A USE SALT y thatEr - s801, - 5613,547, y - 575, E - 64,543 and y - 549,281. or decrease? Explain your answer. as x increases. ymaximum wind speed in miles per hour) ymaximum wind speed din miles per houri) (Lanoy ad sagu up paads pu unuprun y maximum wind speed in miles per hour)

MATLAB: An Introduction with Applications
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ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
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### Analyzing Barometer Readings for Predicting Cyclone Wind Speed

#### Overview

The study investigates whether barometer readings (in millibars) can predict maximum wind speed (in miles per hour) of approaching tropical cyclones. The analysis uses a random sample of tropical cyclones.

#### Scatter Diagrams

- **First Scatterplot (Left)**: 
  - **Axes**: X-axis represents the lowest pressure in millibars (millibars), ranging from 40 to 140. Y-axis represents maximum wind speed in miles per hour (mph), ranging from 60 to 140.
  - **Data Points**: Various points are plotted, showing a distribution that suggests a possible non-linear relationship.
  - **Line of Fit Option**: Users are asked to select the line that best fits the data.

- **Second Scatterplot (Middle)**
  - **Axes**: X-axis as lowest pressure (millibars) from 940 to 1000. Y-axis for maximum wind speed (mph) from 890 to 1010.
  - **Data Points**: Displays a clearer pattern where pressure decreases as wind speed increases.
  - **Line of Fit Option**: Users are asked to select the line that best fits the data.

- **Third Scatterplot (Right)**
  - **Axes**: X-axis is the lowest pressure (millibars) from 940 to 1000. Y-axis represents maximum wind speed (mph) from 40 to 140.
  - **Data Points**: Points suggest a possible correlation; sensitivity to pressure changes shows an upward trend where pressure decreases with increasing wind speed.
  - **Line of Fit Option**: Selection for best fit line available.

#### Correlation Analysis

- **Question (b)**: Participants are asked to assess if the correlation between variables is low, moderate, or strong.
- **Correlation Type**: Determine if positive or negative.

#### Calculation Verification

Using the provided sums:
- \(\sum x = 580\)
- \(\sum x^2 = 5,613,547\)
- \(\sum y = 575\)
- \(\sum y^2 = 64,543\)
- \(\sum xy = 549,281\)

**Compute \(r\)**: Users calculate the correlation coefficient \(r\) and round it to four decimal places.

#### Discussion

- **Question (
Transcribed Image Text:### Analyzing Barometer Readings for Predicting Cyclone Wind Speed #### Overview The study investigates whether barometer readings (in millibars) can predict maximum wind speed (in miles per hour) of approaching tropical cyclones. The analysis uses a random sample of tropical cyclones. #### Scatter Diagrams - **First Scatterplot (Left)**: - **Axes**: X-axis represents the lowest pressure in millibars (millibars), ranging from 40 to 140. Y-axis represents maximum wind speed in miles per hour (mph), ranging from 60 to 140. - **Data Points**: Various points are plotted, showing a distribution that suggests a possible non-linear relationship. - **Line of Fit Option**: Users are asked to select the line that best fits the data. - **Second Scatterplot (Middle)** - **Axes**: X-axis as lowest pressure (millibars) from 940 to 1000. Y-axis for maximum wind speed (mph) from 890 to 1010. - **Data Points**: Displays a clearer pattern where pressure decreases as wind speed increases. - **Line of Fit Option**: Users are asked to select the line that best fits the data. - **Third Scatterplot (Right)** - **Axes**: X-axis is the lowest pressure (millibars) from 940 to 1000. Y-axis represents maximum wind speed (mph) from 40 to 140. - **Data Points**: Points suggest a possible correlation; sensitivity to pressure changes shows an upward trend where pressure decreases with increasing wind speed. - **Line of Fit Option**: Selection for best fit line available. #### Correlation Analysis - **Question (b)**: Participants are asked to assess if the correlation between variables is low, moderate, or strong. - **Correlation Type**: Determine if positive or negative. #### Calculation Verification Using the provided sums: - \(\sum x = 580\) - \(\sum x^2 = 5,613,547\) - \(\sum y = 575\) - \(\sum y^2 = 64,543\) - \(\sum xy = 549,281\) **Compute \(r\)**: Users calculate the correlation coefficient \(r\) and round it to four decimal places. #### Discussion - **Question (
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