Quantitative Observation Definition
Have you ever thought about this question “Quantitative Observation Definition” Today on Solsarin we’re going to answer this question.
What is quantitative observation?
Quantitative observation is a method of gathering and analyzing data. It uses numerical data and statistical calculations to measure research and draw conclusions.
It usually involves variables with a numerical value. Another form of quantitative observation is when researchers associate specific variables with a number, like rating their satisfaction on a scale of one to ten.
Typically, researchers use quantitative data when researching large groups of people, since their results may be more accurate depending on how large the group is.
It’s most common for researchers to use quantitative data to better understand the feelings, health and behaviors of large populations of people.
Commonly, researchers conduct in-person questionnaires, polls and surveys to gather their research, or they use online platforms to administer research.
Quantitative Observation Definition
Quantitative observation is an objective collection of data which is primarily focused on numbers and values – it suggests “associated to, of or depicted in terms of a quantity”.
Results of quantitative observation are derived using statistical and numerical analysis methods.
It implies observation of any entity that can be associated
with a numeric value such as age, shape, weight, volume, scale etc.
This observation technique is conducted on a sample which best represents the target market.
It is important to have a larger sample size so that the observations can be made considering most of the diversities that exist in a population.
By considering a large population, the observation results are most likely to have higher credibility.
Once a market researcher collects data from the sample, the process of analysis begins and observed results are attained.
The University of South Alabama has termed Quantitative Observation as “Standardized Observation” and it is mostly used in scientific research as it produces statistically observed information.
Quantitative Observation: Definition And Examples
Quantitative observation is the type of observation that deals in quantifiable variables, things that you can use numbers to express.
In contrast, qualitative observation focuses on the characteristics of specific events or experiences. Observation is necessary when it comes to scientific research and studies.
To gain a better understanding of the difference between qualitative observation and quantitative observation, let’s look at some examples of quantitative observation and contrast them with qualitative ones.
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Defining Qualitative And Quantitative Observations
Qualitative observation pertains to the collection of information about the quality or subjective experience of phenomena or events. A person doing qualitative observation is collecting information using his/her senses, hearing, seeing and feeling things.
The ability for researchers to have one on one interactions with participants allows the participants to confide in them and give them detailed descriptions of their thoughts, feelings,
and sensations during the events the researchers are studying.
This type of personal data collection becomes more difficult the more participants you have.
Quantitative observation involves the collecting of data that can be quantified, expressed numerically in some form.
As this form of observation deals with numbers and measurements, it’s reserved for objects or phenomena that can be tracked and measured with precision.
Though the data collected by the scientist must be
filtered through the scientist’s subjective experience,
it’s usually said that quantitative data is objective in nature.
The hard sciences, physics, chemistry, etc. usually deal with quantitative data and eschew the collection of too much qualitative data.
In order to make sense of quantitative data, a reliable system of measuring and interpreting data must be created. For this reason, scientists used standardized measurements for data.
Why Is Observation Important?
Before going any farther, we should cover why observation is important in scientific research. Without observation, it is impossible to draw any conclusions about the nature of the world.
People observe the environment and activity around them, collecting information on events and phenomena.
They then use the information collected (data) combined with reasoning and analysis to draw conclusions.
For any scientific research to occur, the scientists must observe the participants, plants, animals, or the environment they are studying.
Observation often has the goal of discovering relationships between different variables and events.
Benefits of quantitative observation
Here are several benefits of quantitative observation:
- Offers high level of accuracy: Quantitative data may be easier to validate, since researchers can check their calculations to ensure accuracy. For example, a scientist may check the accuracy of his quantitative data by running through the calculations several times.
- Ensures constant results: Quantitative data has results that remain constant, since typically the variables of the data are unchanging.
- Verifies research using statistical analysis: You can verify quantitative observation research by performing a statistical analysis of their data, like associational statistical analysis or descriptive statistical analysis.
- Increases result reliability: You may use qualitative observation to boost the reliability of your research. For example, a researcher may perform qualitative research, like a case study or interview with their target group, before performing quantitative research on them.
Quantitative Observation Characteristics
- Accuracy: Under quantitative observation, data can be measured (quantified) and so, it produces accurate results in comparison to other methods such as qualitative observation which produce results that can’t be quantified.
For example, the boiling temperature of water at sea level is 100°C is a quantitative observation.
- Constant Results: Results of this observation method are constant – the boiling point of water at sea level will be 100°C and will not change with other variables remaining constant.
- Sample Creation: A sample should be formed for quantitative observation and the size of this sample should be considerably large for researchers to generalize the observation to the entire population.
- Scientific Research: This method measures and “quantifies” multiple aspects mainly for scientific research.
- Bias-free Results: As the results are quantified, the observations derived from those are free from bias but have a margin of error involved and is usually based on a hypothesis.
- Improve reliability of results: For a marketer to have a quantity linked to his/her qualitative observation, he/she needs to conduct quantitative observation as well. A quantitative result can be derived for the qualitative observation to increase reliability on the results.
- Conduct statistical analysis: Quantitative observation verifies details by conducting statistical analysis of a statement.
- Numerical results: All the results of quantitative observation are numerical.
- Use various instruments: Instruments such as rulers, thermometers, balances etc. are used for quantitative observation.
- Methods to process and analyze data: There are various methods and to process and analyze collected information. Rich quantitative observational data can be processed using codes/scores, for example, evaluation scales, checklists, tables etc. can be created to analyze collected data.
- Create a plan: Based on the purpose of observation, a quantitative observation plan is created. On this basis of this plan, settings are changed and method of conducting this observation is decided.
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Characteristics of quantitative observation
Here are several characteristics of quantitative observation:
- A research plan: You can create a plan to conduct your research based on your reasoning for the quantitative observation. You can include information about your research setting, target group or timeline for the research.
- Scientific research: A major part of quantitative research involves interpreting the results of research and applying them to scientific methods. For example, a chemist may measure the temperature that a chemical freezes and then apply that temperature to other chemicals
- Large samples: Quantitative research involves creating samples that are large enough for researchers to draw conclusions about the entire population. For example, if a researcher is finding the average weight of a 5-year-old child in a certain town, they may survey hundreds of children within that town to get an accurate conclusion.
- Bias-free results: The results of quantitative research should be free from bias so that the results have more accuracy. You can keep your research bias-free by having several people collect research data or having participants of the research review your findings to check for accuracy.
- Numerical results: You should only record quantitative observation research as numerical.
- Research equipment: You may use tools like rulers, thermometers, scales or measuring tape to complete their quantitative research.
- Various methods for analyzing data: You can analyze quantitative data using various methods like checklists, tables, graphs and evaluation tables. You may use a template to insert the data into, or you may create your own document to analyze the data.
