The image displays a table containing patient data with several columns. Below is a detailed transcription of the column headers and a brief explanation of the data:### Column Headers:1. **Patient**: An identifier for each individual (possibly a reference number, but shown here as a sequential list from 1-39).2. **Age (Years)**: The age of the patients, ranging from 24 to 87 years.3. **Gender**: The gender of each patient, indicated as male or female.4. **Primary DX**: The primary diagnosis for each patient. Diagnoses include CAD, HTN, CHF, DM, MI.5. **Insurance Provider**: The insurance provider for each patient, including Aetna, Horizon, Cigna, Medicaid, Medicare.6. **BMI**: Body Mass Index values for each patient.7. **Oxygen Saturation (%)**: The percentage of oxygen saturation in each patient.8. **PTT (seconds)**: Partial Thromboplastin Time, a measure of blood clotting in seconds.9. **Hemoglobin A1c (%)**: A measure of blood sugar levels over the past three months.10. **BUN (mg/dL)**: Blood Urea Nitrogen levels in milligrams per deciliter.11. **Creatinine (mg/dL)**: Creatinine levels in milligrams per deciliter.12. **Glucose (mg/dL)**: Blood glucose levels in milligrams per deciliter.13. **Glucose (g/L)**: Blood glucose levels represented differently, in grams per liter.### Explanation of Data:- Each row represents a different patient and displays their details concerning demographics, medical diagnosis, insurance, and various health indicators.- The table can be utilized to analyze correlations between demographic factors, diagnoses, insurance coverage, and health metrics.- Common medical terms are used to represent health conditions (e.g., CAD for Coronary Artery Disease, HTN for Hypertension, etc.) and tests (e.g., PTT, Hemoglobin A1c).- The data can assist healthcare providers or researchers in understanding trends, health outcomes, or insurance impacts on health statistics.No graphs or diagrams are present in the image—only a tabular presentation of data. **Text Transcription and Analysis of Boxplot: Oxygen Saturation (%):****Text:**The boxplot below represents the oxygen saturation for your patients. What does this boxplot tell you about the distribution of the data? Also describe the upper and lower quartiles, the smallest and largest value in the data set, and the median. Are there any outliers (how do you know this)?**Boxplot Explanation:**- **Title:** Boxplot of Oxygen Saturation (%)- **Y-Axis:** Oxygen Saturation (%), ranging from 88 to 100.**Features of the Boxplot:**1. **Box:** - Represents the interquartile range (IQR), which contains the middle 50% of the data. - The lower edge of the box (Q1) is at 94%. - The upper edge of the box (Q3) is at 98%.2. **Median:** - Represented by the line inside the box. - The median is approximately 96%.3. **Whiskers:** - Extend from the quartiles to the smallest and largest values within 1.5 times the IQR. - The lower whisker reaches 92%. - The upper whisker reaches 100%.4. **Outliers:** - No points are shown outside the whiskers, indicating there are no outliers in this data set.**Conclusion:**The boxplot indicates that the majority of patients have oxygen saturation levels between 94% and 98%. The data is slightly skewed towards lower values with the median closer to the upper quartile. There are no outliers, suggesting a relatively consistent range of oxygen saturation levels among the patients.

Given data: The boxplot representing the oxygen saturation for the patients is provided. The boxplot…

Answered: Boxplot of Oxygen Saturation (%) 100 90

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Boxplot of Oxygen Saturation (%) 100 90

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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Question

The image displays a table containing patient data with several columns. Below is a detailed transcription of the column headers and a brief explanation of the data:

### Column Headers:
1. **Patient**: An identifier for each individual (possibly a reference number, but shown here as a sequential list from 1-39).
2. **Age (Years)**: The age of the patients, ranging from 24 to 87 years.
3. **Gender**: The gender of each patient, indicated as male or female.
4. **Primary DX**: The primary diagnosis for each patient. Diagnoses include CAD, HTN, CHF, DM, MI.
5. **Insurance Provider**: The insurance provider for each patient, including Aetna, Horizon, Cigna, Medicaid, Medicare.
6. **BMI**: Body Mass Index values for each patient.
7. **Oxygen Saturation (%)**: The percentage of oxygen saturation in each patient.
8. **PTT (seconds)**: Partial Thromboplastin Time, a measure of blood clotting in seconds.
9. **Hemoglobin A1c (%)**: A measure of blood sugar levels over the past three months.
10. **BUN (mg/dL)**: Blood Urea Nitrogen levels in milligrams per deciliter.
11. **Creatinine (mg/dL)**: Creatinine levels in milligrams per deciliter.
12. **Glucose (mg/dL)**: Blood glucose levels in milligrams per deciliter.
13. **Glucose (g/L)**: Blood glucose levels represented differently, in grams per liter.

### Explanation of Data:
- Each row represents a different patient and displays their details concerning demographics, medical diagnosis, insurance, and various health indicators.
- The table can be utilized to analyze correlations between demographic factors, diagnoses, insurance coverage, and health metrics.
- Common medical terms are used to represent health conditions (e.g., CAD for Coronary Artery Disease, HTN for Hypertension, etc.) and tests (e.g., PTT, Hemoglobin A1c).
- The data can assist healthcare providers or researchers in understanding trends, health outcomes, or insurance impacts on health statistics.

No graphs or diagrams are present in the image—only a tabular presentation of data.

**Text Transcription and Analysis of Boxplot: Oxygen Saturation (%):**

**Text:**
The boxplot below represents the oxygen saturation for your patients. What does this boxplot tell you about the distribution of the data? Also describe the upper and lower quartiles, the smallest and largest value in the data set, and the median. Are there any outliers (how do you know this)?

**Boxplot Explanation:**

- **Title:** Boxplot of Oxygen Saturation (%)
- **Y-Axis:** Oxygen Saturation (%), ranging from 88 to 100.

**Features of the Boxplot:**

1. **Box:**
- Represents the interquartile range (IQR), which contains the middle 50% of the data.
- The lower edge of the box (Q1) is at 94%.
- The upper edge of the box (Q3) is at 98%.

2. **Median:**
- Represented by the line inside the box.
- The median is approximately 96%.

3. **Whiskers:**
- Extend from the quartiles to the smallest and largest values within 1.5 times the IQR.
- The lower whisker reaches 92%.
- The upper whisker reaches 100%.

4. **Outliers:**
- No points are shown outside the whiskers, indicating there are no outliers in this data set.

**Conclusion:**
The boxplot indicates that the majority of patients have oxygen saturation levels between 94% and 98%. The data is slightly skewed towards lower values with the median closer to the upper quartile. There are no outliers, suggesting a relatively consistent range of oxygen saturation levels among the patients.

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