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Quantitative observation: definition, characteristics and example

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Data Analysis using Qualitative and Quantitative Techniques1
Table of Contents

What do you mean by quantitative observation?

The word quantitative means something that can be numbered or measured in numbers. quantitative observation refers to the data collection method which brings you the data in the form of numbers and values. The data gathered from quantitative observation is depicted in terms of a measurable quantity.

The results of quantitative observation are calculated through statistical and numerical analysis methods. The data indicates that the observation is being made often by entities that can be measured or presented using a numerical value. Some examples of quantitative observation entities can be age, shape, height, wait, volume, etc.

Quantitative observation is done on a group of participants called a sample population, which is considered as a representative of a larger population. This larger population is mostly market targets, target customers, or research study subjects. It is always advisable to have a sample population of a larger size so that the observations consider all the diversity that exists within that population. Along with that, it also ensures higher reliability in results and less biased answers.

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Characteristics of quantitative observation

  • Data accuracy – as the quantitative observation gives you data that can be measured in numbers, you can actually see the statistical calculations that go behind that data analysis and be sure about how accurate the results are.
  • Constant results – as the results of quantitative data analysis or in numbers, they are constants. For example, the average height of the students studying in the same class turns out to be 4 inches. This is a solid number and you do not have to guess or predict any conclusions here.
  • Sample population – quantitative observation demands to have a sample population that is the best representative of the entire population under study. It is important that the size of this population sample is large enough to be considerate of all the diversity’s and biases within the population.
  • Research – scientists use quantitative observation on a large scale to help them quantify various aspects of science.
  • No bias – quantitative observation provides quantified results which are generally derived from non biased observations. although the researchers do include a margin of error based on their respective hypothesis.
  • Results and reliability – When a researcher has to observe the sample population for qualitative data, he/she can use quantitative results to be derived from qualitative observations so that it increases the reliability of the results.
  • Statistical analysis – one observation uses statistical analysis to cross check the details and facts behind the collected data.
  • Use of instruments – quantitative observation makes use of various mathematical instruments such as thermometers, balances, rulers and so on to analyze the gathered data.
  • Data analysis methods – going to give observations also use various data analysis methods such as scales, tables, graphs, checklists, ratings and so on which helps the researcher analyze and process the data using scores.

Quantitative observations in business

Quantitative observations are way different than qualitative observations, which focus more on the quality of the data collected. So when we talk about quantitative observations, the researcher is expected to look at the numbers and figures that are in front of him, try to put the observations on a scale and try to quantify it.

In businesses, where fields like sales, marketing, customer reach, product competition, etc. play an important role in defining how your business does on the market level. In such cases it is important for the organization to make emotionless but rational decisions while studying the market. Quantitative observation just does the trick for such organizations to bring out the numbers and statistical understandings of the market trends and changes. 

Quantitative observations are set to be factual because as we know the numbers don’t lie. so it can be considered as an ultimate resort for the conclusions to be made if you like to make decisions based on facts and proofs.

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Quantitative observation example

Consider the following customer survey question:

How satisfied are you with our customer service?

  • Very satisfied
  • Somewhat satisfied
  • Neutral
  • Somewhat unsatisfied
  • very unsatisfied

If you look at the question, you are actually asking the customer to tell you the quality of your customer service. but imagine asking a question like this, “please explain in short about your customer service satisfaction”. you surely will get your answer but in a paragraph form, where did respondents will try to tell some good things and some bad things about your customer service first up but when you sit down to analyze these descriptive data, you will understand that it is actually hard to decide what the overall existence of that answer was, whether the customer likes your customer service or he doesn’t? 

but in our question, we have numbers assigned to some general answers of the question. These answers can be spread out on a scale of 4, 5, 7, depending on how detailed you want your answer to be. So when the customers select their choices, you will have direct numbers of the customers well choosing the options and how many times. So you just have to take one look at the gathered answers and analyze them based on which option was chosen the most, and that is what the majority of the customers feel about your customer service.

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