Data Table: ln(k) Uncertainty of ln(k) 1/T Uncertainty of 1/T 0.26136 6% 0.003309 0.0034% -0.10536 6% 0.003301 0.0033% 0.139762 4% 0.003288 0.0032% 0.34359 4% 0.003279 0.0031% 0.625938 3% 0.003266 0.0029% 1.011601 2% 0.003259 0.0029% 1.105257 2% 0.003256 0.0029% 1.348073 1% 0.00325 0.0028% 1.824549 0.81% 0.003213 0.0026% 1) Calculating the uncertainty i) Uncertainty for ln(k) Eg: ln(k)= 0.26136 Uncertainty= ((0.05)/ (0.26136))100 Uncertainty=>
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Student Activity A Generic Function Use the generic graph of f(x) with domain [–6‚ –3] and [–2‚ 6] to answer the questions below. 7 Y 6 5 4 3 2 1 X -7 -6 -5 -4 -3 -2 -1 0 -1 1 2 3 4 5 6 7 -2 -3 -4 -5 -6 -7 1. What is the range of f(x)? 2. What is the domain? 3. On what intervals is f(x) decreasing? 4. On what intervals will the following statements be true? a) As x increases‚ y increases. b) As x increases
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An extract and clarifications of changes in rules and systems of Lovely Professional University (Applicable w.e.f. Session 2013-14) Lovely Professional University has always valued feedback from its different stakeholders – especially from students and teachers. We can boast of a formal system of feedback in the University which supplements the informal mechanisms for feedback on issues such as curriculum‚ pedagogy‚ evaluation and other rules and systems of the University. Feedbacks on some key
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Student Answer form Unit 2 1. a. x-4x=-6 A) 1 B) -10 C) -6 X^2-10x-24=0 (X-4) (x+6) X-4=0 x=4 X+6=0 x+-6 b. x=7+4=5.5 x=7-4=1.5 x=-b±b2-4ac2a x= (-7) ± (-7)2-4(3) (20)2a x=7±64-802a x=7±-16 x=7+4/2=5.5 x=7-4/2=1.5 c. 10x^2+x-3=0 x=-b±b2-4ac2a x=-1± (1)2-4(10) (-3)2(10) x=1±1-12020 x=1±10 x=1+320 = 5 x=1-320= 10 2. a. (-2.3‚ 0)‚ (0‚ 6.3) b. This is a maximum function.
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XLSTAT&2014.4.08&-&Histograms&-&on&2014-09-18&at&5:27:23&PM Data:&Workbook&=&Math&1p98&final.xlsx&/&Sheet&=&Sheet1&/&Range&=&Sheet1!$A:$A&/&40&rows&and&1&column Intervals:&&Number&=&10 Summary&statistics: Variable Data Observations Obs.&with&missing&data Obs.&without&missing&data Minimum Maximum 40 0 40 4.100 13.500 Histogram)(Data)) 12& 10& Frequency) 8& 6& 4& 2& 0& 2& 4& 6& 8& Data) 10& 12& 14& & Descriptive&statistics&for&the&intervals&:
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Smbd – Assignment 4 Submitted to Prof. Ishwar Murthy 1 Introduction Mr. Debashish Chatterjee‚ owner of hotel Aria‚ is working on room booking policy to maximize the revenues. And specifically‚ he is working on the weekend operations in which the number of bookings are maximum. There are two types of bookings‚ Class I – One day bookings which start from SAT noon to SUN noon or SUN noon to MON noon and Class II – Two day bookings which start from SAT noon to SUN noon. The tariff of Class I booking
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Running head: QUADRATIC FUNCTIONS 1 Real World Quadratic Functions Gail Frazier MAT 222 Week 4 Assignment Instructor: Simone Danielson March 6‚ 2014 Real World Quadratic Functions [no notes on this page] -1- QUADRATIC FUNCTIONS 2 Quadratic functions are perhaps the best example of how math concepts can be combined into a single problem. To solve these‚ rules for order of operations‚ solving equations‚ exponents‚ and radicals must be used. Because multiple variables
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SPIDER’S WEB INTERNET CAFE Sustaining Positively your Initial Demand for an Economical Rate as We Endeavour Blessing Target Budget P 300‚000.00 Cost of Operation Estimated: Space Rental (2 months advance + 1 month deposit) P 21‚000.00 Furniture (Computer Tables & Chairs) 25‚000.00 10 sets of PCs @ P 17‚500.00 each 175‚000.00 Air Condition (second hand including installation) 15‚000.00 Printer/Scanner 5‚000.00 Xerox Machine (rental/franchise
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1. | Define each term and write the formula if needed | a) Amplitude Amplitude is half the distance between the minimum and maximum values of the range of a periodic function with a bounded range. b) Period A function whose value is repeated at constant intervals‚ such as sin x. c) Area of a sector Area = (1/2 )(r^2)(θ) radians = (θ/360)( π r^2) degrees d) Micron A unit of length equal to one millionth of a meter. e) Area of a minor segment
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TAYLMC04_0131961381.QXD 4/14/09 8:33 AM Page 42 Chapter Four: Linear Programming: Modeling Examples PROBLEM SUMMARY 1. “Product mix” example 2. “Diet” example 3. “Investment” example 4. “Marketing” example 5. “Transportation” example 6. “Blend” example 7. Product mix (maximization) 8. Sensitivity analysis (4–7) 9. Diet (minimization) 10. Product mix (minimization) 11. Product mix (maximization) 12. Product mix (maximization) 13. Product mix (maximization) 14. Ingredients mix (minimization)
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