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? **Histogram of Weights****Descriptive Statistics: Weights****Statistics**- **Variable**: Weights- **N**: 30- **Mean**: 92.37- **SE Mean**: 5.11- **StDev**: 28.01- **Minimum**: 44.00- **Q1**: 64.50- **Median**: 96.50- **Q3**: 114.25- **Maximum**: 137.00**Explanation of the Histogram**The histogram displayed visually represents the distribution of the weights dataset. - **X-axis**: Displays the weights ranging from approximately 0 to 130.- **Y-axis**: Indicates the frequency of each weight range.- The histogram bars are yellow, showing intervals of weight grouped in categories.- A red curve is overlaid on the histogram, likely representing a normal distribution fit for the dataset.**Data Table**Names and corresponding weights are listed:- Jase Anders- Leelin Dye- Wes Obyrne- Marcus Mitchell- Kaden Dupree: 116- Easton Gifford: 125- Joel Ramos: 130- Andrew Boyd: 135- Troy Clevinger: 137These values provide a sample representation of individual weights within the dataset.

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?

**Histogram of Weights**

**Descriptive Statistics: Weights**

**Statistics**

- **Variable**: Weights
- **N**: 30
- **Mean**: 92.37
- **SE Mean**: 5.11
- **StDev**: 28.01
- **Minimum**: 44.00
- **Q1**: 64.50
- **Median**: 96.50
- **Q3**: 114.25
- **Maximum**: 137.00

**Explanation of the Histogram**

The histogram displayed visually represents the distribution of the weights dataset.

- **X-axis**: Displays the weights ranging from approximately 0 to 130.
- **Y-axis**: Indicates the frequency of each weight range.
- The histogram bars are yellow, showing intervals of weight grouped in categories.
- A red curve is overlaid on the histogram, likely representing a normal distribution fit for the dataset.

**Data Table**

Names and corresponding weights are listed:

- Jase Anders
- Leelin Dye
- Wes Obyrne
- Marcus Mitchell
- Kaden Dupree: 116
- Easton Gifford: 125
- Joel Ramos: 130
- Andrew Boyd: 135
- Troy Clevinger: 137

These values provide a sample representation of individual weights within the dataset.

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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