MATLAB: An Introduction with Applications
6th Edition
ISBN: 9781119256830
Author: Amos Gilat
Publisher: John Wiley & Sons Inc
expand_more
expand_more
format_list_bulleted
Concept explainers
Question
Fifty-four
wild bears were anesthetized, and then their weights and chest sizes were measured and listed in a data set. Results are shown in the accompanying display. Is there sufficient evidence to support the claim that there is a α=0.05.
|
Correlation Results
|
Correlation coeff, r:
|
0.979514
|
---|---|
Critical r:
|
±0.2680855
|
P-value (two tailed):
|
0.000
|
|
|
|
Determine the null and alternative hypotheses.
H0:
ρ(>,≠,=,<) ________
H1:
ρ
(>,≠,=,<) ________
(Type integers or decimals. Do not round.)
Identify the correlation coefficient, r.
r=_____
(Round to three decimal places as needed.)Identify the critical value(s).
(Round to three decimal places as needed.)
There is one critical value at
r=______.
There are two critical values at
r=±__________.
Is there sufficient evidence to support the claim that there is a linear correlation between the weights of bears and their chest sizes? Choose the correct answer below and, if necessary, fill in the answer box within your choice.
(Round to three decimal places as needed.)
Yes, because the absolute value of the test statistic
nothing
exceeds the critical value.No, because the absolute value of the test statistic
nothing
exceeds the critical value.Yes, because the test statistic
nothing
falls between the critical values.No, because the test statistic
nothing
falls between the critical values.The answer cannot be determined from the given information.
When measuring an anesthetized bear, is it easier to measure chest size than weight? If so, does it appear that a measured chest size can be used to predict the weight?
Yes, it is easier to measure a chest size than a weight because measuring weight would require lifting the bear onto the scale. The chest size could be used to predict weight because there is a linear correlation between the two.
No, it is easier to measure weight than chest size because the chest is not a flat surface.
Yes, it is easier to measure a chest size than a weight because measuring weight would require lifting the bear onto the scale. The chest size could not be used to predict weight because there is too much variance in the weight of the bears.
Yes, it is easier to measure a chest size than a weight because measuring weight would require lifting the bear onto the scale. The chest size could not be used to predict weight because there is not a linear correlation between the two.
Expert Solution
This question has been solved!
Explore an expertly crafted, step-by-step solution for a thorough understanding of key concepts.
This is a popular solution
Trending nowThis is a popular solution!
Step by stepSolved in 2 steps with 1 images
Knowledge Booster
Learn more about
Need a deep-dive on the concept behind this application? Look no further. Learn more about this topic, statistics and related others by exploring similar questions and additional content below.Similar questions
- Fifty-four wild bears were anesthetized, and then their weights and chest sizes were measured and listed in a data set. Results are shown in the accompanying display. Is there sufficient evidence to support the claim that there is a linear correlation between the weights Correlation Results of bears and their chest sizes? When measuring an anesthetized bear, is it easier to measure chest size than weight? If so, does it appear that a measured chest size can be used to predict the weight? Use a significance level of a = 0.05. Correlation coeff, r: 0.969467 Critical r: +0.2680855 P-value (two tailed): 0.000 ..... Determine the null and alternative hypotheses. Ho: P (Type integers or decimals. Do not round.) Identify the correlation coefficient, r. r= (Round to three decimal places as needed.) Identify the critical value(s). (Round to three decimal places as needed.) A. There are two critical values at r= + В. There is one critical value at r= Is there sufficient evidence to support the…arrow_forwardThis question has 5 parts, Thank you.arrow_forwardFor a data set of weights (pounds) and highway fuel consumption amounts (mpg) of twelve types of automobile, the linear correlation coefficient is found and the P-value is 0.009. Write a statement that interprets the P-value and includes a conclusion about linear correlation.arrow_forward
- Listed below are amounts of bills for dinner and the amounts of the tips that were left. Construct a scatterplot, find the value of the linear correlation coefficient r, and find the P-value of r. Determine whether there is sufficient evidence to support a claim of linear correlation between the two variables. Use a significance level of a = 0.05. If everyone were to tip with the same percentage, what should be the value of r? Bill (dollars) Tip (dollars) Tip Amount ($) Construct a scatterplot. Choose the correct graph below. O A. 25- 30 C ● ·· Bill Amount (S) 32.25 49.72 87.12 101.52 66.52 104.21 4.25 7.70 7.90 11.83 7.08 11.35 120 Q M O B. Tip Amount ($) 25- ++++ 30 .. Bill Amount (S) 120 Q Q M C O C. Tip Amount ($) 25- 0+ 30 ● ·· Bill Amount ($) 120 Q Q O D. ip Amount ($) 25- to 0- 30 · Bill Amount (S) 120 Q Q Uarrow_forwardplease answer blank questions only and or ones with a red x next to them.arrow_forwardFifty-four wild bears were anesthetized, and then their weights and chest sizes were measured and listed in a data set. Results are shown in the accompanying display. Is there sufficient evidence to support the claim that there is a linear correlation between the weights of bears and their chest sizes? When measuring an anesthetized bear, is it easier to measure chest size than weight? If so, does it appear that a measured chest size can be used to predict the weight? Use a significance level of α=0.05. Correlation Results Correlation coeff, r: 0.963947 Critical r: ±0.2680855 P-value (two tailed): 0.000 Determine the null and alternative hypotheses. H0: ρ is: = 0 H1: ρ is: ≠ 0 Given all the information provided: Identify the correlation coefficient, r. r= _____ (round to three decimal places)arrow_forward
- Fifty-four wild bears were anesthetized, and then their weights and chest sizes were measured and listed in a data set. Results are shown in the accompanying display. Is there sufficient evidence to support the claim that there is a linear correlation between the weights of bears and their chest sizes? When measuring an anesthetized bear, is it easier to measure chest size than weight? If so, does it appear that a measured chest size can be used to predict the weight? Use a significance level of a = 0.05 Question: Determine the null and alternative hypothesesarrow_forwardIf one wishes to assess the relation between a farming county's average annual temperature and the crop yield, it may be important to take into account the overlapping variability that crop yield and temperature share with rainfall. To do so, one would compute a: a. partial correlation. b. split-half reliability. c. concurrent validity. d. coefficient alpha.arrow_forwardBaseball owners believe that the more runs scored, the higher the attendance. Is there evidence that more fans attend games if the teams score more runs? Data collected midway through the season indicate a correlation of 0.848 between runs scored and the number of people at games. a) Does the scatterplot indicate that it's appropriate to calculate a correlation? Explain. O A. Yes, because the relationship between number of runs scored and attendance appears to be straight. O B. Yes, because the association between the number of runs scored and attendance is positive. 37500- OC. No, because there are too many outliers for a numerical correlation to be appropriate. 30000- O D. No, because the number of runs scored and attendance are not quantitative variables. b) Describe the association between attendance and runs scored. 22500- 320 360 400 440 480 O A. The association between attendance and runs scored is negative, straight, and moderate. Runs O B. The association between attendance…arrow_forward
- Listed below are amounts of bills for dinner and the amounts of the tips that were left. Construct a scatterplot, find the value of the linear correlation coefficient r, and find the P-value of r. Determine whether there is sufficient evidence to support a claim of linear correlation between the two variables. Use a significance level of a = 0.01. If everyone were to tip with the same percentage, what should be the value of r? Bill (dollars) Tip (dollars) 31.80 52.94 85.82 102.16 60.17 111.77 D 5.46 6.07 15.82 15.40 11.15 20.32 Construct a scatterplot. Choose the correct graph below. O A. O B. Oc. D. Q 25- 25- 25 0- 30 0- 30 Bill Amount ($) 0+ 30 Bill Amount (S) 0- 30 Bill Amount (S) 120 120 120 Bill Amount (S) 120 The linear correlation coefficient is r= 0.954 (Round to three decimal places as needed.) Determine the null and alternative hypotheses. Ho: p H,: P (Type integers or decimals. Do not round.) Tip Amount ($) ip Amount ($) Tip Amount ($) Tip Amount ($)arrow_forwardA researcher measures GPA and height for a group of high school students. What kind of correlation is likely to be obtained for these two variables?arrow_forwardIn running a Pearson correlation, you notice that there are a few outliers. Please describe the next course of action, if any, for the dataset and explain your reasoning.arrow_forward
arrow_back_ios
SEE MORE QUESTIONS
arrow_forward_ios
Recommended textbooks for you
- MATLAB: An Introduction with ApplicationsStatisticsISBN:9781119256830Author:Amos GilatPublisher:John Wiley & Sons IncProbability and Statistics for Engineering and th...StatisticsISBN:9781305251809Author:Jay L. DevorePublisher:Cengage LearningStatistics for The Behavioral Sciences (MindTap C...StatisticsISBN:9781305504912Author:Frederick J Gravetter, Larry B. WallnauPublisher:Cengage Learning
- Elementary Statistics: Picturing the World (7th E...StatisticsISBN:9780134683416Author:Ron Larson, Betsy FarberPublisher:PEARSONThe Basic Practice of StatisticsStatisticsISBN:9781319042578Author:David S. Moore, William I. Notz, Michael A. FlignerPublisher:W. H. FreemanIntroduction to the Practice of StatisticsStatisticsISBN:9781319013387Author:David S. Moore, George P. McCabe, Bruce A. CraigPublisher:W. H. Freeman
MATLAB: An Introduction with Applications
Statistics
ISBN:9781119256830
Author:Amos Gilat
Publisher:John Wiley & Sons Inc
Probability and Statistics for Engineering and th...
Statistics
ISBN:9781305251809
Author:Jay L. Devore
Publisher:Cengage Learning
Statistics for The Behavioral Sciences (MindTap C...
Statistics
ISBN:9781305504912
Author:Frederick J Gravetter, Larry B. Wallnau
Publisher:Cengage Learning
Elementary Statistics: Picturing the World (7th E...
Statistics
ISBN:9780134683416
Author:Ron Larson, Betsy Farber
Publisher:PEARSON
The Basic Practice of Statistics
Statistics
ISBN:9781319042578
Author:David S. Moore, William I. Notz, Michael A. Fligner
Publisher:W. H. Freeman
Introduction to the Practice of Statistics
Statistics
ISBN:9781319013387
Author:David S. Moore, George P. McCabe, Bruce A. Craig
Publisher:W. H. Freeman