PROBABILITY & STATS FOR ENGINEERING &SCI
9th Edition
ISBN: 9781285099804
Author: DEVORE
Publisher: CENGAGE L
expand_more
expand_more
format_list_bulleted
Question
Chapter 13.5, Problem 64E
a.
To determine
Check if any observations are influential.
b.
To determine
Identify whether the second observation is influential or not.
c.
To determine
Identify whether the fourth observation is influential or not.
Expert Solution & Answer
Want to see the full answer?
Check out a sample textbook solutionStudents have asked these similar questions
A group of researchers studied the effect of acid rain on wildlife and collected n = 12 samples from streams in different States. They recorded the pH (X) of
the water (i.e. units above pH 7), and the BCI, a measure of biological diversity (Y). The data obtained is summarized below.
DATA:
Observation
1
2
3
4
5
6
7
8
9
10
11
12
pH above 7 (X)
0.67
0.70
0.93
0.95
1.09
1.01
1.29
1.24
1.41
1.56
1.73
1.80
Units of BCI (Y)
14.4
20.9
16.2
25.0
18.9
19.8
20.7
22.1
23.9
24.9
27.6
29.7
Find the correlation coefficient between pH and BCI (round to the nearest hundredth; place your answer in the box below)
pan's high population density has resulted in a multitude of resource-usage problems. One especially serious difficulty concerns waste removal. An article reported the development of a new compression machine for processing sewage sludge. An important part of the investigation involved relating the moisture content of compressed pellets (y, in %) to the machine's filtration rate (x, in kg-DS/m/hr). The following data was read from a graph in the article.
x
125.8
98.1
201.4
147.3
145.9
124.7
112.2
120.2
161.2
178.9
159.5
145.8
75.1
151.5
144.2
125.0
198.8
133.9
y
77.9
76.8
81.5
79.8
78.2
78.3
77.5
77.0
80.1
80.2
79.9
79.0
76.9
78.2
79.5
78.1
81.5
71.0
(a) Determine the slope and intercept of the estimated regression line. (Round your answers to 5 decimal places, if needed.)slope: intercept: (b) Does there appear to be a useful linear relationship? Carry out a test using the ANOVA approach and a significance level of 0.05. State the appropriate null and alternative hypotheses.…
Suppose you are interested in uncovering the relationship between snowfall (in inches) in the month of December and the flow rate of Yosemite Falls in April (in cubic meters per second) over the span of years from 2005 to 2010 (inclusive). You observe the following snowfall and Yosemite Falls flowrate data: December Snowfall (X)=[16,19,18,16,20,17] and April Flowrate (Y)=[22,23,21,18,26,21]. What is β₁?
Group of answer choices
About 0.251
About 1.325
About 0.803
About 1.310
None of the above are close
Chapter 13 Solutions
PROBABILITY & STATS FOR ENGINEERING &SCI
Ch. 13.1 - Suppose the variables x = commuting distance and y...Ch. 13.1 - Prob. 2ECh. 13.1 - Prob. 3ECh. 13.1 - Prob. 4ECh. 13.1 - As the air temperature drops, river water becomes...Ch. 13.1 - The accompanying scatterplot is based on data...Ch. 13.1 - Prob. 7ECh. 13.1 - Prob. 8ECh. 13.1 - Consider the following four (x, y) data sets; the...Ch. 13.1 - a. Show that i=1nei=0 when the eis are the...
Ch. 13.1 - Prob. 11ECh. 13.1 - Prob. 12ECh. 13.1 - Prob. 13ECh. 13.1 - If there is at least one x value at which more...Ch. 13.2 - No tortilla chip aficionado likes soggy chips, so...Ch. 13.2 - Polyester fiber ropes are increasingly being used...Ch. 13.2 - The following data on mass rate of burning x and...Ch. 13.2 - Failures in aircraft gas turbine engines due to...Ch. 13.2 - Prob. 19ECh. 13.2 - Prob. 20ECh. 13.2 - Mineral mining is one of the most important...Ch. 13.2 - Prob. 22ECh. 13.2 - Prob. 23ECh. 13.2 - Kyphosis refers to severe forward flexion of the...Ch. 13.2 - Prob. 25ECh. 13.3 - The following data on y 5 glucose concentration...Ch. 13.3 - The viscosity (y) of an oil was measured by a cone...Ch. 13.3 - Prob. 29ECh. 13.3 - The accompanying data was extracted from the...Ch. 13.3 - The accompanying data on y 5 energy output (W) and...Ch. 13.3 - Prob. 32ECh. 13.3 - Prob. 33ECh. 13.3 - The following data resulted from an experiment to...Ch. 13.3 - The article The Respiration in Air and in Water of...Ch. 13.4 - Cardiorespiratory fitness is widely recognized as...Ch. 13.4 - A trucking company considered a multiple...Ch. 13.4 - Let y = wear life of a bearing, x1 = oil...Ch. 13.4 - Let y = sales at a fast-food outlet (1000s of ),...Ch. 13.4 - The article cited in Exercise 49 of Chapter 7 gave...Ch. 13.4 - The article A Study of Factors Affecting the Human...Ch. 13.4 - An investigation of a die-casting process resulted...Ch. 13.4 - Prob. 43ECh. 13.4 - The accompanying Minitab regression output is...Ch. 13.4 - The article Analysis of the Modeling Methodologies...Ch. 13.4 - A regression analysis carried out to relate y =...Ch. 13.4 - Efficient design of certain types of municipal...Ch. 13.4 - An experiment to investigate the effects of a new...Ch. 13.4 - Prob. 49ECh. 13.4 - Prob. 50ECh. 13.4 - The article Optimization of Surface Roughness in...Ch. 13.4 - Utilization of sucrose as a carbon source for the...Ch. 13.4 - Prob. 53ECh. 13.4 - Prob. 54ECh. 13.5 - The article The Influence of Honing Process...Ch. 13.5 - Prob. 56ECh. 13.5 - In the accompanying table, we give the smallest...Ch. 13.5 - Prob. 58ECh. 13.5 - Prob. 59ECh. 13.5 - Pillar stability is a most important factor to...Ch. 13.5 - Prob. 61ECh. 13.5 - Prob. 62ECh. 13.5 - Prob. 63ECh. 13.5 - Prob. 64ECh. 13 - Curing concrete is known to be vulnerable to shock...Ch. 13 - Prob. 66SECh. 13 - The article Validation of the Rockport Fitness...Ch. 13 - Feature recognition from surface models of...Ch. 13 - Air pressure (psi) and temperature (F) were...Ch. 13 - An aeronautical engineering student carried out an...Ch. 13 - An ammonia bath is the one most widely used for...Ch. 13 - The article An Experimental Study of Resistance...Ch. 13 - The accompanying data on x = frequency (MHz) and y...Ch. 13 - Prob. 74SECh. 13 - Prob. 75SECh. 13 - The article Chemithermomechanical Pulp from Mixed...Ch. 13 - Prob. 77SECh. 13 - Prob. 78SECh. 13 - Prob. 79SECh. 13 - Prob. 80SECh. 13 - Prob. 81SECh. 13 - Prob. 82SECh. 13 - Prob. 83SE
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
- What does the y -intercept on the graph of a logistic equation correspond to for a population modeled by that equation?arrow_forwardCan the average rate of change of a function be constant?arrow_forwardSuppose you are interested in uncovering the relationship between snowfall (in inches) in the month of December and the flow rate of Yosemite Falls in April (in cubic meters per second) over the span of years from 2005 to 2010 (inclusive). You observe the following snowfall and Yosemite Falls flowrate data: December Snowfall (X)=[16,19,18,16,20,17] and April Flowrate (Y)=[22,23,21,18,26,21]. What is TSS? About 4.37 About 6.27 About 13.33 About 22.46 None of the above are closearrow_forward
- Consider the following regression model, log(CON)=Bo + B,INC + B2INC2 + B3PRICE + u Where CON = Household consumption expenditure INC = Household income INC? = Household income squared PRICE = General price level Regression Estimates- Dependent variable: log(CON) Variables Coefficient Estimates and (Standard Errors) Equation 1 Equation 2 1.2136 (0.1961) Constant 1.5731 (0.0849) INC 0.0029 (0.001) INC? 0.0013 (0.00051) PRICE -0.0081 -0.0095 (0.0035) (0.0017) N (Number of Observations) SSR (Sum of Squared Residuals) R2 500 500 145.63 184.09 0.52 0.45 You wanted to test whether income has significant effect on household consumption. Which of the following represents the approximate critical value for this test at 1% level of significance? Critical value of F with 1% level of significance and 3 and 496 df is: F = 2.60 Critical value of t with 1% level of significance and 2 and 498 df is: F = 2.326 Critical value of F with 1% level of significance and 2 and 496 df is: F = 4.61 Critical…arrow_forwardA paper gives data on x = change in Body Mass Index (BMI, in kilograms/meter) 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 0.7 0.5 0.1 0.8 1 1.5 1.2 1 0.4 0.4 Depression Score Change -1 4 4 8 13 14 16 18 12 14 The accompanying computer output is from Minitab. Fitted Line Plot Depression score change = 6.598 + 5.327 BMI change 20- 5.10254 R-Sq R-Sq (adj) 20.06% 27.32% 15- 10- 5- 0- -0.5 0.0 0.5 1.0 1.5 BMI change R-sq 5.10254 27.32% Coefficients Term Coef SE Coef T-Value P-Value VIF Constant 6.598 2.19 3.01 0.0132 BMI change 5.327 2.75 1.94 0.0812 1.00 Regression Equation Depression score change = 6.598 + 5.327 BMI change (a) What percentage of observed variation in depression score change can be explained by the simple linear regression model?…arrow_forwardThe data in the following table relate grams plant dry weight (Y) to percent soil organic matter (X1) and kilograms of supplemental soil nitrogen added per 1000 square meters (X2). Y 78.5 X1 X2 2.6 1 2.9 5.6 74.3 104.3 | 11 87.6 11 5.2 95.9 5.5 109.2 | 11 102.7 | 3 3.1 7 7.1 Compute X'X and X'Y.arrow_forward
- Ocean currents are important in studies of climate change, as well as ecology studies of dispersal of plankton. Drift bottles are used to study ocean currents in the Pacific near Hawaii, the Solomon Islands, New Guinea, and other islands. Let x represent the number of days to recovery of a drift bottle after release and y represent the distance from point of release to point of recovery in km/100. The following data are representative of one study using drift bottles to study ocean currents. Σx = 476, Σy = 87.1, Σx2 = 62,290, Σy2 = 2046.87, Σxy = 11121.3,and r ≈ 0.94367. x days 72 76 32 91 205y km/100 14.7 19.6 5.3 11.7 35.8 a) Use a 1% level of significance to test the claim ? > 0.(Use 2 decimal places.)t =critical t= b) Find the predicted distance (km/100) when a drift bottle has been floating for 60 days. (Use 2 decimal places.)________ km/100 c) Find a 90% confidence interval for your prediction of part (d). (Use 1 decimal place.)lower limit = _____…arrow_forwardThe materials handling manager of a manufacturing company is trying to forecast the cost of maintenance for the company's fleet of over-the-road tractors. The manager believes that the cost of maintaining the tractors increases with their age. The following data was collected: Age (years) 5.5 where Y = Yearly maintenance cost in dollars and X = Age in years. 5.5 5.5 5.0 5.0 5.0 6.0 6.0 6.5 Yearly Maintenance Cost (S) 1,319 1,749 1,733 1,195 1,423 1,381 1,590 2,222 1,687 Age (years) 5.0 1.5 1.5 Y = 7.0 7.0 2.0 2.0 2.0 Yearly Maintenance Cost ($) 1,894 863 882 a. Use POM for Windows' least squares-linear regression module to develop a relationship to forecast the yearly maintenance cost based on the age of a tractor. (Enter your responses rounded to three decimal places and include a minus sign if necessary.) 1,464 2,073 1,678 1,166 1,249arrow_forwardA paper gives data on x = change in Body Mass Index (BMI, in kilograms/meter) 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) 0.7 0.8 1 1.5 1.2 1 0.4 0.4 0.5 -0.5 0.1 Depression Score Change -1 | 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 5.26270 20 - R-Sq R-Sq (adj) 19.88% 27.16% 15- 10-. 5- -0.5 0.0 0.5 1.0 1.5 BMI change 5.26270 27.166 Coefficients Term Coef SE Coef T-Value P-Value VIF Constant 6.512 2.26 2.88 0.0164 BMI change 5.472 2.83 1.93 0.0823 1.00 Regression Equation Depression score change = 6.512 + 5.472 EMI change (a) What percentage of observed variation in depression score change can be explained by the simple linear regression model?…arrow_forward
- The data in the accompanying table is from observing the count of bacteria. The COUNT (Y) is recorded in 1000's of a BACTERIA (X₁) and the growth rate, RATE (X₂) of a type of bacteria. Below is the data set to be used for analysis. Y COUNT 9 9.1 10.2 11.3 12.2 10.6 X₁ BACTERIA A A C B B C 2.1. Change the dataset into a usable format for modelling. X₂ RATE 0.15 014 0.08 0.12 0.16 0.01arrow_forwardAn article in the journal Air and Waste (Update on Ozone Trends in California's South Coast Air Basin, Vol. 43, 1993) investigated the ozone levels in the South Coast Air Basin of California for the years 1976-1991. The author believes that the number of days the ozone levels exceeded 0.20 ppm (the response) depends on the seasonal meteorological index, which is the seasonal average 850-millibar Temperature (the predictor). The following table gives the data. Year Index 1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 Days 91 105 106 108 88 91 58 82 81 65 61 48 61 43 33 36 16.7 17.1 18.2 18.1 17.2 18.2 16.0 17.2 18.0 17.2 16.9 17.1 18.2 17.3 17.5 16.6 (a) Construct a scatter diagram of the data. (b) Estimate the prediction equation. (c) Test for significance of regression. (d) Calculate the 95% CI and PI on for a seasonal meteorological index value of 17. Interpret these quantities.arrow_forwardWhen water flows across farmland, some soil is washed away, resulting in erosion. An experiment was conducted to investigate the effect of the rate of water flow (liters per second) on the amount of soil (kilograms) washed away. The data are given in the following table: Flow rate 0.31 0.85 1.26 2.47 3.75 Eroded soil 0.82 1.95 2.18 3.01 6.07 Let xx represent the flow rate variable and yy represent the variable for soil eroded. Then \bar x = 1.73, s_x = 1.38, \bar y = 2.81, s_y = 1.99xˉ=1.73,sx=1.38,yˉ=2.81,sy=1.99 Use this to complete the following calculation of the correlation coefficient for these data. r = \frac{1}{n-1}\left[\left(\frac{x_1 - \bar x}{s_x}\right)\left(\frac{y_1 - \bar y}{s_y}\right) + \left(\frac{x_2 - \bar x}{s_x}\right)\left(\frac{y_2 - \bar y}{s_y}\right) + \cdots + \left(\frac{x_n - \bar x}{s_x}\right)\left(\frac{y_n - \bar y}{s_y}\right)\right]r=n−11[(sxx1−xˉ)(syy1−yˉ)+(sxx2−xˉ)(syy2−yˉ)+⋯+(sxxn−xˉ)(syyn−yˉ)]…arrow_forward
arrow_back_ios
SEE MORE QUESTIONS
arrow_forward_ios
Recommended textbooks for you
- Algebra & Trigonometry with Analytic GeometryAlgebraISBN:9781133382119Author:SwokowskiPublisher:Cengage
Algebra & Trigonometry with Analytic Geometry
Algebra
ISBN:9781133382119
Author:Swokowski
Publisher:Cengage
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