11.12 Estimating repair and replacement costs of water pipes.Refer to Exercise 2.124 (p. 107). A team of civil engineersused simple linear regression analysis to model the ratioof repair to replacement cost of commercial pipe as afunction of the pipe's diameter. (IHS Journal of HydraulicEngineering, September 2012.)a. In this study, identify the dependent and independentvariables.b. Explain why a probabilistic model is more appropriatethan a deterministic model.c. Write the equation of the straight-line, probabilistic model.

Given : a) The Independent variable is the explanatory variable or the predictor variable which…

Answered: 11.12 Estimating repair and replacement…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

See similar textbooks

Similar questions

4. The following regression is fitted using variables identified that could be related to tuition charges ($) of a university. TUITION = a+ B ACCEPT + y MSAT + 1 VSAT Where ACCEPT = the percentage of applicants that was accepted by the university, MSAT = Median Math SAT score for the freshman class and VSAT = Median English SAT score for the freshman class. The data was processed using MNITAB and the following is an extract of the output obtained: Predictor Coef StDev T P Constant -26780 6115 -4.38 0.000 ACCEPT 116.00 37.17 * 0.003 MSAT -4.21 14.12 VSAT 70.85 15.77 -0.30 4.49 0.767 ** S = 2685 R-Sq = 69.6% Analysis of Variance R-Sq (adj) = 67.7% Source DF SS MS F P Regression 3 808139371 Residual Error 49 353193051 269379790 7208021 37.37 0.000 Total 52 1161332421 a) Write out the regression equation. b) State the dependent and independent variable(s) c) Fill in the blanks identified by ** and ****. d) Is B significant, at the 10% level of significance? e) State one limitation of using…
ABC Company is exploring different prediction models that can be used to forecast indirect labor costs. One independent variable under consideration is machine hours. Following are matching observations on indirect labor costs and machine hours for the past six months: Machine hours Indirect labor costs P20,000 P24,000 P17,000 P22,000 P13,000 P14,000 Month 1 300 400 240 4 370 5 200 6 225 Using linear regression analysis, the estimated variable indirect labor cost per machine hour is closest to: P35.62 P15.44 P52.71 P58.31
A market study found that the sales for a firm were related to advertising expenditure, as follows: Advertising Expenditure (Kshs ‘000’) Sales (Kshs ‘000’) 0 13 1 16 2 14 3 22 4 17 5 21 6 26 Required Draw a scatter diagram with the line of best fit to show the relationship. Determine the regression line equation for estimating the sales for a given level of advertising expenditure What is the estimated sale in thousand, if no advertising expenditure is incurred?
q13
A retail company wants to understand the factors that impact its sales revenue. The company has collected data on the following variables for the past 5 months: Total sales revenue (Y), Average store foot traffic (XI), and Marketing budget (X3). Develop a multiple linear regression model to predict that, what is the impact of average store foot traffic, and marketing budget on total sales revenue for the retail company. The data is summarized in Table 4. Table 4 Average Store foot traffic (X1) Sales Revenue (Y) 50$ 5 130S 45$ 48$ 7 6 120$ 200$ 60$ 708 5 4 Marketing Budget (X2) 130$ 250$ Note: Average Store foot traffic is the average number of people enter in the store per minute
18)The regression equation is intended to be the “best fitting” straight line for a set of data. Whatis the criterion for “best fitting”?
In order to explain the U.S. defense budget, the following variables are considered. Data from 1962-1981 is collected. Variable Definition Y Defense budget-outlay for year t, $ billions X2 GNP for year t, $ billions X3 U.S. military sales/assistance in year t, $ billions X4 Aerospace industry sales, $ billions Dependent Variable: Y Method: Least Squares Date: 11/22/21 Time: 11:20 Sample: 1962 1981 Included observations: 20 Variable Coefficient Std. Error t-Statistic Prob. X2 0.016703 0.007017 2.380261 0.0301 X3 -0.696174 0.453978 -1.533497 0.1447 X4 1.467729 0.277608 5.287047 0.0001 22.77514 3.311695 6.877186 0.0000 R-squared 0.971088 Mean dependent var 83.86000 Adjusted R-squared 0.965667 S.D. dependent var 28.97771 S.E. of regression Sum squared resid 5.369339 Akaike info criterion 6.376143 461.2769 Schwarz criterion 6.575290 Log likelihood -59.76143 Hannan-Quinn criter. 6.415019 F-statistic 179.1337 Durbin-Watson stat 0.676777 Prob(F-statistic) 0.000000
A group of Maternal and Child Health public health practitioners are interested in the relationship between depression and a number of health outcomes. Suppose the research team gathers information on a group of participants, and constructs a multiple linear regression model looking at the relationship between depression and household income dichotomized as above and below the federal poverty line controlling for a number of potential confounders. The following is a computerized output displaying the results of their analysis. Parameter Estimate Standard Error t Value Pr > |t| Intercept 0.2617346843 0.09209917 2.84 0.0046 Income (1/0) -.1962038300 0.04574793 -4.29 <.0001 Race (W or AA) -.0320329506 0.03900447 -0.82 0.4118 bmicontinuous 0.0051185980 0.00216986 2.36 0.0186 Alcohol (Y/N) -.0088735044 0.03090631 -0.29 0.7741 A) What are the independent and dependent variables? B) Which potential…
Scientific mass appraisal is a technique in which linear regression methods applied to the problem of property valuation. The objective in the Scientific Mass Appraisal is to predict the sale price of a home from selected characteristics of the building and taxes paid on the buildingTwenty four observations were obtained. The list of variables is also given.Answer the following questions, in each case justifying your answer by appropriate analyses.(a) In a fitted regression model that relates the sale price to taxes and building characteristics, would you include all the variables?(b) A veteran real estate agent has suggested that local taxes, number of rooms and age of the house would adequately describe the sale price . Do you agree ?(c) A real estate expert who who was brought into the project reasoned as follows:“ The selling price of a home is determined by its desirability and this is certainly a function of the physical characteristic of the building. This overall assessment is…
3. Wine Participant magazine has collected average price per bottle for the prestigious Chateau Le Thundebird bordeaux for different vintages (years). The data appears in the table below. year of bottling price a) draw the scatter diagram showing how wine price varies by vintage year b) use the most appropriate regression equation to determine the relationship between year of bottling (age) and price. c) what is the explanatory power (RSQ) of that equation d) determine the predicted price of a bottle of this wine for the 2017 vintage. 2009 36 2010 40 2011 51 2012 60 2013 68 2014 72 2015 70 2016 65 2018 51 2019 44 2020 39
Parameter estimates Direct effects Freedom Generosity Family Life Expectancy Note. Delta method Indirect effects Freedom Freedom Generosity Generosity Family Family Total effects Freedom Generosity Estimate Std. Error Freedom Generosity Family Life Expectancy 1.476 0.381 1.118 1.289 GDP per Capita Happiness Score Happiness Score Government Corruption CDP per Capita Government Corruption GDP per Capita Government Corruption GDP per Capita Government Corruption Happiness Score Happiness Score Life Expectancy Happiness Score Happiness Score Life Expectancy Note. Delta method standard errors, normal theory confidence intervals, ML estimator. Happiness Score Happiness Score Happiness Score Happiness Score standard errors, normal theory confidence intervals, ML estimator. 1111 0.335 0.322 0.197 0.314 Estimate Std. Error 1.828 0.253 1.402 2.278 z-value Estimate 0.352 -0.128 0.284 0.989 Р 4.409 <.001 1.183 0.237 5.661 <.001 4.102 <.001 Happiness Score Happiness Score 0.331 0.332 0.194 0.227…

Recommended textbooks for you

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

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

SEE MORE TEXTBOOKS