/*! 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 23 If a slope is 1.63 when \(x=\) i... [FREE SOLUTION] | 91Ó°ÊÓ

91Ó°ÊÓ

If a slope is 1.63 when \(x=\) investment in thousands of euros, then what is the slope when \(x=\) investment in euros?

Short Answer

Expert verified
The slope when investment is in euros is 0.00163.

Step by step solution

01

Understand the Relationship

First, let's comprehend the relationship presented in the problem. Here we have a slope of 1.63, which is given for investments measured in thousands of euros. Hence, this slope reflects how much the dependent variable changes per 1000 € change in the independent variable, investment.
02

Conversion to Single Euro Scale

Next, we need to determine how the slope changes when we measure investment in single euros rather than thousands. Since 1 thousand euros is 1000 euros, we must adjust the slope accordingly.
03

Calculate the New Slope

To find the new slope when investment is measured in euros (not thousands), divide the original slope by 1000. Thus, the new slope is given by: \[ \text{New Slope} = \frac{1.63}{1000} \]
04

Simplify the Calculation

Perform the division to determine the new slope: \[ \text{New Slope} = 0.00163 \] The slope, when investments are expressed in individual euros, is 0.00163.

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.

Unit Conversion
Unit conversion is a critical aspect of mathematical problem-solving because it allows us to change measurements into a more workable and contextual form. In this exercise, we start with a measurement (the slope) that's based on investments in 'thousands of euros.' Why convert it? Because different problems or decisions might require the slope in different terms or units.

To perform unit conversion, follow these steps:
  • Understand the initial unit of measurement. In this exercise, it's 'thousands of euros.'
  • Identify the unit you are converting to, which is 'single euros' in this case.
  • Use a conversion factor, which is essentially how many of the new unit fit into one of the old unit. Here, 1 thousand euros equals 1000 euros.
  • Apply the conversion factor to adjust the measurement. Divide the initial slope by 1000 to convert from 'thousands' to 'single' euros.
By carrying out these conversions thoughtfully, you can manage and solve problems more accurately across diverse contexts.
Mathematical Problem Solving
Problem-solving in mathematics involves understanding the problem, deciding which strategies to use, solving the problem, and checking your solution. Each step uses different skills.

Let's apply these in relation to our exercise:
  • Understanding the Problem: Recognize that the problem asks for a conversion of slope from one unit measurement to another. It requires comprehension of how slope relates to units.
  • Choosing a Strategy: We decide to use division to convert the given slope based on the units involved.
  • Solving the Problem: Perform the division of the slope by 1000. This calculation is straightforward but essential. It represents applying the solution regularly needed in engineering, finance, or physics.
  • Checking the Solution: Ensure the outcome makes sense, both mathematically and within the context. Double-check your division and examine if the new slope seems smaller logically, given it now reflects per euro rather than thousand.
Effectively breaking down and applying these steps is a powerful way to tackle not just this problem but many mathematical challenges.
Linear Relationships
Linear relationships describe how two variables interact in a straight-line relationship, which can be expressed using a linear equation like \( y = mx + b \), where \( m \) represents the slope.

This exercise focuses on converting the slope in a linear relationship into a different unit. The slope of 1.63 initially indicates how much the dependent variable changes for every 1000 €, thus highlighting its rate of change in large investments. By converting this to a slope of 0.00163, we now interpret the linear relationship for a more granular, per-euro basis.

Why is understanding linear relationships crucial?
  • They model predictability and consistency in diverse fields like economics, science, and operations.
  • A linear relationship gives clear insight into how changing one variable affects another.
  • In financial scenarios, such adjustments help organizations see fine-grained impacts of investment changes.
Understanding and working with linear relationships is about seeing the pure interaction between components, even when the units alter.

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

Fast food and indigestion Let \(y=\) number of times fast food was eaten in the past month and \(x=\) number of times indigestion happened in the past month, measured for all students at your school. Explain the mean and variability aspects of the regression model \(\mu_{y}=\alpha+\beta x\) in the context of these variables. In your answer, explain why (a) it is more sensible to use a straight line to model the means of the conditional distributions rather than individual observations and (b) the model needs to allow variation around the mean.

It is expected that the female population in a city will double in two decades. a. Explain why this is possible for a growth rate of \(3.6 \%\) a year. (Hint: What does \((1.036)^{20}\) equal?) b. You might think that a growth rate of \(5 \%\) a year would result in \(100 \%\) growth (i.e. the female population doubles) over two decades. Explain why a growth rate of \(5 \%\) a year would actually cause the female population to multiply by 2.65 over two decades.

Higher income with experience Suppose the regression line \(\mu_{y}=-10,000+9500 x\) models the relationship for the population of working adults in a country between \(x=\) experience (in years) and the mean of \(y=\) annual income (in US dollars). The conditional distribution of \(y\) at each value of \(x\) is modeled as normal with \(\sigma=6500 .\) Use this regression model to describe the mean and the variability around the mean for the conditional distribution at an experience of (a) 5 years and (b) 10 years.

Assumption violated For prediction intervals, an important inference assumption is a constant standard deviation \(\sigma\) of \(y\) values at different \(x\) values. In practice, the standard deviation often tends to be larger when \(\mu_{y}\) is larger. a. Sketch a hypothetical scatterplot for which this happens, using observations on \(x=\) family income and \(y=\) amount donated to charity. b. Explain why a \(95 \%\) prediction interval would not work well at very small or at very large \(x\) values.

Study time and college GPA Exercise 3.39 in Chapter 3 showed data collected at the end of an introductory statistics course to investigate the relationship between \(x=\) study time per week (average number of hours) and \(y=\) college GPA. The table here shows the data for the eight males in the class on these variables and on the number of class lectures for the course that the student reported skipping during the term. $$ \begin{array}{cccc} \hline \text { Student } & \text { Study Time } & \text { GPA } & \text { Skipped } \\ \hline 1 & 14 & 2.8 & 9 \\ 2 & 25 & 3.6 & 0 \\ 3 & 15 & 3.4 & 2 \\ 4 & 5 & 3.0 & 5 \\ 5 & 10 & 3.1 & 3 \\ 6 & 12 & 3.3 & 2 \\ 7 & 5 & 2.7 & 12 \\ 8 & 21 & 3.8 & 1 \\ \hline \end{array} $$ a. Create a data file and use it to construct a scatterplot between \(x\) and \(y\). Interpret. b. Find the prediction equation and interpret the slope. c. Find the predicted GPA for a student who studies 25 hours per week. d. Find and interpret the residual for Student \(2,\) who reported \(x=25\)

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.