5-17. The annual production statistics for the West Oakvale (Sligo)Field are given below.DateStock-tank LiquidAnnual ProductionGravity,*APIOil, STB Water, STB Gas, Mscf1982198319841985465047484,6462,6081,3501,4301,6621,1101,4841,1771,2159321,122665463,265342,075241,048221,020267,106178,9511986*19875051*through August 1987Classify this reservoir fluid.

Answered: Image /qna-images/answer/9760a205-76d2-4990-ac56-3ba3fcb02ce5.jpg

Answered: 5-17. The annual production statistics…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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EXAMPLE A civil engineer is interested in determining whether four different methods of estimating flood flow frequency pro- duce equivalent estimates of peak discharge when applied to the same watershed. Each procedure is used six times on the watershed, and the resulting discharge data (in cubic feet per second) are shown Estimation Method Observations 1 0.34 0.12 1.23 0.70 1.75 0.12 2 0.91 2.94 2.14 2.36 2.86 4.55 3 6.31 8.37 9.75 6.09 9.82 7.24 4 17.15 11.82 10.95 17.20 14.35 16.82
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The following data was reported on total Fe for four types of iron formation (1 carbonate, 2 silicate, 3 magnetite, 4 hematite). 1: 21.0 28.1 27.8 27.0 27,8 25.2 25.3 27.1 20.5 31.5 2: 26.2 24.0 26.2 20.2 23.6 34.0 17.1 26.8 23.7 25.0 3: 29.6 34.0 27.5 29.4 26.4 26.2 29.9 29.5 30.0 35.5 4: 37.1 44,2 34.1 30.3 31.8 33.134.1 32.9 36,3 25.3 A USE SALT Carry out an analysis of variance F test at significance level 0.01. State the appropriate hypotheses. H at least two 's are equal Ho Hi= Ha = H4 H at least two 's are unequal O Ho = = 4 H al four s are unequal H all four 's are equal
Ims.tu.edu.sa قائمة القراءة. Remaining Time: 34 minutes, 24 seconds. v Question Completion Status: QUESTION 1 "Suppose X has an exponential distribution with ß=1/2 , then P (X2 2) is " 0.3988 O 0.0183 0.4786 O 0.2916 QUESTION 2 "Suppose X has an exponential distribution with ß=1/4 , then P (Xs1.) is " O 0.9817 O 0.3246 O 0.4105 O 0.5116 QUESTION 3
3. Exercise 15.38. Cooking vegetables in different pots. Let's first concentrate on the 12 observations for the vegetable dish. Does the vegetable dish vary in iron content when cooked in aluminum, clay, and iron pots? Pot Rep Dish Aluminum 1 Aluminum 2 Aluminum 3 Aluminum 4 1 Clay Clay Clay Clay Iron Iron Iron Iron 3 4 Iron content vegetable 1.03 vegetable 1.53 vegetable 1.07 vegetable 1.30 vegetable 1.55 vegetable 0.79 vegetable 1.68 vegetable 3.52 vegetable 2.45 vegetable 2.99 vegetable 2.80 vegetable 2.92 (a) Check the conditions for one-way ANOVA. Which requirements are a bit dubious in this setting? (b) Instead of using ANOVA, using a nonparametric method. Summarize your conclusions about the effect of pot material on the iron content of the vegetable dish.
15. (Percentile, median) The pth percentile of a sample is a number Q, such that at least p% of the sample values are smaller than or equal to Q, and also at least (100 – p)% of those values are larger than or equal to Q. If there is more than one such number (in which case there will be an interval of them), the pth percentile is defined as the average of the numbers (midpoint of that interval). In particular, Q50 is called the middle quartile or median and is denoted by r. Find for the sample in Table 24.2 (Sec. 24.3).
Assignment: Analyze Filling Line Problems Using Control Charting Attached Files: File Filling line example for X-bar & control chart.xlsxOpen this document with ReadSpeaker docReader (13.354 KB) Using the provided data, calculate the control limits (X-bar and r-chart, Capability Index, create a control chart, and calculate the percentage of units that are expected to be out of spec (z-value). Show your work A quick way to do the percents part of the filling line problem (you know, the percent underfilled, the percent overfilled, etc.), is to use Excel's norm.dist function rather than looking it up on a printed Z table. Use the norm.dist excel function with the LSL in the first position in the parameter list. Norm.dist gives you the left side return from the Z table. "Excel offers you the NORM.DIST statistical function for working with normal distributions. The NORM.DIST function calculates the probability that variable X falls below or at a specified value"…
Given the following figures 5,12,6,3,8,11,15,9,12,15 calculate a measure of relative Kurtosis round to 2 decimals I
10. An engineering study was undertaken to determine the optimum thickness of aluminum to be used to construct cans to be used for cat food. Cans made of aluminum of thickness 2.10 mm and 1.90 mm were tested to determine the maximum load each would sustain before collapsing. The sample data is summarized below. Use a = 0.05 to test the claim that the thicker cans are stronger (will withstand a higher load). 2.10 mm thick 1.90 mm thick sample size 175 170 mean maximum load (kg) 28.18 26.71 standard deviation of maximum load (kg) | 2.78 2.21
A researcher studies water clarity at the same location in a lake on the same dates during the course of a year and repeats the measurements on the same dates 5 years later. The researcher immerses a weighted disk painted black and white and measures the depth (in inches) at which it is no longer visible. The collected data is given in the table below. Complete parts (a) through (c) below Observation 3 4 Date 1/25 3/19 5/30 7/3 9/13 11/7 Initial Depth, X, 57.1 67.5 70.3 41.2 70.9 44.3 Depth Five Years Later, Y, 54.6 67.7 67.4 41.9 66.6 47.6 a) Why is it important to take the measurements on the same date? O A. Those are the same dates that all biologists use to take water clarity samples. O B. Using the same dates maximizes the difference in water clarity. O C. Using the same dates makes it easier to remember to take samples. O D. Using the same dates makes the second sample dependent on the first and reduces variability in water clarity attributable to date. b) Does the evidence…
lustration 13.3. The price quotations for five different commo- dities for 1951 and 1965 are given below. Calculate index number for 1965 with 1951 as base by using the weighted average of price relatives. Commodities 1951 1955 Price per kgm Quantity kgm Price A 6. 50 10 · 2 100 C 4 60 6. 10 30 12 E 8. 40 12

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