Quantitative methods involve the use of numerical data and mathematical calculations to analyze and solve problems. It includes various techniques such as statistics, mathematics, econometrics, and operations research.
Four rules of numeracy:
Addition: The process of combining two or more numbers to find the total.
Subtraction: The process of finding the difference between two numbers.
Multiplication: The process of finding the product of two numbers.
Division: The process of dividing one number by another to find the quotient.
Values of Financial Transactions:
The text mentions various thresholds and reporting requirements for different types of financial transactions, such as:
Immovable Property: Property transactions exceeding Rs 30 lakh need to be reported.
Professionals: Receipt of cash payment exceeding Rs 2 lakh for goods or services must be reported.
Cash Deposits in Banks: Cash deposits of Rs 10 lakh or more in a financial year need to be reported.
Term Deposits in Banks: Cash deposits of Rs 10 lakh or more in time deposit ac- counts need to be reported.
Deposits in Current Accounts: Cash deposits or withdrawals of Rs 50 lakh or more in a financial year need to be reported.
Bank Drafts and Prepaid Instruments: Cash payment of Rs 10 lakh or more for bank drafts or prepaid instruments needs to be reported.
Credit Card Bill Payments: Payments exceeding Rs 1 lakh in cash or Rs 10 lakh through other modes need to be reported.
Investments in Financial Securities: Receipt of Rs 10 lakh or more from an in- dividual for securities like bonds, shares, or mutual funds needs to be reported.
Negative Numbers:
Negative numbers are values less than zero. The text provides examples and rules for addition, subtraction, multiplication, and division involving negative numbers.
Data Types:
The text mentions three data types:
Numerical data: Data that can be measured or counted, such as height, weight, or the number of shares.
Discrete data: Data that can be counted and takes on specific values, such as the number of books owned. Continuous data: Data that represents measurements and can take on any value within a range, such as temperature or volume.
Probability Laws and Rules:
The text briefly mentions laws and rules of probability, such as the addition rule, the multiplication rule, and the rule of partitions.
Rules and Principles
When providing descriptions in data visualization, there are various methods that can be used. However, the most common ones include telling a story, directly labeling shapes, or explaining the visuals in a lead-in paragraph.
Explain encodings
Encodings in data visualization refer to the techniques used to represent values. For example, a color scale may be used to indicate size or the dimension of a square can represent values. It is important to explain what these encodings are intended to show and not assume that the reader understands everything. By clearly explaining the meaning of the encodings, any confusion can be eliminated for the reader.
Maintain their geometry in check
Accuracy in the geometry of data visualization is crucial. If the geometry is in- correct, it will be the first thing that people notice and criticize. This is especially true when using bubble size to represent numerical values. Therefore, it is important to ensure that the geometry is accurate to avoid negative feedback or criticism on platforms such as blogs.
Include units
When presenting numerical values, it is important to include units. Leaving numbers without units can lead to ambiguity, as they can be interpreted in various ways. Units provide clarity and eliminate any uncertainty for the reader. By including units, the reader can accurately understand and interpret the values being presented.
Enhance the data: According to Tufte, data visualizations should enhance the data and not obscure it. This means that the visualization should be easy to read and interpret, without adding unnecessary elements that might distract from the data itself.
Present comparisons: Tufte emphasizes that data visualizations should be used to present comparisons. The visualization should enable easy comparison between different data points or sets of data, allowing viewers to quickly grasp similarities, differences, and patterns.
Avoid distortion: Tufte stresses the importance of avoiding distortion in data visualizations. Distortion can misrepresent the data and lead to inaccurate interpretations. Visualizations should accurately represent the data without ex- aggeration, manipulation, or misleading techniques.
Repetition: Tufte suggests that repetition can be employed to emphasize important information in a data visualization. This can be achieved by repeating visual elements or employing consistent color schemes throughout the visualization, reinforcing key points or patterns.
By adhering to these rules and principles in data visualization, the effectiveness and clarity of the visual representation can be enhanced. Clear explanations, accurate geometry, inclusion of units, and following Tufte’s guidelines can help convey the intended message accurately to the reader or viewer.
References
Study.com. (2017). Financial Transactions: Types, Overview – Video & Lesson Transcript.
Tufte, Edward R. (2001). The Visual Display of Quantitative Information. Second edition. Cheshire, CT: Graphics Press.
Yau, N. (2017). 7 Basic Rules for Making Charts and Graphs.
Herman, I., & Paris, C. (2015). “The Visual Language of Data: A Comprehensive Guide to Making Effective Data Visualizations.” Wiley.
Tufte, E. R. (2001). The Visual Display of Quantitative Information(2nd ed.). Graphics Press.
