/*! 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 3 Give the equation and graph for ... [FREE SOLUTION] | 91Ó°ÊÓ

91Ó°ÊÓ

Give the equation and graph for a line with \(y\) -intercept equal to 3 and slope equal to -1.

Short Answer

Expert verified
The equation for the line is y = -x + 3. To graph the line, plot the y-intercept point (0, 3), and then from that point, move 1 unit down and 1 unit to the right to plot the point (1, 2). Then, draw a straight line passing through these two points (0, 3) and (1, 2).

Step by step solution

01

Using the slope-intercept form

We are given the slope (m) as -1 and the y-intercept (b) as 3. The slope-intercept form of a linear equation is given by: y = mx + b We just need to plug in the given values of m and b into this equation.
02

Substitute m and b values

Now, we have: y = (-1)x + 3 or y = -x + 3 This is the equation of the line.
03

Graphing the line

To graph the line, follow these steps: 1. Plot the y-intercept point (0, 3) on the graph. 2. Since the slope is -1, from the y-intercept point, move 1 unit down and 1 unit to the right. 3. Plot this new point (1, 2). 4. Draw a straight line passing through the two points (0, 3) and (1, 2). Now, we have the equation and graph for a line with a y-intercept equal to 3 and a slope equal to -1. The equation is y = -x + 3, and the graph is a straight line passing through the points (0, 3) and (1, 2).

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.

Slope-Intercept Form
The slope-intercept form is one of the simplest ways to represent a linear equation. It is written as \( y = mx + b \). Here, \( m \) is the slope of the line, and \( b \) is the y-intercept. This form is widely used because it directly reveals two important characteristics of a line:
  • The slope \( m \), which tells us how steep the line is and the direction it goes (upward if positive, downward if negative).
  • The y-intercept \( b \), which is the point where the line crosses the y-axis.
Knowing the values of \( m \) and \( b \) allows you to quickly understand and graph the line without additional calculations.
Graphing Lines
Graphing lines using the slope-intercept form is straightforward. It involves a clear process that requires minimal effort once you understand these two components. Starting with the y-intercept visually anchors the line on the graph. From there, the slope tells you how to find another point on the line.
  • First, plot the y-intercept \( (0, b) \) on the graph.
  • Then, use the slope, which is the rise over the run, to find another point. For instance, a slope of -1 means from the y-intercept, go one unit down and one unit to the right. This yields another coordinate point.
  • Finally, connect these points with a straight line, extending it across the graph. This line represents the equation visually.
Graphing lines is a visual representation that helps to better understand the relationship between \( x \) and \( y \). It shows how changes in \( x \) affect \( y \).
Y-Intercept
The y-intercept \( b \) is a vital part of a linear equation. It indicates where the line crosses the y-axis. This is the value of \( y \) when \( x \) is zero, literally the starting point in many graph plots.A positive y-intercept means your line crosses the y-axis above the origin, while a negative one means it crosses below. This intercept provides immediate insight into part of the line's position on the graph. Once plotted, the y-intercept serves as a reference point for determining the rest of the line. Knowing only this value allows you to start graphing, teamed up with the slope, to shape the entire line path. Recognizing this simple point can ease understanding complex equations and graph-construction to depict real-world scenarios.

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

The demand for healthy foods that are low in fat and calories has resulted in a large number of "low-fat" or "fat-free" products. The table shows the number of calories and the amount of sodium (in milligrams) per slice for five different brands of fat-free American cheese. $$ \begin{array}{lcc} \text { Brand } & \text { Sodium (mg) } & \text { Calories } \\ \hline \text { Kraft Fat Free Singles } & 300 & 30 \\ \text { Ralphs Fat Free Singles } & 300 & 30 \\ \text { Borden }^{\text {( }} \text { Fat Free } & 320 & 30 \\ \text { Healthy Choice }^{@} \text { Fat Free } & 290 & 30 \\ \text { Smart Beat }^{@} \text { American } & 180 & 25 \end{array} $$ a. Should you use the methods of linear regression analysis or correlation analysis to analyze the data? Explain. b. Analyze the data to determine the nature of the relationship between sodium and calories in fat-free American cheese. Use any statistical tests that are appropriate.

In Exercise we described an informal experiment conducted at McNair Academic High School in Jersey City, New Jersey. Two freshman algebra classes were studied, one of which used laptop computers at school and at home, while the other class did not. In each class, students were given a survey at the beginning and end of the semester, measuring his or her technological level. The scores were recorded for the end of semester survey \((x)\) and the final examination \((y)\) for the laptop group. \({ }^{6}\) The data and the MINITAB printout are shown here. $$ \begin{array}{crr|ccc} & & \text { Final } & & & \text { Final } \\ \text { Student } & \text { Posttest } & \text { Exam } & \text { Student } & \text { Posttest } & \text { Exam } \\ \hline 1 & 100 & 98 & 11 & 88 & 84 \\ 2 & 96 & 97 & 12 & 92 & 93 \\ 3 & 88 & 88 & 13 & 68 & 57 \\ 4 & 100 & 100 & 14 & 84 & 84 \\ 5 & 100 & 100 & 15 & 84 & 81 \\ 6 & 96 & 78 & 16 & 88 & 83 \\ 7 & 80 & 68 & 17 & 72 & 84 \\ 8 & 68 & 47 & 18 & 88 & 93 \\ 9 & 92 & 90 & 19 & 72 & 57 \\ 10 & 96 & 94 & 20 & 88 & 83 \end{array} $$ a. Construct a scatterplot for the data. Does the assumption of linearity appear to be reasonable? b. What is the equation of the regression line used for predicting final exam score as a function of the posttest score? c. Do the data present sufficient evidence to indicate that final exam score is linearly related to the posttest score? Use \(\alpha=.01\) d. Find a \(99 \%\) confidence interval for the slope of the regression line.

Leonardo da Vinci (1452-1519) drew a sketch of a man, }\end{array}\( indicating that a person's armspan (measuring across the back with your arms outstretched to make a "T") is roughly equal to the person's height. To test this claim, we measured eight people with the following results: $$ \begin{array}{l|clll} \text { Person } & 1 & 2 & 3 & 4 \\ \hline \text { Armspan (inches) } & 68 & 62.25 & 65 & 69.5 \\ \text { Height (inches) } & 69 & 62 & 65 & 70 \\ \text { Person } & 5 & 6 & 7 & 8 \\ \hline \text { Armspan (inches) } & 68 & 69 & 62 & 60.25 \\ \text { Height (inches) } & 67 & 67 & 63 & 62 \end{array} $$ a. Draw a scatterplot for armspan and height. Use the same scale on both the horizontal and vertical axes. Describe the relationship between the two variables. b. If da Vinci is correct, and a person's armspan is roughly the same as the person's height, what should the slope of the regression line be? c. Calculate the regression line for predicting height based on a person's armspan. Does the value of the slope \)b$ confirm your conclusions in part b? d. If a person has an armspan of 62 inches, what would you predict the person's height to be?

Why is it that one person may tend to gain weight, even if he eats no more and exercises no less than a slim friend? Recent studies suggest that the factors that control metabolism may depend on your genetic makeup. One study involved 11 pairs of identical twins fed about 1000 calories per day more than needed to maintain initial weight. Activities were kept constant, and exercise was minimal. At the end of 100 days, the changes in body weight (in kilograms) were recorded for the 22 twins. \({ }^{16}\) Is there a significant positive correlation between the changes in body weight for the twins? Can you conclude that this similarity is caused by genetic similarities? Explain. $$ \begin{array}{rrr} \text { Pair } & \text { Twin A } & \text { Twin B } \\ \hline 1 & 4.2 & 7.3 \\ 2 & 5.5 & 6.5 \\ 3 & 7.1 & 5.7 \\ 4 & 7.0 & 7.2 \\ 5 & 7.8 & 7.9 \\ 6 & 8.2 & 6.4 \\ 7 & 8.2 & 6.5 \\ 8 & 9.1 & 8.2 \\ 9 & 11.5 & 6.0 \\ 10 & 11.2 & 13.7 \\ 11 & 13.0 & 11.0 \end{array} $$

How is the cost of a plane flight related to the length of the trip? The table shows the average round-trip coach airfare paid by customers of American Airlines on each of 18 heavily traveled U.S. air routes. $$ \begin{array}{lrr} & \text { Distance } & \\ \text { Route } & \text { (miles) } & \text { Cost } \\ \hline \text { Dallas-Austin } & 178 & \$ 125 \\ \text { Houston-Dallas } & 232 & 123 \\ \text { Chicago-Detroit } & 238 & 148 \\ \text { Chicago-St. Louis } & 262 & 136 \\ \text { Chicago-Cleveland } & 301 & 129 \\ \text { Chicago-Atlanta } & 593 & 162 \\ \text { New York-Miami } & 1092 & 224 \\ \text { New York-San Juan } & 1608 & 264 \\ \text { New York-Chicago } & 714 & 287 \\ \text { Chicago-Denver } & 901 & 256 \\ \text { Dallas-Salt Lake } & 1005 & 365 \\ \text { New York-Dallas } & 1374 & 459 \\ \text { Chicago-Seattle } & 1736 & 424 \\ \text { Los Angeles-Chicago } & 1757 & 361 \\ \text { Los Angeles-Atlanta } & 1946 & 309 \\ \text { New York-Los Angeles } & 2463 & 444 \\ \text { Los Angeles-Honolulu } & 2556 & 323 \\ \text { New York-San Francisco } & 2574 & 513 \end{array} $$ a. If you want to estimate the cost of a flight based on the distance traveled, which variable is the response variable and which is the independent predictor variable? b. Assume that there is a linear relationship between cost and distance. Calculate the least-squares regression line describing cost as a linear function of distance. c. Plot the data points and the regression line. Does it appear that the line fits the data? d. Use the appropriate statistical tests and measures to explain the usefulness of the regression model for predicting 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.