Utilizing excell bookkeeping page:

5.84 5.00 4.48 5.14 5.78 3.98 6.16 6.02 5.52 4.56

4.33 5.63 5.27 4.25 5.43 5.78 4.57 5.03 4.60 5.00

5.82 4.23 5.86 5.22 4.89 5.33 5.53 4.72 5.07 5.60

5.05 5.35 4.28 5.64 5.13 5.56 5.52 5.07 4.30 5.78

4.79 4.89 4.52 4.53 4.52 5.31 5.27 5.22 5.14 5.20

5.03 5.39 5.18 5.19 4.45 5.53 4.96 5.44 5.59 4.60

4.32 4.45 4.91 5.55 5.22 5.65 4.76 5.31 4.39 5.50

6.09 4.52 4.63 5.22 4.51 4.79 5.50 4.98 4.79 4.51

For all inquiries, compose your answers in the yellow cells.

Figure the accompanying insights utilizing Excel works so that Excel computes for you: Mean

Middle You are an analyst contracted to test and examine loads of the 5 lb packs of espresso. You gather the accompanying information:

First quartile utilizing QUARTILE.EXC

Third quartile utilizing QUARTILE.EXC

Interquartile range (IQR)

Greatest

Least

Reach

Change

Standard deviation

Coeficient of Variation (CV)

For the standard deviation, when do you utilize STDEV.S and when do you utilize STDEV.P?

Clarify why the standard deviation is a preferable measure to use over the fluctuation.

The coefficient of variety (CV) is a proportion of relative changeability equivalent to the proportion between the standard deviation isolated by the mean, and designed to %. It is routinely used to analyze hazard (unpredictability) in contributing, and is particularly helpful in to contrast information on various scales or and various units of measure. Consider loads of 10 oz, 13.4 oz, 15.1 oz with SD of 2.597 oz. The relating loads in pounds 0.625 lb, 0.838 lb, 0.944 lb have SD 0.162 lb. The SDs are not equivalent, yet the example and its inconstancy are something similar. How might we analyze changeabilities? The CV, in contrast to different proportions of inconstancy, doesn't rely upon the units of measure. The units are separated out in partitioning the standard deviation by the mean. For a "dependable guideline", a CV of more noteworthy than 5% is considered huge. Along these lines, the CV is additionally used to survey information with no earlier history to contrast with assess any patterns.

When is the Coefficient of Variation (CV) particularly helpful?

Duplicate the entirety of the information into cells M1:M80 to utilize Data Analysis Descriptive Statistics.

What occurs on the off chance that you don't and rather use B3:K10 for the Input Range?

Utilize the Data Analysis, Descriptive Statistics. Snap the Summary Statistics box and put the yield at B65.

Feature the mean, middle, Standard deviation, Range, Minimum, and Maximum.

As a contracted analyst, you have no related knowledge with the organization's item. The organization has no earlier cycle history and information with which to contrast the example with assess any patterns.

The mode isn't particularly helpful for this information, however clarify why there is or isn't a worry with sack weight as far as different proportions of focal inclination.

What measurement would it be advisable for you to use to survey changeability of the item?

Clarify why there is or isn't a worry with the fluctuation of the item.

The upward velocity of a rocket is given as a mction of time in Table 3. Table 3 Velocity as a function of time. 3) Determine the value of the VElDCil'y at t=l seconds using the direct method of interpolation and a third order polynomial. h) Find the absolute relative approximate error for the third order polynomial approximation. c) Using the third order polynomial hitetpolant for velocity from part {a}. nd the distance covered by the rocket from t = 1 15 to r: 155. d] Using the third order polynomial interpolant for velocity 'om part {a}, nd the acceleration of the rocket at ." = 165. 4. [Lagrange Interpolation] Interpolate f (1) = 1+12 at evenly spaced points on the interval [-5, 5], with Lagrange polynomials of order n = 5, 10, 20. Does the approxi- mation get better? 5. [Piecewise Linear Interpolation] Interpolate f(:) = 1 1+ 12 at evenly spaced points on the interval [-5, 5] using piecewise linear interpolation with the same points as in Problem 4. Does the approximation get better with more points?[2] Let f(x) = sin(x) and x0 = 1, x1 = 1.25, and x2 = 1.6. (a) Construct interpolation polynomials of degree at most one and at most two to approximate f (1.4) and find the absolute error. (b) Use the theorem expressing the error in Lagrange interpolation to find an error bound for the approximations