Introduction to Probability and Statistics
14th Edition
ISBN: 9781133103752
Author: Mendenhall, William
Publisher: Cengage Learning
expand_more
expand_more
format_list_bulleted
Question
Chapter 9, Problem 9.64SE
i.
To determine
The null hypothesis and alternative hypothesis statement
ii.
To determine
To draw:
The rejection region for statistical test at
iii.
To determine
Test the hypothesis and give the conclusion
Expert Solution & Answer
Want to see the full answer?
Check out a sample textbook solutionStudents have asked these similar questions
A certain chemical pollutant in the Pasig River has been constant for several years with
mean u = 34 ppm (parts per million). A group of industry representatives claim that their
waste management programs have lowered this average significantly.
1) What is the line of best fit for this data?
a. y =-1.11x+ 11.83; r=-0.9760964904
Average Speed
(mi/h)
Time (hours)
b. y 11.83x- 1. 11; r=0.9527643586
8.5
2.5
c. y= 11.83x –- 1. 11; r=-0.9760964904
7.5
3.75
d. y =-1.11x+ 11.83; r= 0.9527643586.
6.5
4.5
6.0
5.0
5.5
5.5
5.0
6.25
4.0
6.75
3.5
8.75
r notes
MacBook Pro
*
2$
&
4
5
6
7
8
9.
%3D
deletc
{
[
Y
]
G H
J
K
L
>
?
C
V
N
M
+ ||
.. ..
B
The toco toucan, the largest member of the toucan family, possesses the largest beak relative to body size of all birds. This exaggerated feature has received various interpretations, such as being a refined adaptation for feeding. However, the large surface area may also be an important mechanism for radiating heat (and hence cooling the bird) as outdoor temperature increases. Here are data for beak heat loss, as a percent of total body heat loss from all sources, at various temperatures in degrees Celsius. [Note: The numerical values in this problem have been modified for testing purposes.]
Temperature (oC)(oC)
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
Percent heat loss from beak
33
33
34
31
37
46
54
49
41
50
44
56
55
61
64
59
The equation of the least-squares regression line for predicting beak heat loss, as a percent of total body heat loss from all sources, from temperature is: (Use decimal notation. Enter the values of the intercept and slope rounded to two decimal…
Chapter 9 Solutions
Introduction to Probability and Statistics
Ch. 9.3 - Find the appropriate rejection regions for the...Ch. 9.3 - Prob. 9.2ECh. 9.3 - Find the appropriate rejection regions for the...Ch. 9.3 - Prob. 9.4ECh. 9.3 - For the three tests given in Exercise 9.4, use the...Ch. 9.3 - A random sample of n=35 observations from a...Ch. 9.3 - Prob. 9.7ECh. 9.3 - Prob. 9.8ECh. 9.3 - A random sample of 100 observations from a...Ch. 9.3 - Prob. 9.10E
Ch. 9.3 - Prob. 9.11ECh. 9.3 - Prob. 9.12ECh. 9.3 - Prob. 9.14ECh. 9.3 - Prob. 9.15ECh. 9.3 - What’s Normal? What is normal, when it comes to...Ch. 9.4 - Prob. 9.18ECh. 9.4 - Independent random samples of 36 and 45...Ch. 9.4 - Prob. 9.20ECh. 9.4 - Cure for the Common Cold? An experiment was...Ch. 9.4 - Healthy Eating As Americans become more conscious...Ch. 9.4 - Prob. 9.24ECh. 9.4 - Prob. 9.25ECh. 9.4 - Prob. 9.26ECh. 9.4 - Prob. 9.27ECh. 9.4 - Prob. 9.28ECh. 9.4 - What’s Normal II Of the 130 people in Exercise...Ch. 9.5 - A random sample of n=1000 observations from a...Ch. 9.5 - A random sample of n=1400 observations from a...Ch. 9.5 - Prob. 9.32ECh. 9.5 - Prob. 9.33ECh. 9.5 - Prob. 9.38ECh. 9.5 - Prob. 9.40ECh. 9.5 - Prob. 9.41ECh. 9.6 - Independent random samples of n1=140 and n2=140...Ch. 9.6 - Prob. 9.43ECh. 9.6 - Prob. 9.46ECh. 9.6 - Prob. 9.47ECh. 9.6 - Prob. 9.48ECh. 9.6 - Prob. 9.49ECh. 9.6 - Prob. 9.50ECh. 9 - Prob. 9.52SECh. 9 - Prob. 9.53SECh. 9 - Prob. 9.54SECh. 9 - Prob. 9.55SECh. 9 - Prob. 9.56SECh. 9 - Prob. 9.57SECh. 9 - Prob. 9.58SECh. 9 - Prob. 9.59SECh. 9 - Prob. 9.60SECh. 9 - White-Tailed Deer In an article entitled “A...Ch. 9 - Prob. 9.62SECh. 9 - Prob. 9.63SECh. 9 - Prob. 9.64SECh. 9 - Prob. 9.65SECh. 9 - Prob. 9.66SECh. 9 - Prob. 9.67SECh. 9 - Prob. 9.68SECh. 9 - Prob. 9.69SECh. 9 - Prob. 9.70SECh. 9 - Prob. 9.71SECh. 9 - Actinomycin D A biologist hypothesizes that high...Ch. 9 - Prob. 9.73SECh. 9 - Prob. 9.74SECh. 9 - Heights and Gender It is a well-accepted fact that...Ch. 9 - Prob. 9.79SECh. 9 - Prob. 9.81SE
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
- Table 6 shows the population, in thousands, of harbor seals in the Wadden Sea over the years 1997 to 2012. a. Let x represent time in years starting with x=0 for the year 1997. Let y represent the number of seals in thousands. Use logistic regression to fit a model to these data. b. Use the model to predict the seal population for the year 2020. c. To the nearest whole number, what is the limiting value of this model?arrow_forwardThe toco toucan, the largest member of the toucan family, possesses the largest beak relative to body size of all birds. This exaggerated feature has received various interpretations, such as being a refined adaptation for feeding. However, the large surface area may also be an important mechanism for radiating heat (and hence cooling the bird) as outdoor temperature increases. Here are data for beak heat loss, as a percent of total body heat loss from all sources, at various temperatures in degrees Celsius. [Note: The numerical values in this problem have been modified for testing purposes.] Temperature (oC)(oC) 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 Percent heat loss from beak 33 33 33 31 37 44 56 52 45 54 46 55 59 59 61 63 The equation of the least-squares regression line for predicting beak heat loss, as a percent of total body heat loss from all sources, from temperature is: (Use decimal notation. Enter the values of the intercept and slope rounded to two…arrow_forwardThe toco toucan, the largest member of the toucan family, possesses the largest beak relative to body size of all birds. This exaggerated feature has received various interpretations, such as being a refined adaptation for feeding. However, the large surface area may also be an important mechanism for radiating heat (and hence cooling the bird) as outdoor temperature increases. Here are data for beak heat loss, as a percent of total body heat loss from all sources, at various temperatures in degrees Celsius. [Note: The numerical values in this problem have been modified for testing purposes.] Temperature (oC)(oC) 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 Percent heat loss from beak 34 32 33 29 38 46 58 50 46 53 44 51 57 58 59 58 The equation of the least-squares regression line for predicting beak heat loss, as a percent of total body heat loss from all sources, from temperature is: (Use decimal notation. Enter the values of the intercept and slope rounded to two…arrow_forward
- A photoconductor film is manufactured at a nominal thickness of 25 mils. The product engineer wishes to increase the mean speed of the film, and believes that this can be achieved by reducing the thickness of the film to 20 mils. Eight samples of each film thickness are manufactured in a pilot production process, and the film speed (in microjoules per square inch) is measured. For the 25-mil film, the sample data result is = 1.15 and 81 = 0.11, while for the 20-mil film, the data yield 2 = 1.06 and 82 = 0.09. Note that an increase in film speed vould lower the value of the observation in microjoules per square inch. (a) Do the data support the claim that reducing the film thickness increases the mean speed of the film? Use a = 0.10 and assume that the two population variances are equal and the underlying population of film speed is normally distributed. What is the P-value for this test? Round your answer to three decimal places (e.g. 98.765). The data the claim that reducing the film…arrow_forwardA researcher is interested in testing the relationship between smoking and BMI (kg/m2) in adults aged 30-45. In order to test this association, the researcher divides smoking into currently more than a pack a day, currently less than a pack a day, and never smokers. The following table represents the BMIs for each participant enrolled by their respective smoking category. Current Smoker (≥1pack/day) Current Smoker (<1 pack/day Never Smoked 26.7 29.4 22.1 29.4 28.6 30.4 24.3 27.4 21.3 28.4 23.2 26.4 21.6 20.1 19.7 27.4 20.6 19.8 26.8 19.7 21.6 36.4 19.6 22.3 31.5 21.6 24.3 27.4 21.5 *Continue as though all assumptions for ANOVA are met. A) Calculate the MSW and MSB for the data represented above. B) Carry out a formal test for a one-way analysis of variance among the groups and interpret your results.arrow_forwardA paper gives data on x = change in Body Mass Index (BMI, in kilograms/meter2) and y = change in a measure of depression for patients suffering from depression who participated in a pulmonary rehabilitation program. The table below contains a subset of the data given in the paper and are approximate values read from a scatterplot in the paper. BMI Change (kg/m²) 0.5 -0.5 0 0.1 0.7 0.8 1 1.5 1.2 1 0.4 0.4 Depression Score Change -1 9 4 4 5 8 13 14 17 18 12 14 The accompanying computer output is from Minitab. Fitted Line Plot Depression score change = 6.512 + 5.472 BMI change 20 S 5.26270 R-Sq 27.16% R-Sq (adj) 19.88% 15- : 10- -0.5 0.0 1.5 Ⓡ S 5.26270 Coefficients Term Coef VIF SE Coef 2.26 T-Value 2.88 P-Value 0.0164 Constant 6.512 BMI change 5.472 2.83 1.93 0.0823 1.00 Regression Equation Depression score change = 6.512 + 5.472 BMI change (a) What percentage of observed variation in depression score change can be explained by the simple linear regression model? (Round your answer to…arrow_forward
- A photoconductor film is manufactured at a nominal thickness of 25 mils. The product engineer wishes to increase the mean speed of the film and believes that this can be achieved by reducing the thickness of the film to 20 mils. Eight samples of each film thickness are manufactured in a pilot production process, and the film speed (in microjoules per square inch) is measured. For the 25-mil film, the sample data result is.x₁ = 1.15 and S₁ = 0.11, while for the 20-mil film, the data yield 2 = 1.06 and s2 = 0.09. Note that an increase in film speed would lower the value of the observation in microjoules per square inch. Do the data support the claim that reducing the film thickness increases the mean speed of the film? Use a = 0.10 and assume that the two population variances are equal and the underlying population of film speed is normally distributed. The appropriate decision for the test is to reject the null hypothesis True Falsearrow_forwardThe following scatterplot shows the mean annual carbon dioxide (CO,) in parts (CO2) per million (ppm) measured at the top of a mountain and the mean annual air temperature over both land and sea across the globe, in degrees Celsius (C). Complete parts a through h on the right. f) View the accompanying scatterplot of the residuals vs. CO2. Does the scatterplot of the residuals vs. CO, show evidence of the violation of any assumptions behind the regression? 16.800 A. Yes, the outlier condition is violated. 16.725 O B. Yes, the linearity and equal variance assumptions are violated. 16.650 C. Yes, the equal variance assumption is violated. 16.575 O D. No, all assumptioris are okay. 16.500 O E. Yes, all the assumptions are violated. 325.0 337.5 350.0 362.5 CO2 (ppm) OF Yes, the linearity assumption is violated. his vear, What mean temperature doesarrow_forwardWrinkle recovery angle and tensile strength are the two most important characteristics for evaluating the performance of crosslinked cotton fabric. An increase in the degree of crosslinking, as determined by ester carboxyl band absorbance, improves the wrinkle resistance of the fabric (at the expense of reducing mechanical strength). The accompanying data on x = absorbance and y = wrinkle resistance angle was read from a graph in the paper "Predicting the Performance of Durable Press Finished Cotton Fabric with Infrared Spectroscopy".† x 0.115 0.126 0.183 0.246 0.282 0.344 0.355 0.452 0.491 0.554 0.651 y 334 342 355 363 365 372 381 392 400 412 420 Here is regression output from Minitab: Predictor Constant absorb S = 3.60498 Coef 321.878 156.711 SOURCE Regression Residual Error Total SE Coef 2.483 6.464 R-Sq = 98.5% DF 1 9 10 SS 7639.0 117.0 7756.0 T 129.64 24.24 0.000 0.000 R-Sq (adj) = 98.3% MS 7639.0 13.0 F P 587.81 (a) Does the simple linear regression model appear to be…arrow_forward
- Wrinkle recovery angle and tensile strength are the two most important characteristics for evaluating the performance of crosslinked cotton fabric. An increase in the degree of crosslinking, as determined by ester carboxyl band absorbance, improves the wrinkle resistance of the fabric (at the expense of reducing mechanical strength). The accompanying data on x = absorbance and y = wrinkle resistance angle was read from a graph in the paper "Predicting the Performance of Durable Press Finished Cotton Fabric with Infrared Spectroscopy".t 半 0.115 0.126 0.183 0.246 0.282 0.344 0.355 0.452 0.491 0.554 0.651 334 342 355 363 365 372 381 392 400 412 420 Here is regression output from Minitab: Predictor Coef SE Coef P Constant 321.878 2.483 129.64 0.000 absorb 156.711 6.464 24.24 0.000 S = 3.60498 R-Sq = 98.5% R-Są (adj) - 98.3% SOURCE DF MS F P Regression 1 7639.0 7639.0 587.81 0.000 Residual Error 9 117.0 13.0 Total 10 7756.0 (a) Does the simple linear regression model appear to be…arrow_forwardWrinkle recovery angle and tensile strength are the two most important characteristics for evaluating the performance of crosslinked cotton fabric. An increase in the degree of crosslinking, as determined by ester carboxyl band absorbance, improves the wrinkle resistance of the fabric (at the expense of reducing mechanical strength). The accompanying data on x = absorbance and y = wrinkle resistance angle was read from a graph in the paper "Predicting the Performance of Durable Press Finished Cotton Fabric with Infrared Spectroscopy".t x 0.115 0.126 0.183 0.246 0.282 0.344 0.355 0.452 0.491 0.554 0.651 y 334 342 355 363 365 372 381 400 392 412 420 Here is regression output from Minitab: Predictor Constant absorb S = 3.60498 Coef 321.878 156.711 SOURCE Regression Residual Error Total R-Sq= 98.5% DF SE Coef 2.483 6.464 1 9 10 SS 7639.0 117.0 7756..0 T 129.64 24.24 P 0.000 0.000. R-Sq (adj) 98.3% MS 7639.0 13.0 F 587.81 (a) Does the simple linear regression model appear to be appropriate?…arrow_forwardplease answer the question!arrow_forward
arrow_back_ios
SEE MORE QUESTIONS
arrow_forward_ios
Recommended textbooks for you
- Linear Algebra: A Modern IntroductionAlgebraISBN:9781285463247Author:David PoolePublisher:Cengage LearningGlencoe Algebra 1, Student Edition, 9780079039897...AlgebraISBN:9780079039897Author:CarterPublisher:McGraw Hill
Linear Algebra: A Modern Introduction
Algebra
ISBN:9781285463247
Author:David Poole
Publisher:Cengage Learning
Glencoe Algebra 1, Student Edition, 9780079039897...
Algebra
ISBN:9780079039897
Author:Carter
Publisher:McGraw Hill
Hypothesis Testing using Confidence Interval Approach; Author: BUM2413 Applied Statistics UMP;https://www.youtube.com/watch?v=Hq1l3e9pLyY;License: Standard YouTube License, CC-BY
Hypothesis Testing - Difference of Two Means - Student's -Distribution & Normal Distribution; Author: The Organic Chemistry Tutor;https://www.youtube.com/watch?v=UcZwyzwWU7o;License: Standard Youtube License