A project schedule has the following characteristics as shown in TableActivityNameTimeActivityNameTime (days)1-2A45-6G41-3B15-7H82-4C16-8I13-4D17-8J23-5E68-10K54-9F59-10L7i. Construct PERT network.ii. Compute TE and TL foreach activity.iii. Find the critical path.

Step 1: Construct PERT NetworkNodes represent events, and directed edges represent activities.Each…

Answered: A project schedule has the following…

Advanced Engineering Mathematics

10th Edition

ISBN:9780470458365

Author:Erwin Kreyszig

Publisher:Erwin Kreyszig

Chapter2: Second-order Linear Odes

Section: Chapter Questions

Problem 1RQ

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Northern flying squirrels eat lichen and fungi, which makes for a relatively low quality diet. The authors of the paper "Nutritional Value and Diet Preference of Arboreal Lichens and Hypogeous Fungi for Small Mammals in the Rocky Mountains" + measured nitrogen intake and nitrogen retention in six flying squirrels that were fed the fungus Rhizopogon. Data read from a graph that appeared in the paper are given in the table below. (The negative value for nitrogen retention for the first squirrel represents a net loss in nitrogen.) Nitrogen Intake, x (grams) 0.03 0.10 0.07 0.06 0.07 0.25 (a) Construct a scatterplot of these data. y 0.10 0.05 -0.05 y 0.10 0.05 -0.05 0.05 0.10 g 0.05 0.10 Nitrogen Retention, y (grams) -0.04 0.00 0.01 0.01 0.04 0.11 g + 0.15 0.20 0.25 0.15 ●● 0.20 0.25 X y 0.10 0.05 -0.05 y 0.10 0.05 -0.05 (b) Find the equation of the least-squares regression line. (Round your values to five decimal places.) ŷ = 0.05 0.10 0.15 0.20 0.25 0.05 0.10 0.15 0.20 0.25 (c) Based on…
please do this by hand, not in excel
Ernesto is a web developer who is looking to determine which of two types of advertisements are the most cost effective. He suspects that advertisements with animations generate more clicks than advertisements without animations but wants to confirm his intuition before he starts recommending advertisements with animations to his clients. Ernesto creates advertisements with animations for 12 different products and then creates advertisements without animations for those same products. Then he measures the click-through rate for those advertisements. The data are provided below (given as percentages of total visitors to the site who clicked on the advertisement). Assume that the conditions required for this hypothesis test are satisfied. Use a calculator to test the paired data, where α=0.01. Compute the sample differences d using d=Without−With. Which of the following statements are accurate for this hypothesis test in order to evaluate the claim that the true mean difference between…
or Module 10: MTH X A ALEKS-Paige Bohnert - Learn X + www-awu.aleks.com/alekscgi/x/lsl.exe/10_u-IgNslkr7j8P3jH-IQikyJ-bCdyps2nJxZ_kvzXfsB26H8ZG13mFz8Trt0JQE3aRS7wyovsTkW6JXUeyLfp-s_IZm5Nj... ☆ esc Suppose that the lifetimes of tires of a certain brand are normally distributed with a mean of 75,000 miles and a standard deviation of a miles. These tires come with a 65,000-mile warranty. The manufacturer of the tires can adjust o during the production process, but the adjustment of o is quite costly. The manufacturer wants to set o once and for all so that only 5% of the tires will fail before warranty expires. Find the standard deviation to be set. Carry your intermediate computations to at least four decimal places. Round your answer to at least one decimal place. O RANDOM VARIABLES AND DISTRIBUTIONS Normal distribution: Finding a mean or standard deviation tion 1 miles Q A Explanation Z 2 S 6 MAGAHAUDDUBAA X Check H command X 3 80 F3 WERTY D $ с 4 % F 5 V MacBook Air G B H & ← F7 7 U N…
Osteoporosis is a degenerative disease that primarily affects women over the age of 60. A research analyst wants to forecast sales of StrongBones, a prescription drug for treating this debilitating disease. She uses the model Sales = β0 + β1Population + β2Income + ε, where Sales refers to the sales of StrongBones (in $1,000,000s), Population is the number of women over the age of 60 (in millions), and Income is the average income of women over the age of 60 (in $1,000s). She collects data on 38 cities across the United States and obtains the following regression results: Coefficients StandardError t Stat p-Value Intercept 10.35 4.02 2.57 0.0199 Population 8.47 2.71 3.12 0.0062 Income 7.62 6.63 1.15 0.2661 a. What is the sample regression equation? (Enter your answers in millions rounded to 2 decimal places.) b-1. Interpret the coefficient of population. multiple choice 1 As the number of women over the age of 60 increases by 1 million, sales of StrongBones…
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Consider a model with an interaction term between being female and being married. The dependent variable is the log of the hourly wage: log(wage) = 0.151 - 0.038 female + 0.1 married - 0.301 female* married + 0.079 educ + 0.027 exper+0.029 tenure (0.072) (0.056) (0.055) (0.007) (0.005) (0.007) n = 536, R2 = 0.461 Numbers in parantheses are standard errors of coefficients. Given the estimation result and the observation number fill in the blanks below which aim at discussing the statistical significance of variables. The test statistic of the interaction term is The critical value at 1% significance level is Then the interaction term statistically significant at 1% significance level. (Hint: to fill the blank make a choice between "is" and "is not".)
The data for lab 1-2 was created based upon the paper by the STARSproject and modified by Dr. Hole. Fast food meals are typically high incalories, fat, sodium and cholesterol, which are known to increase the riskof obesity and diabetes. Researchers found that unhealthy ingredients,large portion size, low cost, and convenience make fast food cause obesity.The dataset provided by Dr. Hole is derived from a very large consumersurvey conducted by market researchers at Milward Brown. The survey wascarried out using a CATI (computer Aided Telephone Interviewing)methodology. Random digit telephone numbers were dialed and theperson answering was asked “Do you buy fast food nowadays?” Only thoseresponding “Yes” were then surveyed. In class, we already examined thedatasets, found results, and drew tables to answer several questions.Dataset: Lab 1-2.savRequirements: For your 1-2 assignment, please provide scholarly tables and your findings/thoughts with reasonable justification for the following…
Use 3 point graphing tool
Why won't the whiteboard image show up?
9. Find the equation y = ax² + bx + c of the least-square parabola that best fits the given data points (-1,0), (0,3), (1,3), (2,5), and (3,9).
A college bookstore must order books two months before each semester starts. They believe that the number of books that will ultimately be sold for any particular course is related to the number of students registered for the course when the books are ordered. They would like to develop a bestfitting line to predict how many books to order. From past records, the bookstore obtains the number of students registered, X, and the number of books actually sold for a course, Y , for 12 different semesters.A scatterplot of the data along with the best fitting line is presented below. a. The correlation between the two variables is r = .89. Calculate and interpret the value of r2.b. The equation for the best fitting line is Y = 9.30 + 0.673X. Explain and interpret the value of 9.30.c. How many books should the store order for a class of 50 students? Would you trust this prediction?

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