25, ans = 25 ans = fx 25 143 Given the data 29.65 28.55 28.65 30.15 29.35 29.75 29.25 30.65 28.15 29.85 29.05 30.25 30.85 28.75 29.65 30.45 29.15 30.45 33.65 29.35 29.75 31.25 29.45 30.15 29.65 30.55 29.65 29.25 Determine (a) the mean, (b) median, (c) mode, (d) range, (e) standard deviation, (f) variance, and (g) coefficient of variation. (h) Construct a histogram. Use a range from 28 to 34 with increments of 0.4. (i) Assuming that the distribution is normal, and that your estimate of the standard deviation is valid, compute the range (ie., the lower and the upper values) that encom- passes 68% of the readings. Determine whether this is a valid estimate for the data in this problem. P14.4 144 Using the same approach as was employed to derive Eqs. (14.15) and (14.16), derive the least-squares fit of the following model: y=ax+e That is, determine the slope that results in the least-squares fit for a straight line with a zero intercept. Fit the following data with this model and display the result graphically. Σ - Σ. Σ nΣx-(x)² a-y-ax x 2 4 6 7 10 11 y 4 5 6 5 8 8 14 17 20 12 69 P14.6 Fit a power model to the data from Table 14.1, but use natural logarithms to perform the transformations. TABLE 14.1 Experimental data for force (N) and velocity (m/s) from a wind tunnel experiment. v, m/s F,N 10 20 30 40 25 70 380 550 50 610 60 1220 70 830 80 1450

Elements Of Electromagnetics

7th Edition

ISBN:9780190698614

Author:Sadiku, Matthew N. O.

Publisher:Sadiku, Matthew N. O.

ChapterMA: Math Assessment

Section: Chapter Questions

Problem 1.1MA

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Question

Please help Matlab, as well needs to be on excel data sheet.

P14.19 You perform experiments and determine the following values of heat capacity c
at various temperatures T for a gas:
I) For c, determine (a) the mean, (b) median, (c) mode, (d) range, (e) standard
deviation, (f) variance, and (g) coefficient of variation.
II) Using linregr given function, fit the data using a straight line (determine a1,
a0, r
2
). Plot the data and the regression curve.
III) Using polyfit command, fit the data using a quadratic curve (determine a2, a1, a0).
Plot the data and the regression curve.
IV) Using linregr given function, fit the data using exponential model (determine
α, β, r
2
). Plot the data and the regression curve in the T-c space (not the T-log(c)
space)

T -50 -30 0 60 90 110

C 1250 1280 1350 1480 1580 1700