The percent of fat calories that a person in America consumes each day is normally distributed with a mean of about 38 and a standard deviation of 10. Suppose that one individual is randomly chosen. Let X=percent of fat calories. Round all answers to 4 decimal places if where possible ### Task: Calculating the Upper Quartile for Fat Calorie Percentage**Objective:**Find the minimum number representing the upper quarter (75th percentile) of the percentage of fat calories.**Instructions:**- Assess a dataset where you have the percentage of fat calories.- Arrange these percentages in ascending order.- Determine the value at the upper quarter or the 75th percentile.- Enter your calculated minimum number for the upper quartile in the provided space. **Note:** The 75th percentile is calculated by identifying the point below which 75% of the data falls.

Answered: c. Find the minimum number for the…

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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The percent of fat calories that a person in America consumes each day is normally distributed with a mean of about 38 and a standard deviation of 10. Suppose that one individual is randomly chosen. Let X=percent of fat calories. Round all answers to 4 decimal places if where possible

### Task: Calculating the Upper Quartile for Fat Calorie Percentage

**Objective:**
Find the minimum number representing the upper quarter (75th percentile) of the percentage of fat calories.

**Instructions:**
- Assess a dataset where you have the percentage of fat calories.
- Arrange these percentages in ascending order.
- Determine the value at the upper quarter or the 75th percentile.
- Enter your calculated minimum number for the upper quartile in the provided space.

**Note:** The 75th percentile is calculated by identifying the point below which 75% of the data falls.

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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