t = eAV – 1.(4.8) The following data were obtained for Experiment 4(b) with a silicondiode:VI(volt)(A)0.30750.25280.2010.60.153.30.101.20.050.360.00.01-0.05-0.13-0.10-0.15-0.15-0.19-0.20-0.19-0.25-0.20-0.30-0.20-0.40-0.20(a) Plot a graph of I versus V.(b) Determine the saturation current Io for the diode from the graphof your measurements.(c) Linearise equation (4.8) showing all your work.(d) Do a linear regression analysis of the data and plot the beststraight line through the points.

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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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The following are measurements of the heat-producing capacity (in millions of calories per ton) of random samples of five specimens each of coal from two mines: Mine 1: Mine 2: 8380 8210 8360 7840 7910 7540 7720 7750 8100 7690 Below are the EXCEL outputs of the data at 95% confidence level: t-Test: Paired Two Sample for Means t-Test: Two-Sample Assuming Equal Vari MINE 1 MINE 2 MINE 1 MINE 2 7760 8140 63450 Mean Mean 8140 7760 Variance 42650 Variance 63450 42650 Observations Pooled Variance Observations Pearson Correlation-0.69059 Hypothesized Mear df 53050 Hypothesized Me df 4 8 t Stat P(T<=t) one-tail t Critical one-tail P(T<=t) two-tail t Critical two-tail 2.014279 t Stat 2.608621 0.05712 P(T<=t) one-tail t Critical one-tail 0.015599 1.859548 2.131847 0.11424 P(T<=t) two-tail 0.031197 2.306004 A. 2.776445 B. tCritical two-tail
4 The normalized cumulative distribution function is given by 1 D(x)=- Te dt. The following table is generated from the above function. 0.0 0.4 0.6 1.0 $(x) .5000 0.6554 0.7257 0.8413 (a) (b) Present the Divided Difference Table associated with this data. Using Newton's Forward Divided Difference Formula, approximate D(0.18). Using Newton's Backward Divided Difference Formula, approximate (0.85). (c)
2. Abe Lincoln, stump remover, mixes a thimbleful of aluminum shavings with varying amounts of rust to create explosions that break up the root structure of some particularly difficult trees. He measures the energy released by each such reaction and tabulates che following results. m (moles of rust) E(m) (megajoules) 1 3.5 5.5 6 6 1 1.5 4 8 15 30 A. What would E'(1.5) = 4.5 represent? %3D i. Abe needs to use 1.5 moles of rust in order to release 4.5 megajoules of energy. ii. Abe needs to use 4.5 moles of rust in order to release 1.5 megajoules of energy. iii. With respect to a control experiment using up 1.5 moles of rust, the energy released in a thermite reaction increases by 4.5 megajoules per mole of rust. iv. The first 1.5 moles of rust each contributed 4.5 megajoules of energy. B. Which of the following would best explain the value of E'(8)? i. Abe's 19th century equipment couldn't measure energies in excess of 6 megajoules. ii. Scarcity of decent writing paper in the 19th…
Consider a random sample X1,...,Xn (n > 2) from Beta(θ,1), where we wish to estimate the parameter θ. (a) Find the MLE θˆ and write it as a function of T = − ∑ni=1 log Xi. (b) Find the sampling distribution of T = − ∑ni=1 log Xi . (Hint: First find the distribution of Ti = − log Xi .)
A CI is desired for the true average stray-load loss μ (watts) for a certain type of induction motor when the line current is held at 10 amps for a speed of 1500 rpm. Assume that stray-load loss is normally distributed with = 2.1. (Round your answers to two decimal places.) (a) Compute a 95% CI for μ when n = 25 and x = 56.0. watts (b) Compute a 95% CI for μ when n = 100 and x = 56.0. watts (c) Compute a 99% CI for μ when n = 100 and x = 56.0. watts (d) Compute an 82% CI for μ when n = 100 and x = 56.0. watts (e) How large must n be if the width of the 99% interval for u is to be 1.0? (Round your answer up to the nearest whole number.) n =
A CI is desired for the true average stray-load loss (watts) for a certain type of induction motor when the line current held at 10 amps for a speed of 1500 rpm. Assume that stray-load loss is normally distributed with = 2.9. (Round your answers to two decimal places.) (a) Compute a 95% CI for μ when n = 25 and x = 59.1. watts (b) Compute a 95% CI for when n = 100 and x = 59.1. watts (c) Compute a 99% CI for μ when n = 100 and x = 59.1. watts (d) Compute an 82% CI for when n = 100 and x = 59.1. watts (e) How large must n be if the width of the 99% interval for is to be 1.0? (Round your answer up to the nearest whole number.) n =
44
The calculated experimental values for the heat capacity of ammonia are: T(C) 0 Cp (cal/g.mol C) 8.371 18 8.472 25 8.514 100 9.035 200 9.824 300 10.606 400 11.347 500 12.045 1. Fit the data for the following function: Cp=aT³+bT²+eT+d Where T is in C 2. Then calculate amount of heat Q required to increase the temperature of 150 mol/hr of ammonia vapor from 0 C to 200 C if you know that: Tout Q=n Cpdt Tin
A E F В D Suppose in the picture above 3|AE| = |EC| 2|BD| = |DC| (GAF) = 0.96 (GDC) = 4.8 Then (GBD) : =| 2.4 and (GCE) = .72
Q.21 Given the following set of discrete data: 0.2 1.0832 0.3 0.4 y 1.1972 1.3771 Find the approximate value of f'(0.4) using all the appropriate difference formulas. solution with f(x) = ²x². Which method gives better approximation? Check X 0.4 1.6487 your 0.6 2.0544 0.7 2.6644
(a) Use the following data to compute a 95% CI for μ₁ - M₂: m = 661, x = 2228, s₁ = 1518, n = 405, y = 2634, and s₂ = 1138. (Round your answers to two decimal places.) Does the resulting interval suggest that μ₁ −μ₂ has been precisely estimated? O The interval is fairly narrow, which suggests a precise estimate. O The interval is fairly wide, which does not suggest a precise estimate. The interval is fairly narrow, which does not suggest a precise estimate. O The interval is fairly wide, which suggests a precise estimate. (b) Use the following data to compute a 95% upper confidence bound for μ₁-₂: m = 50, x = 43,600, s₁ = 2500, n = 50, = 36,600, and s₂ = 1800. (Round your answer to two decimal places.) y You may need to use the appropriate table in the Appendix of Tables to answer this question.
Please answer d and e

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