Determine what percentage of your data is within 2 standard deviations of the mean. (Show your calculations). How does this seem to compare with the 68-95 99.7 rule?does this data seem to be normally distributed why or why not? Minitab Mean Project-histogram.MP)File Edit Data Calc Stat Graph Editor Tools Window Help AssistantSessionHistogram of WeightsHistogram of WeightsDescriptive Statistics: WeightsStatisticsVariableN N°Mean SE Mean StDev MinimumQ1 MedianQ3 MaximumWeights 3092.375.11 28.0144.00 64.5096.50114.25137.00Worksheet 1C1-TNames22 Jase Anders2030 4050607080 90 100 110 120 13023 Lellin DyeWeights24 Wes Obyrne25 Marcus Mitchell11626 Kaden Dupree12527 Easton Gifford13028 Joel Ramos13229 Andrew Boyd13530 Troy Clevinger13731urrent Worksheet Worksheet 19 Type here to search北

To find what percentage of the data is within 2 Standard deviations of the mean, Chebyshev's…

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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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Determine what percentage of your data is within 2 standard deviations of the mean. (Show your calculations). How does this seem to compare with the 68-95 99.7 rule?

does this data seem to be normally distributed why or why not?

Minitab Mean Project-histogram.MP)
File Edit Data Calc Stat Graph Editor Tools Window Help Assistant
Session
Histogram of Weights
Histogram of Weights
Descriptive Statistics: Weights
Statistics
Variable
N N°
Mean SE Mean StDev Minimum
Q1 Median
Q3 Maximum
Weights 30
92.37
5.11 28.01
44.00 64.50
96.50
114.25
137.00
Worksheet 1
C1-T
Names
22 Jase Anders
20
30 40
50
60
70
80 90 100 110 120 130
23 Lellin Dye
Weights
24 Wes Obyrne
25 Marcus Mitchell
116
26 Kaden Dupree
125
27 Easton Gifford
130
28 Joel Ramos
132
29 Andrew Boyd
135
30 Troy Clevinger
137
31
urrent Worksheet Worksheet 1
9 Type here to search
北

Definition Definition Measure of central tendency that is the average of a given data set. The mean value is evaluated as the quotient of the sum of all observations by the sample size. The mean, in contrast to a median, is affected by extreme values. Very large or very small values can distract the mean from the center of the data. Arithmetic mean: The most common type of mean is the arithmetic mean. It is evaluated using the formula: μ = 1 N ∑ i = 1 N x i Other types of means are the geometric mean, logarithmic mean, and harmonic mean. Geometric mean: The nth root of the product of n observations from a data set is defined as the geometric mean of the set: G = x 1 x 2 ... x n n Logarithmic mean: The difference of the natural logarithms of the two numbers, divided by the difference between the numbers is the logarithmic mean of the two numbers. The logarithmic mean is used particularly in heat transfer and mass transfer. ln x 2 − ln x 1 x 2 − x 1 Harmonic mean: The inverse of the arithmetic mean of the inverses of all the numbers in a data set is the harmonic mean of the data. 1 1 x 1 + 1 x 2 + ...

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