Distinguish between the following: a) Inductive Research and Deductive Research b) Survey and Schedule c) Null Hypothesis and Alternative Hypothesis d) Qualitative Data and Quantitative Data

Introduction

Understanding the key differences between research methodologies and data classifications is vital for designing effective studies. This question focuses on four crucial distinctions in business research. Let’s explore each pair of terms in detail.

a) Inductive Research and Deductive Research

Inductive Research:

• Begins with observations or data collection and moves toward developing a theory.
• It follows a bottom-up approach.
• Often used in qualitative research.
• Example: Observing consumer behavior in different stores and forming a theory about purchase decisions.

Deductive Research:

• Starts with a theory or hypothesis and tests it using data.
• It follows a top-down approach.
• Common in quantitative research.
• Example: Hypothesizing that discounts increase sales and using data to test it.

b) Survey and Schedule

Survey:

• A method of data collection where respondents answer questions in a structured format.
• Can be self-administered (online, paper) or interviewer-led.
• More flexible and cost-effective for large samples.
• Requires participant literacy if self-administered.

Schedule:

• A list of questions presented by a trained enumerator who fills in responses.
• Used when direct interaction is needed (illiterate or rural populations).
• More accurate in terms of response quality.
• Time-consuming and resource-intensive.

c) Null Hypothesis and Alternative Hypothesis

Null Hypothesis (H₀):

• States that there is no effect or relationship between variables.
• Serves as a default assumption to be tested.
• Example: There is no difference in sales between two stores.

Alternative Hypothesis (H₁):

• Contradicts the null hypothesis and proposes a significant effect or relationship.
• If the null hypothesis is rejected, the alternative is accepted.
• Example: There is a significant difference in sales between two stores.

d) Qualitative Data and Quantitative Data

Qualitative Data:

• Descriptive and conceptual data, usually non-numeric.
• Explores meanings, experiences, and interpretations.
• Methods include interviews, focus groups, and observations.
• Example: Customer opinions about a product.

Quantitative Data:

• Numeric data used for statistical analysis.
• Focuses on measurements and quantities.
• Collected through surveys, experiments, etc.
• Example: Number of units sold, income levels.

Conclusion

These fundamental distinctions—between inductive and deductive research, survey and schedule, hypotheses types, and data forms—are crucial in determining the approach, tools, and analysis techniques in research. Understanding them ensures that research design is methodologically sound and aligned with research objectives.