All brawn? The following scatterplot plots the average brain weight (in grams) versus average body weight (in kilograms) for 96 species of mammals.18 There are many small mammals whose points overlap at the lower left.

a. The correlation between body weight and brain weight is r=0.86 Interpret this value.

b. What effect does the human have on the correlation? Justify your answer.

Short Answer

Expert verified

Part (a) There is a fairly strong and positive association between body weight (inkg)and brain weight (ing)

Part (b) The correlation coefficient r would decrease due to a decrease in linearity.

Step by step solution

01

Part (a) Step 1: Given information

Correlation, r=0.86

02

Part (a) Step 2: Explanation

A positive linear correlation exists when r is positive.

A negative linear correlation exists when r is negative.

For weak correlation,

0<|r|<0.5

For moderate correlation,

0.5<|r|<0.8

For strong correlation,

0.8<|r|<1

Note that

The association between body weight in kilograms and brain weight in grams is a strong and positive association.

03

Part (b) Step 1: Explanation

Note that

The dot corresponding to "Human" in the scatterplot is above the typical pattern in the other points.

Thus,

In comparison to other mammals, humans have a larger brain weight in proportion to their body weight.

Also,

Because of the divergence from the linear pattern, the data's linearity is reduced.

We also know

The correlation measures the degree of linearity between the variables.

Hence,

Due to a decrease in linearity, the correlation coefficientr would also decrease.

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 Vaia!

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 stock market Some people think that the behavior of the stock market in January predicts its behavior for the rest of the year. Take the explanatory variable x to be the percent change in a stock market index in January and the response variable y to be the change in the index for the entire year. We expect a positive correlation between x and y because the change during January contributes to the full year’s change. Calculation from data for an 18-year period gives x¯=1.75% sx=5.36% y¯=9.07% sy=15.35% r=0.596

a. Find the equation of the least-squares line for predicting full-year change from January change.

b. Suppose that the percent change in a particular January was 2 standard deviations above average. Predict the percent change for the entire year without using the least-squares line.

Longer strides In Exercise 43, we summarized the relationship between x =

height of a student (in inches) and y = number of steps required to walk the length of a school hallway, with the regression line y^=113.6−0.921x. For this

model, technology gives s = 3.50 and r2 = 0.399.

a. Interpret the value of s.

b. Interpret the value of r2.

Managing diabetes People with diabetes measure their fasting plasma glucose (FPG, measured in milligrams per milliliter) after fasting for at least 8 hours. Another measurement, made at regular medical checkups, is called HbA. This is roughly the percent of red blood cells that have a glucose molecule attached. It measures average exposure to glucose over a period of several months. The table gives data on both HbA and FPG for 18 diabetics five months after they had completed a diabetes education class.

a. Make a scatterplot with HbA as the explanatory variable. Describe what you see.

b. Subject 18 is an outlier in the x-direction. What effect do you think this subject has on the correlation? What effect do you think this subject has on the equation of the least-squares regression line? Calculate the correlation and equation of the least-squares regression line with and without this subject to confirm your answer.

c. Subject 15 is an outlier in the y-direction. What effect do you think this subject has on the correlation? What effect do you think this subject has on the equation of the least-squares regression line? Calculate the correlation and equation of the least-squares regression line with and without this subject to confirm your answer.

IQ and grades Exercise 3 (page 158) included the plot shown below of school grade point average (GPA) against IQ test score for 78seventh-grade students. (GPA was recorded on a 12-point scale with A+=12,A=11,A-=10,B+=9,...D-=1,F=0.) Calculation shows that the mean and standard deviation of the IQ scores areX¯=108.9and Sx=13.17For the GPAs, these values are Y=7.447andSy=2.10. The correlation between IQ and GPA is 0.6337

(a) Find the equation of the least-squares line for predicting GPA from IQ. Show your work.

(b) What percent of the observed variation in these students’ GPAs can be explained by the linear relationship between GPA and IQ?

(c) One student has an IQ of 103but a very low GPA of 0.53. Find and interpret the residual for this student

In addition to the regression line, the report on the Mumbai measurements says that r2 =0.95. This suggests that

a. although arm span and height are correlated, arm span does not predict height very accurately.

b. height increases by 0.95=0.97 cm for each additional centimeter of arm

span.

c. 95% of the relationship between height and arm span is accounted for by the regression line.

d. 95% of the variation in height is accounted for by the regression line with x = arm span. e. 95% of the height measurements are accounted for by the regression line with x = arm span.

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.

Sign-up for free