Statistical Analysis Methods for Market Research
Clarke Ricks
School of Business, Liberty University
BUSI 690: Policy and Strategy in Global Competition
Dr. Hicks
April 6, 2021
Statistical Analysis Methods for Market Research
Statistical analysis is a quantitative data analysis method that uses numbers to assign a
measurability factor that is easy to compare and interpret. Under statistical analysis, the raw
data is collected and analyzed to identify any patterns and trends which can be used for
informed decision making.
The process of using statistics for market research involves:
Defining the type of data to be extracted from the target population
Exploring the relationship of the data with the population set
Developing a model that summarizes insights and defines any visible links
between the data set and the population
Testing the model to establish the validity of the model
Incorporating the results into your business strategy by anticipating future
trends
Statistical Analysis Methods
There are two main statistical analysis methods commonly used for market research
purposes: descriptive and inferential statistics. Both methods have different goals and
applications, making them suitable for evaluating different data sets.
Descriptive Statistics
Descriptive statistics provide insight into the data collected, but they do not draw any
conclusions about the larger population the data sample is extracted from. This method
essentially describes a sample by summarizing and graphing data.
Conducting market research with descriptive statistics can help organizations
understand the basic features of any set of quantifiable data by grouping data and
identifying any patterns or trends. Inferential statistics use insights and measurements
derived from the sample set and extrapolates the results to a larger set.
This method is primarily used to draw conclusions from an experiment sample and
generalize the points to a relevant population. An underlying assumption of this method is
that the sample size is an accurate representation of the population which requires us to
identify the population, include relevant sampling techniques to extract the sample set, and
have some built-in safeguards to account for sampling errors.
While this method is more complicated than descriptive statistics, it provides richer
numerical data for future business strategies. Some common inference statistical analysis
methods include:
Benefits of Using Statistical Analysis in Market Research
Statistical analysis methods can provide worthwhile benefits to facilitate market
research processes by:
Producing theories backed by numerical evidence. The quantitative nature of statistical
analysis provides a solid numeric framework to provide objective support for relationships
between variables and hypotheses. These statistics make it easier for organizations to make
well thought out decisions to serve customers better and provide relevant products and
services to align with long-term goals and a positive impact on productivity.
Yielding data that is easily calculated and analyzed. The precision offered by numbers
and percentages can provide answers that can be analyzed by performing arithmetic
functions. They do not need to be coded, unlike qualitative data, to improve
understandability. This cuts down on data processing time while producing relevant results.
Yielding a larger respondent pool. Before implementing any statistical analysis
techniques, you need to have a data set. It is important to note that the data set for
quantitative research is typically larger than that of qualitative research because it consists
of close-ended questions, which are less time consuming, thereby encouraging more people
to complete the survey or questionnaire. The larger data set allows you to have a more
accurate sample representing the population which provides greater credibility to any
results derived from the analysis
