37. Eat your kale: Kale is a type of cabbage commonly found insalad and used in cooking in many parts of the world. Sixmeasurements were made of the mineral content (in percent) ofkale, with the following results.26.1 17.5 15.4 16.4 15.1 12.8It turns out that the value 26.1 came from a specimen that theinvestigator forgot to wash before measuring.a. The data contain an outlier that is clearly a mistake.Eliminate the outlier, then construct a 95% confidenceinterval for the mean mineral content from the remainingvalues.b. Leave the outlier in and construct the 95% confidenceinterval. Are the results noticeably different? Explain why itis important to check data for outliers.Source: Journal of Nutrition 66:55–66

Given data: To construct 95% confidence interval 1. By eliminating outliers 2. By considering…

Answered: 37. Eat your kale: Kale is a type of…

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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Illustration: 23.3. C-Chart. Following 20 figures correspond to the number of defects (spots) in 20 sheets of 1'X2' selected as 20 šamples during a process of manufacturing metal sheets. Plot a suitable control chart. 27, 26, 20, 19, 12, 16, 22, 29, 13, 17, 22, 26, 25, 18, 17, 13, 19, 15, 18, 22.
Given the data as in Table 2. x y 2 2.757 Table 2 3 7 9 12 3.279 6.009 9.751 12.906 15 15.988 Use an appropriate interpolation technique to find interpolated value at x=5.
Plot the data on the given graph paper. Consider what should go on the X and Y axes.
c?
First, gently shade this area in on your curve, then calculate your z scores for X = 47 and for X = 48. %3D I find it handy to use these little tables: Body or tail? Area from Unit Normal Table 47 - 46/1.50 = 48 - 46/1.50%3= For THIS problem, which answer below shows the Area for the first (top) number and the second (bottom) number? .7486 (top): .9082 (bottom) 2514 (top); .0918 (bottom) O.9332 (top); .0668 (bottom) O.0918 (top); .2514 (bottom)
Determine the following for each data set Data Set Student X Student Y x s RSD(ppt) R RR(ppt) C.I.
NOTE: ANSWER 5-10
USE THE COOROINATES BELOW AND " AREA BY COOROINATES FoemuLA "TO DETEAMINE THE AREA TO THE NEANEST SUARE Fcor ANO DETERMINE THE ACAEAGE TO THE NEAREST THOUSANDTH. YW=5,000.00o XE)= 5,850 coo 2 YA) = 5,000.000 x0=6,05%.130 3. YOS=4,791.302 4 Yas-4,744.30z X6)=5846.351 X() = 6,055.087
Trace metals in drinking water affect the flavor and an unusually high concentration can pose a health hazard. Ten pairs of data were taken measuring zinc concentration in bottom water and surface water. Bottom 0.430 0.266 0.567 0.531 0.707 0.716 0.651 0.589 0.469 0.723 Surface 0.415 0.238 0.390 0.410 0.605 0.609 0.632 0.523 0.411 0.612 With the help of Mathematics and R Studio: Does the data suggest that the true average concentration in the bottom water is different than that of surface water? You can assume that the conditions for inference are met.
- TABLE 6E.2 Bearing Diameter Data Sample Number i Sample Number R 1 34.5 3 13 35.4 8. 2 34.2 4 14 34.0 6 3 31.6 4 15 37.1 5 4 31.5 4 16 34.9 7 5 35.0 5 17 33.5 4 34.1 6. 18 31.7 3 7 32.6 4 19 34.0 8. 8 33.8 3 20 35.1 4. 9. 34.8 7 21 33.7 2 10 33.6 8 22 32.8 1 11 31.9 3 23 33.5 3 12 38.6 9 24 34.2 2 inside diameter of the bearing, with only the last three decimals recorded (i.e., 34.5 should be 0.50345). (a) Set up ī and R charts on this process. Does the process seem to be in statistical control? If nec- essary, revise the trial control limits. (b) If specifications on this diameter are 0.5030 ± 0.0010, find the percentage of nonconforming bearings produced by this process. Assume that diameter is normally distributed.
Q. 1 Proportion of hypothetical life table is given as: Age 1000 1. 991 6. 2. 985 3 982 3. 4. 979 976 4. 6. 972 968 4 964 4 9 959 Find Oa.959 Ob.964 Oc. 976 Od. 985 Oe. 979 (ii) dz Oa. 4 Ob.3 Oc. 6 6 "PO Oe. 5 (iii) Probability that a newborn will die before reaching 7 years; Oa. 0.018 Ob.0.032 Oc. 0.036 Od. 0.024 Oe. 0.046 (iv) Probability that a new born will live more than 5 years; Oa. 0.985 Ob. 0.976 Oc. 0.964 Od. 0.959 Oe. 0.999 (v) Probability that a 2-year old will die when his age is between 5 years and 7 years. Oa. 0.00765 Ob. 0.00835 Oc. 0.00675 Od. 0.00567 Oe. 0.00358
Illustration 13.4. Compute a quantity Index for the following data, using weighted aggregate of quantities method. 1960 1970 Cоommodity Pr:ce Оuantity Quantity A 40 30 20 25 15 20 10 10 10 20 10 CS Scanned with CamScanner

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