Important Formulas: Data Interpretation | SSC CGL Tier 2 - Study Material, Online Tests, Previous Year PDF Download

What is Data Interpretation?

Data interpretation questions form a significant part of banking exams, aiming to evaluate a candidate’s ability to analyze and draw conclusions from complex numerical data. These questions demand proficiency in interpreting graphs, charts, and tables to solve quantitative problems. Skills in data analysis, calculation, and logical reasoning are essential for success in this section.

Data Interpretation Examples

Data Interpretation is of different forms and we have mentioned below the examples of the data interpretation for the candidates.

Table Interpretation: The table below represents the sales data of a company for the past five years. Calculate the average annual sales during this period and determine the year with the highest sales.

Bar Graph Interpretation: The bar graph displays the monthly expenditure (in thousands) of a household for various categories. Determine the month with the highest expenditure and calculate the total expenditure for the year.

Line Graph Interpretation: The line graph represents the temperature fluctuations (in degrees Celsius) in a city over a week. Identify the day with the lowest temperature and calculate the average temperature during this period.

Data Interpretation Methods

Data interpretation is a technique for analyzing and making sense of numerical data that must be collected, analyzed, and presented. When data is acquired, it is usually in a raw form that is difficult for the average person to comprehend, which is why analysts try to break down the information gathered so that others can understand it. 

Two methods of data interpretation are qualitative methods and quantitative methods.

Qualitative Method

This method is used for the analysis of qualitative data, which is called categorical data. In this method, the text is used instead of numbers or patterns for the representation of the data.
This data first needs to be coded into numbers. This coding is also documented as it will help others in the future. Qualitative data are of two types ordinal and nominal. Both of the data types are performed using the same method. However, the interpretation of ordinal data is easier in comparison to nominal data. 

Quantitative Method

This method is used for the analysis of quantitative data, which is called numerical data. This type includes numbers and can be analyzed with the help of numbers instead of text. They are divided into two main types such as continuous and discrete data. There are further two types of continuous data, namely interval data and ratio data. In this technique, this coding method is not required. In this, statistical techniques like mean, median, mode, standard deviation, etc., are used.

Data Interpretation Formula

While data interpretation questions in banking exams often require a combination of analytical skills and logical reasoning, knowing some common formulas can be helpful for solving certain types of problems. Here are a few formulas commonly used in data interpretation questions:

• Average: Average = (Sum of all values) / (Number of values)
• Percentage: Percentage = (Part / Whole) x 100
• Profit/Loss: Profit = Selling Price – Cost Price Loss = Cost Price – Selling Price Profit/Loss Percentage = (Profit/Loss / Cost Price) x 100
• Simple Interest: Simple Interest = (Principal x Rate x Time) / 100
• Compound Interest: Compound Interest = Principal x [(1 + Rate/100) ^ Time] – Principal
• Ratio and Proportion: If two quantities are in a ratio of a:b, their proportion can be expressed as a:b or a/b.
• Percentile: Percentile = (Number of values below a certain value / Total number of values) x 100