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Quantitative Observation: Definition, Types and Examples

Conduct Quantitative Research With Voxco


Table of Contents

Quantitative observation implies an objective collection of data for analysis based on their numerical and statistical attributes. 

This observation involves the depiction of obtained variables in terms of their quantity. The primary focus is on numbers and values. For instance, quantitative observation is associated with measuring values such as weight, volume, age, etc. 

A quantitative observation is referred to as “Standardized Observation” by the University of South Alabama. Due to the nature of quantitative observation, it is used for market research that can be tracked and measured precisely. This form of observation is generally used by most fields of sciences except social sciences. 

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Example statement of Quantitative Observation

Quantitative observation
  • The water weighs 5 liters.
  • There are 15 girls and 12 boys in Class 8.
  • She had a profit of $ 5000, in her online store, this year in comparison to the previous year.

Characteristics of Quantitative Observation

Quantitative observation 2
  • Accurate result: The data obtained under quantitative observation when analyzed, provides accurate results. The result produced is quantifiable. 
  • Fixed Result: The result of this observation is not subjected to change as long as the variables affecting the result remain the same. The result remains constant and fixed. For instance, the freezing point of water is 0 degrees Celsius, and this observation remains the same.
  • Scientific Findings: A quantitative observation is best practiced in respect of scientific research. For example, temperature, weight, volume, distance, etc., are all variables that can be measured using quantitative data analysis. For Example, 
      • The newborn puppy weighs 250 grams.
      • The apartment I wanted to rent is 990 square feet in size.
  • Unbiased: In the case of quantitative observation, the result gathered is usually biased-free, and accurate. There may be a possibility of a thin line of error. Also, it requires a shorter time for the entire process. 
  • Reliable: Results obtained under quantitative observation are generally highly reliable due to their depending on numerical and statistical quantifiers. However, quantitative observation can be used to increase the reliability of the qualitative analysis. For example, 
      • The water is icy cold. (Qualitative observation)
      • The water is -1 degrees Celsius. (Quantitative observation)                                                    
  • Numerical and Statistical: The data and the result derived in a quantitative observation are numerical. Additionally, they can be verified by statistical analysis.
  • Purposeful planning: A quantitative observation is created based on a well-defined purpose of the survey. After the purpose of conducting the observation is established, you can change the settings based on the requirements and also the method. For example, quantitative observation generally uses surveys, questionnaires, or polls to gather data.
  • Usage: A quantitative observation is popularly used for research that requires data quantification and categorization. It can also be used to categorize data based on qualitative attributes. For instance, if your company requires information on the number of customers who are using your products, then quantitative observation methods can be used. 
  • Data Sample: A quantitative observation requires observation of a large number of participants. It depends on the volume of participants for reliable and meaningful data. The more data collected, the more the result is reliable and accurate. A large number of participants don’t reveal much but it helps the researcher to find credible patterns and trends. 
      • Qualitative data is analyzed from the data gathered at the end of the survey, unlike qualitative data which is analyzed as the data is obtained. 
  • Objectivity: A quantitative data is obtained based on a fixed parameter. Also, it depends on fixed numerical values to quantify and categorize the data sample. The variables don’t undergo a change which gives a more definite result.
  • Deductive Analysis: A quantitative observation undergoes deductive analysis. This means that a researcher develops a theory and based on the theory a hypothesis is built. The data sample is then collected based on the hypotheses and analyzed, to make a quantitative observation.
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How to use Quantitative Observation

NPS® : Net Promoter Scale can be used to obtain quantitative observation. The numerical value derived from the survey method will give the impression of customer loyalty and promotion. For example,

  • How likely would you be to recommend our hotel to your friends and colleagues?

A scale of 1 to 10, ranging from highly unlikely to highly likely in increasing order, can be used. The result will provide us with three groups of customers Promoter, Passives, and Detractors. The result for the quantitative observation can be obtained by using the NPS® formulas. NPS® is a key metric for market research.

NPS® = % promoters – % detractors X 100.

Likert Scale: A Likert scale is also used to make a quantitative observation. Survey-based on employee satisfaction can be analyzed as a quantitative observation. For example,

  • How satisfied are you with your team?

With a 5-point Likert scale, ranging from 1- very unsatisfied to 5- very satisfied, the opinions of the employees can be converted into a numerical variable. The values can then be analyzed under quantitative observation.

Example of Quantitative Observation

  • In a survey of school students between age 12 to 18, 100 favored playing football over video-games.
  • The company has 5 books scheduled to be published in the next 2 months, in order to increase the sales rate by 20%.
  • According to BARC, 9% of the TV viewer’s ratings increased during the pandemic, in the year 2020.

In conclusion, Quantitative Observation is objective in nature and concerned with the numerical parameters of the data gathered in the survey. Although it can be used for market research, it is mostly used for scientific research, it involves conducting a survey on a large number of participants.

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