Everything You Need to Know About

Quantitative Research

OVERVIEW

It may not be all that obvious, but we’re surrounded and guided by numbers every single day,

everywhere we go. All our decisions are based, in one form or another, on numbers. Whether

in our personal or professional lives, numbers are always at work.

It is no surprise that in big business, numbers are also crucial. They help us identify

areas that need improvement, areas where we stand out, and the overall viability of our business future.

Numbers can drive decisions, both big and small. How do firms get the right numerical data so they can make better informed decisions? Enter

quantitative research.

Quantitative research is an umbrella term for the complete process of gathering data through

standardized or protocol-driven techniques. Analysts then apply statistical methods to these

numbers to get important insights.

WHICH PROBLEMS REQUIRE QUANTITATIVE RESEARCH?

If an organization is trying to make certain predictions regarding its marketing campaigns, it

would be too expensive to get data directly from a huge number of people. Quantitative

research enables researchers to use a small segment of a larger audience and project its

findings to the complete audience. This system is conclusive and objective.

For instance, a pet food company is thinking of launching a new product line. It would conduct

a survey on a segment of its existing market. These are consumers who fit the general profile

of the rest of this company’s target market. Based on the taste preferences of the pets of those consumers, the pet food company can then project the findings of these results to its larger target market.

Another example: A nonprofit organization is running a program that helps rural villagers read

and write. The NGO would look at the number of how many individuals attended their

program and how many persons dropped out.

They would then compare these individuals' literacy test scores before they enrolled, and after

they graduated from the program. Using this data, the organization can then get a very clear

understanding of the overall effectiveness of the NGO's village literacy program.

What sets quantitative research apart from qualitative research is the fact that it's usually not

employed at the initial research stages for diagnosing a particular problem or exploring a

specific issue. Instead, quantitative research is generally implemented when research studies

are already ongoing. It is intended to deliver answers to predefined and clearly spelled out

questions.

How to Plan a Study Using Quantitative Research

Clearly Identify the Study's Central Problem

For instance: How does New York City's government ensure less subway commuter

accidents in its subway network?

Compose the Research Study's Questions

All questions must be formulated to directly address the specific problem of the research

study. For example: How many subway commuters report accidents in the course of their use

of the New York subway system?

Once the question is tightly defined, look through existing research databases at universities

or online journal search engines to see if somebody has posed this question before. If there is

existing research already performed on your specific question, access those materials.

You don't have to reinvent the wheel, provided that these materials meet academic or

generally accepted research standards like peer review.

How can Your Organization Benefit from Quantitative Research Methodologies?

 Methods involving quantitative research can deliver relatively concrete and conclusive

answers to your research questions

 When research data is gathered and processed in accordance with generally accepted

standards and protocols, the results of the studies can usually be trusted

 If samples are large enough to be statistically significant, the findings of these studies

can usually be projected to a larger population

It's important to make sure that quantitative research samples are a product of studies that

have been chosen and designed carefully. Otherwise, the results that you get from these

studies might not be statistically representative and you won't be able to generalize your

findings to a larger population.

Common Limitations of Methods that Use Quantitative Research

 They don't account for subject's individual perceptions or thoughts regarding the

phenomenon your study is evaluating

 They focus solely on the "what" and "when" instead of the "how" and "why" issues of a

phenomenon

Which Quantitative Research Methodologies are Available for Researchers?

There are four basic methods that can be used in quantitative research for effective data

collection and analysis.

Questionnaires

These series of questions are probably the most common method of gathering quantitative

information. These questions are often printed out or they can be presented in digital form.

Researchers distribute the questionnaires to the individuals in their research study sample

group. All study participants answer the questionnaire's queries.

These questions are specifically chosen and carefully designed to collect data that can enable

researchers to get the answer to the central questions of their study.

Generally, questionnaires ask closed-ended queries. In other words, the study participant only

needs to choose among the existing answer options presented by the question.

Depending on the type of study you're conducting, you may also use quantitative open-ended

queries. One example of an open-ended question is: "How many times do you go to the gym

per week?" Or, another open-ended question is "How many cans of diet soda do you drink

every week?"

These questions don't have a preset answer. The study participant is completely free to

answer based on their experience.

Closed-ended questions, on the other hand, give you specific options that limit your choices.

For example, "How many times do you go to the gym per week?" The options could be 0

days, 1 to 3 days, 4 to 5 days, 6 days, or all 7 days.

It's important for quantitative research designers to choose carefully between open-ended and

closed questions. Click here to check our guide on when you should use closed or open-

ended questions and how to craft these types of queries.

Regardless of your question type, the materials in your questionnaire must have a well-

defined and clear objective. It must be easy to understand, written in plain language, and is

free from spelling, grammar and typo errors.

Strengths

 Questionnaires take much less time than doing one-to-one or other direct person-to-

person quantitative research

 They are a fairly straightforward, simple, and common way to gather data

 They allow for cost-effective approach to collecting information from large population

samples

Weaknesses

 Question responses may be limited in scope and lack depth

 Survey participants might get bored or refuse to complete the questionnaire if they

think it's too long

 Respondents might not read the questions properly or misunderstand it. Both these

situations can lead to unreliable and inaccurate responses

Response Bias

Response bias refers to a number of factors that can influence participants to supply incorrect

answers. Response bias can seriously compromise the data quality of your survey. Click here

to learn how response bias comes about and what you could do to avoid it.

One-to-One Interviews

Quantitative research interviews involve talking to people directly. These are one to one

interactions between the researcher and the study participant.

Just like with other quantitative research methods, the sole goal of such interviews is to

collect numerical data. These can be done face to face or through the phone. It can also be

freeform or can follow some sort of structured script.

In structured interviews, the participants are asked by the researcher a set number of

questions. The questions are determined in advance by the person conducting the interview.

The interview is quite formal and follows a preset pattern. Not surprisingly, structured

interviews cost less money and time.

Unstructured interviews, on the other hand, involve questions that the researcher thinks of as

the interview unfolds. These questions just come to the interviewer and the whole flow of the

exchange is conversational. It is freewheeling, open-ended, and the interview can even

stretch for hours.

Unstructured interviews give researchers a tremendous amount of flexibility. They are also

able to structure and shape the question based on the answers the participants are giving

them.

These open-ended interviews tend to produce in-depth information because researchers are

given the freedom to pursue any issues or interesting points raised by the participant's

answers.

Strengths

 Unstructured interviews can provide very deep and nuanced information

 Unstructured interviews are generally more flexible than surveys and questionnaires

because interviewers can change their questions to fit each participant better. They

can also ask follow up queries

 Interviewers can also ask questions that clear up or more fully define the answers that

they were previously given

Weaknesses

 One-to-one interviews can take a long time

 Interviewer salaries, travel costs, and miscellaneous expenses can add up and make

interviews quite expensive

 Unstructured interviews may lead to answers that may be very hard to quantify

One effective way of reducing the cost of interviews is to conduct group interviews or focus

groups. Click here to get all the basic info you need to be able to conduct an effective focus

group discussion.

Observation

Observation involves collecting data by just observing people in their natural surroundings or

settings. Although this method is usually associated with gathering qualitative information,

observation can also yield quantitative data.

Observation can take the form of behavioral observation, or simple observation.

Simple observation is more objective. The researchers generally just looks at the numbers

involved. For example, "How many stray dogs are in a 1-square mile area of a specific city?"

Similarly, "How many people pass by the main student plaza in a specific university?"

On the other hand, behavioral observation focuses on observing and interpreting individuals'

behaviors. For example, "How many of the stray dogs in that 1-square mile are acting in a

menacing or alarming way?" Similarly, "How many people passing by the central student

plaza are riding their bikes in a reckless way?"

Simple direct observation can be a great method for gathering numerical data. This recording

can be achieved by using a set of numerical variables that are clear and can be collected

while observing.

For instance, "What time to students leave a class?" This information can then be gathered by

simply looking at students at many different buildings over an extended period of time, and

noting when students leave specific buildings or classrooms.

Strengths

 Observation is a fairly cheap way of gathering data

 Since researchers collect the information themselves instead of participants supplying

the data, most of the information gathered is usable

 Researchers can begin and stop data gathering whenever they want. This makes for a

very flexible quantitative research tool

Weaknesses

 Researchers or data collectors need extensive training so they know what to look for

and how to properly collect data

 From time to time, the research or the environment may produce bias, like when study

participants become aware that they are being observed.

 Sometimes, the situation that is supposed to be observed simply doesn't happen.

Researchers may end up wasting quite a bit of time trying to collect data

Behavioral observation versus simple observation is just one pairing of the different types of

observational data available out there. To find more information about the five types of

observation data and how you should use them, click here.

Records

Quantitative research requires numerical data. External data, also known as records, can give

important information that may supply these numbers.

Records are routinely kept by institutions. These take the form of statistics and inventory

records. These are taken and monitored as part of the general administration of any kind of

institution.

For instance, you can easily look up how many patients a hospital admitted within a certain

timeframe. The same applies to the number of students that attend a specific school within a

period of time.

In terms of larger populations, governments periodically and predictably conduct census

surveys. The US Census is one of the most powerful and consequential data sets for all sorts

of business and governmental planning.

To learn how census data is collected and how these are conducted, click here.

Strengths

 Records involve comprehensive, long range data that was collected over an extended

period of time

 It takes less time to collect this type of data because it's already been recorded and

stored by another organization or person

Weaknesses

 Records are usually restricted to numbers. It's very hard to see the reason or causes

behind these numbers

 Sometimes, records might have formatting or structure issues. These can take a long

time to correct and clean up

 When institutional records are inaccurate or incomplete, there is really no other

alternative to this type of material

Processing external data to detect and clean up bad information causes massive headaches

if you don't know what to do and what to search for. For a quick guide on how to deal with

data points and data records that are problematic, click here.

The Final Word

Quantitative research methodologies involve some of the best options for identifying problems

or phenomena and figuring out how extensive it is and how it changes over a period of time.

After zeroing in on the problem, quantitative research can be employed to identify trustworthy

solutions.

For quantitative research data to be trustworthy and valid, it has to be produced or processed

through standardized techniques.

Collecting better information is the initial step towards arriving at better decisions. Click here

for a guide on how to design a highly effective data collection plan.