JNTU MBA 2021 RESEARCH METHODOLOGY AND STATISTICAL ANALYSIS Previous Question Paper (July/August - 2021 - R19)

Social science research faces unique challenges due to the complexity of human behavior and the nature of social systems. Key limitations include:

• Complexity of Human Behavior: Human actions are influenced by countless variables, making it difficult to isolate specific causes and effects or predict behavior with the same precision as physical sciences.
• Subjectivity and Bias: Researchers are part of the social world they study, which can lead to researcher bias, subjective interpretation of data, and difficulty in maintaining complete objectivity.
• Ethical Constraints: Many social experiments that could yield definitive data are ethically prohibited, such as manipulating human lives or environments in ways that could cause psychological or social harm.
• Lack of Laboratory Control: Unlike natural sciences, social phenomena occur in dynamic, real-world settings where it is impossible to control all extraneous variables.
• Measurement Difficulties: Abstract concepts like 'happiness,' 'social class,' or 'prejudice' are difficult to quantify accurately, often relying on self-reported data which may be prone to inaccuracies.
• Dynamic Nature of Society: Social structures and norms change over time, meaning research findings may have a limited shelf life and lack universal generalizability across different cultures or time periods.

Levels of measurement categorize data based on the nature of the information and the mathematical operations that can be performed on it. The four levels are:

• Nominal Scale: The simplest level used for labeling variables without any quantitative value. Data are categorized into distinct groups (e.g., gender, nationality, or eye color). No order or distance exists between categories.
• Ordinal Scale: Data are ranked or ordered, but the intervals between the ranks are not necessarily equal. Examples include survey ratings (e.g., 'satisfied' to 'dissatisfied') or academic rankings.
• Interval Scale: Data have a meaningful order and equal distances between points, but there is no 'true zero' point. Mathematical operations like addition and subtraction are possible, but ratios are not. A classic example is temperature in Celsius or Fahrenheit.
• Ratio Scale: The highest level of measurement. It possesses all the properties of an interval scale plus a 'true zero' point, which indicates the total absence of the variable. This allows for all statistical operations, including multiplication and division. Examples include income, weight, and height.