as: Proportion = (Part/Whole)
02

Conversion of millions to actual numbers

To have a consistent unit for the calculation, we need to convert 78 million families to its numerical equivalent. One million is equal to \(10^6\), so 78 million is equal to \(78 \times 10^6\) = 78,000,000
03

Calculation of the Proportion

Now we calculate the proportion of homeless families to the total families: Proportion = (170,000/78,000,000)

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.

Homelessness statistics
Understanding homelessness statistics is vital for gaining insights into socio-economic conditions and making informed policy decisions. These statistics help identify the scale and scope of the problem, enabling governments and organizations to allocate resources effectively. In 2010, approximately 170,000 families were homeless in the United States. These numbers are crucial for planning social services and support systems, such as shelters and affordable housing.
Homelessness statistics often come from extensive surveys and research carried out periodically to track changes over time. Reliable data is essential to grasp the extent of homelessness and to highlight areas most in need of intervention. Knowledge about these statistics can also foster community awareness and drive initiatives towards solving homelessness. Regular updates can help assess the effectiveness of policy measures that address homelessness. The goal is to utilize this data not just to describe the problem, but to work towards solutions that provide permanent and sustainable housing options for those in need.
Census data
Census data plays a significant role in understanding population dynamics and forming a base for statistical analysis. It provides comprehensive data regarding population count, composition, and various socio-economic parameters. Specifically, in determining the proportion of certain demographics, such as homeless families, census data offers the "whole" part of the equation.
For example, the U.S. Census Bureau reported 78 million families in 2010.
  • Large-scale surveys conducted by governmental agencies allow for the collection of reliable and regular data.
  • Such data aids in forming policies, allocating budgets, and creating new programs to meet the needs of the population.
Accurate census data ensures that policymakers have a clear picture of who is in need of assistance, allowing them to tailor interventions accordingly. Furthermore, it helps in understanding trends over time, depicting which areas and communities are growing or shrinking, and what demographic shifts are occurring.
Mathematical notation
Mathematical notation is a system of symbols and expressions used to represent numbers, operations, and relationships precisely and compactly. It helps simplify complex problems by making them easier to understand and communicate.
In calculating proportions, the notation typically involves the division of a part by a whole, written as: \[\text{Proportion} = \frac{\text{Number of Homeless Families}}{\text{Total Number of Families}}\]For the given exercise, this would be expressed as:\[\text{Proportion} = \frac{170,000}{78,000,000}\]This expression shows how essential it is to use a unified system of measurement, like converting millions into an actual numerical value.
Such notations are not only useful in mathematics, but they are also applied in fields like science, engineering, and economics, making it a universally significant language. Emphasizing this notation helps ensure clarity in communication, as complex ideas can be conveyed succinctly among diverse audiences.

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

A Sampling Distribution for Performers in the Rock and Roll Hall of Fame Exercise 3.38 tells us that 206 of the 303 inductees to the Rock and Roll Hall of Fame have been performers. The data are given in RockandRoll. Using all inductees as your population: (a) Use StatKey or other technology to take many random samples of size \(n=10\) and compute the sample proportion that are performers. What is the standard error of the sample proportions? What is the value of the sample proportion farthest from the population proportion of \(p=0.68 ?\) How far away is it? (b) Repeat part (a) using samples of size \(n=20\). (c) Repeat part (a) using samples of size \(n=50\). (d) Use your answers to parts (a), (b), and (c) to comment on the effect of increasing the sample size on the accuracy of using a sample proportion to estimate the population proportion.

In Exercises 3.51 to 3.56 , information about a sample is given. Assuming that the sampling distribution is symmetric and bell-shaped, use the information to give a \(95 \%\) confidence interval, and indicate the parameter being estimated. \(\bar{x}_{1}-\bar{x}_{2}=3.0\) and the margin of error for \(95 \%\) confidence is 1.2

In estimating the mean score on a fitness exam, we use an original sample of size \(n=30\) and a bootstrap distribution containing 5000 bootstrap samples to obtain a \(95 \%\) confidence interval of 67 to \(73 .\) In Exercises 3.106 to 3.111 , a change in this process is described. If all else stays the same, which of the following confidence intervals \((A, B,\) or \(C)\) is the most likely result after the change: \(\begin{array}{ll}A .66 \text { to } 74 & B .67 \text { to } 73\end{array}\) C. 67.5 to 72.5 Using 10,000 bootstrap samples for the distribution.

Better Traffic Flow Exercise 2.155 on page 105 introduces the dataset TrafficFlow, which gives delay time in seconds for 24 simulation runs in Dresden, Germany, comparing the current timed traffic light system on each run to a proposed flexible traffic light system in which lights communicate traffic flow information to neighboring lights. On average, public transportation was delayed 105 seconds under the timed system and 44 seconds under the flexible system. Since this is a matched pairs experiment, we are interested in the difference in times between the two methods for each of the 24 simulations. For the \(n=24\) differences \(D\), we saw in Exercise 2.155 that \(\bar{x}_{D}=61\) seconds with \(s_{D}=15.19\) seconds. We wish to estimate the average time savings for public transportation on this stretch of road if the city of Dresden moves to the new system. (a) What parameter are we estimating? Give correct notation. (b) Suppose that we write the 24 differences on 24 slips of paper. Describe how to physically use the paper slips to create a bootstrap sample. (c) What statistic do we record for this one bootstrap sample? (d) If we create a bootstrap distribution using many of these bootstrap statistics, what shape do we expect it to have and where do we expect it to be centered? (e) How can we use the values in the bootstrap distribution to find the standard error? (f) The standard error is 3.1 for one set of 10,000 bootstrap samples. Find and interpret a \(95 \%\) confidence interval for the average time savings.

Socially Conscious Consumers In March 2015, a Nielsen global online survey "found that consumers are increasingly willing to pay more for socially responsible products."11 Over 30,000 people in 60 countries were polled about their purchasing habits, and \(66 \%\) of respondents said that they were willing to pay more for products and services from companies who are committed to positive social and environmental impact. We are interested in estimating the proportion of all consumers willing to pay more. Give notation for the quantity we are estimating, notation for the quantity we are using to make the estimate, and the value of the best estimate. Be sure to clearly define any parameters in the context of this situation.

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.