Qualitative and Quantitative Research: How to Choose the Best Design

Greg L. Lowhorn
Regent University

Introduction

It is often difficult to choose between quantitative and qualitative research design. At times, a researcher may choose a design because he or she is more familiar with one method or the other or a colleague recommends a particular design. However, our research will be more helpful if we make our decision based on well-considered, suitable design rather than simply choosing a design that is more familiar or comfortable to the researcher. The purpose of this paper is to introduce graduate students and new researchers to quantitative and qualitative research design and to help them choose the best method based on the type of information needed and analytical capability.

Quantitative Design & Analysis

Quantitative Research establishes statistically significant conclusions about a population by studying a representative sample of the population.1 The population consists of the entire group being studied. It does not matter if the population is broad or narrow, only that it includes every individual that fits the description of the group being studied.

Since it is impractical to conduct a census (include everyone in the population) because of constant turnover and resource constraints, a representative sample is chosen from the population. If chosen properly, the sample will be statistically identical to the population and conclusions for the sample can be inferred to the population.2

Quantitative research usually is one of two types: experimental or descriptive. Experimental research tests the accuracy of a theory by determining if the independent variable(s) (controlled by the researcher) causes an effect on the dependent variable (the variable being measured for change).3 Often, surveys, correlation studies, and measures of experimental outcomes are evaluated to establish causality within a credible confidence range.

Descriptive research measures the sample at a moment in time and simply describes the sample’s demography. Although this is not seen as a statistically robust or difficult exercise, a good description of the variables helps the researcher evaluate the statistical output in the proper context.4

Some researchers think that quantitative research is better than qualitative research at establishing causality because of the precise measurements and controlled environment of experiments; however qualitative studies can also be used to establish causality but with less external validity. Laboratory experiments are used when all extraneous variables need to be controlled so that the specific action and effect of the independent variable can be controlled. In addition, it may be important to be able to replicate the study and a laboratory setting makes these things possible. Field experiments are conducted when it is important to measure what the research element actually does, rather than what they say they will do. As can be seen with concept studies, what a person says they will do and what they actually do can be very different.5

Reliability and Validity

Reliability is the ability of separate researchers to come to similar conclusions using the same experimental design or participants in a study to consistently produce the same measurement.6 For example, a person who takes a risk toleration survey will achieve the same score regardless of whether he or she takes it in the morning or evening, in January or July, etc.

Validity refers to the ability of an instrument to measure what it is supposed to measure.7 If I conducted a survey to measure the degree of financial risk a person was willing to tolerate and the survey measured the respondent’s IQ instead, it would not be valid.

Internal Validity refers to the veracity of the study, how well it was constructed and run, accuracy of definitions and theories employed, accurate measurement of variables, and the researcher’s degree of confidence