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Residential Fire Damage Claims, 2010-2020 14,000 12,000 10,000 8,000 - 6,000 - 4,000 2,000 2010 2015 2020 Source: Insurance company records. (a) What kind of display is this? O Line chart O Column chart using pictures for columns O Scatter plot (b-1) Identify its strengths, using the tips and checklists shown in this chapter. (You may select more than one answer. Single click the box with the question mark to produce a check mark for a correct answer and double click the box with the question mark to empty the box for a wrong answer. Any boxes left with a question mark will be automatically graded as incorrect.) Label on Y-axis ? Label on X-axis ? Zero origin ? Non-zero origin 2 Short descriptive title ? Detailed Thousands of Dollars

Residential Fire Damage Claims, 2010-2020 14,000 12,000 10,000 8,000 - 6,000 - 4,000 2,000 2010 2015 2020 Source: Insurance company records. (a) What kind of display is this? O Line chart O Column chart using pictures for columns O Scatter plot (b-1) Identify its strengths, using the tips and checklists shown in this chapter. (You may select more than one answer. Single click the box with the question mark to produce a check mark for a correct answer and double click the box with the question mark to empty the box for a wrong answer. Any boxes left with a question mark will be automatically graded as incorrect.) Label on Y-axis ? Label on X-axis ? Zero origin ? Non-zero origin 2 Short descriptive title ? Detailed Thousands of Dollars

MATLAB: An Introduction with Applications
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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**Residential Fire Damage Claims, 2010–2020** --- **Graph Description:** The graph displays data on residential fire damage claims from 2010 to 2020, measured in thousands of dollars. The claims are represented using pictorial columns shaped like flames, suggesting an increase over time. - **Y-axis:** Labeled as "Thousands of Dollars," ranging from $0 to $14,000. - **X-axis:** Time period in years (2010, 2015, 2020). - **Visual Representation:** Each year features a flame-shaped column that represents the corresponding monetary value of claims. **Question (a):** What kind of display is this? - Options: - Line chart - Column chart using pictures for columns (selected) - Scatter plot **Question (b-1):** Identify its strengths using the tips and checklists shown in this chapter: - Labels on Y-axis (checked) - Labels on X-axis (checked) - Zero origin (unchecked) - Non-zero origin - Short descriptive title (checked) - Detailed (checked) **Source:** Insurance company records This educational material aids in understanding how to interpret pictorial representations of data over a specified time frame and the importance of correctly labeling axes and titles in data visualization.
Transcribed Image Text:**Residential Fire Damage Claims, 2010–2020** --- **Graph Description:** The graph displays data on residential fire damage claims from 2010 to 2020, measured in thousands of dollars. The claims are represented using pictorial columns shaped like flames, suggesting an increase over time. - **Y-axis:** Labeled as "Thousands of Dollars," ranging from $0 to $14,000. - **X-axis:** Time period in years (2010, 2015, 2020). - **Visual Representation:** Each year features a flame-shaped column that represents the corresponding monetary value of claims. **Question (a):** What kind of display is this? - Options: - Line chart - Column chart using pictures for columns (selected) - Scatter plot **Question (b-1):** Identify its strengths using the tips and checklists shown in this chapter: - Labels on Y-axis (checked) - Labels on X-axis (checked) - Zero origin (unchecked) - Non-zero origin - Short descriptive title (checked) - Detailed (checked) **Source:** Insurance company records This educational material aids in understanding how to interpret pictorial representations of data over a specified time frame and the importance of correctly labeling axes and titles in data visualization.
### Assessment of Visual Data Weaknesses **Task (b-2): Identify its weaknesses, using the tips and checklists shown in this chapter.** *(Instructions: You may select more than one answer. Single click the box with the question mark to produce a check mark for a correct answer and double click the box with the question mark to empty the box for a wrong answer. Any boxes left with a question mark will be automatically graded as incorrect.)* - ☑️ No source - ☐ Dramatic title - ☑️ Distracting pictures - ☑️ Use of area trick, which makes 2020 losses seem much greater than 2010 losses. --- **Question (c): Would a different type of display be better?** - ☐ Regular column chart - ☐ Scatter plot - ☐ Pie chart ### Explanation This exercise involves evaluating the weaknesses in the presentation of data. Users are instructed to identify issues using a checklist. Correctly identified weaknesses include the absence of a source, distracting pictures, and the manipulation of data representation to exaggerate losses in 2020 compared to 2010. The question also prompts consideration of alternative data display types to improve clarity and accuracy.
Transcribed Image Text:### Assessment of Visual Data Weaknesses **Task (b-2): Identify its weaknesses, using the tips and checklists shown in this chapter.** *(Instructions: You may select more than one answer. Single click the box with the question mark to produce a check mark for a correct answer and double click the box with the question mark to empty the box for a wrong answer. Any boxes left with a question mark will be automatically graded as incorrect.)* - ☑️ No source - ☐ Dramatic title - ☑️ Distracting pictures - ☑️ Use of area trick, which makes 2020 losses seem much greater than 2010 losses. --- **Question (c): Would a different type of display be better?** - ☐ Regular column chart - ☐ Scatter plot - ☐ Pie chart ### Explanation This exercise involves evaluating the weaknesses in the presentation of data. Users are instructed to identify issues using a checklist. Correctly identified weaknesses include the absence of a source, distracting pictures, and the manipulation of data representation to exaggerate losses in 2020 compared to 2010. The question also prompts consideration of alternative data display types to improve clarity and accuracy.
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