Examine the normal quartile plot and determine whether it depicts sample data from a population with a normal distribution Does the normal quantile plot depict sample data from a population with a normal distribution?A. No. The points do not lie close to a straight lineB. Yes. The points are evenly distributed above and below the mean, 0C. The points exhibit some systematic pattern that is not a straight-line patternd. Yes. The pattern of the points is reasonable close to a straight line. The image displays a graph illustrating a series of data points and a line of best fit. The x-axis of the graph is labeled with values ranging from 60 to 140, likely representing an independent variable or measurement scale. The y-axis is labeled with values from -3.00 to 3.00, representing the dependent variable or the result of a measurement.**Data Points:**- The blue dots represent individual data points scattered along the graph, suggesting an upward trend.- These points show how the variable on the y-axis changes relative to the variable on the x-axis.**Line of Best Fit:**- A red line runs through the data points, representing a line of best fit. This line helps depict the overall trend of the data, suggesting a positive relationship between the x and y variables.- The line appears to follow a linear pattern, indicating that the change in the dependent variable is consistent as the independent variable increases.Overall, this graph visualizes data where the dependent variable increases in response to the increase of the independent variable, fitting a linear model.

Answered: Examine the normal quartile plot and…

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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Examine the normal quartile plot and determine whether it depicts sample data from a population with a normal distribution

Does the normal quantile plot depict sample data from a population with a normal distribution?

A. No. The points do not lie close to a straight line
B. Yes. The points are evenly distributed above and below the mean, 0
C. The points exhibit some systematic pattern that is not a straight-line pattern
d. Yes. The pattern of the points is reasonable close to a straight line.

The image displays a graph illustrating a series of data points and a line of best fit.

The x-axis of the graph is labeled with values ranging from 60 to 140, likely representing an independent variable or measurement scale. The y-axis is labeled with values from -3.00 to 3.00, representing the dependent variable or the result of a measurement.

**Data Points:**
- The blue dots represent individual data points scattered along the graph, suggesting an upward trend.
- These points show how the variable on the y-axis changes relative to the variable on the x-axis.

**Line of Best Fit:**
- A red line runs through the data points, representing a line of best fit. This line helps depict the overall trend of the data, suggesting a positive relationship between the x and y variables.
- The line appears to follow a linear pattern, indicating that the change in the dependent variable is consistent as the independent variable increases.

Overall, this graph visualizes data where the dependent variable increases in response to the increase of the independent variable, fitting a linear model.

Features Features Normal distribution is characterized by two parameters, mean (µ) and standard deviation (σ). When graphed, the mean represents the center of the bell curve and the graph is perfectly symmetric about the center. The mean, median, and mode are all equal for a normal distribution. The standard deviation measures the data's spread from the center. The higher the standard deviation, the more the data is spread out and the flatter the bell curve looks. Variance is another commonly used measure of the spread of the distribution and is equal to the square of the standard deviation.

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