Observation vs Inference
Observation and inference are going hand in hand. These are important techniques in scientific studies. Observation without inference has no value. Also, the inferences made without careful observation are invalid.
Observation is a way used by any animal or human, to receive information from the outside world. The information is received via the senses. For example, we look at things with eyes or hear with ears. Not only can the senses, equipment also be used to observe. Observation is very important in scientific work and studies.
An experiment or research starts when someone finds a new idea. Careful observation is important to find new ideas. Innovative products are coming because of this careful observation. Even when conducting an experiment, observations are important to gather data, predict the outcomes and to plan new experiments.
Observation is always subjective. Bias in observation is a common error that humans make. We tend to see what we expect or what we want to see. Therefore, depending on the observer, the results may vary. This makes it hard to compare. Especially, qualitative observations are hard to record and compare. Even in observing qualitative parameters, several observers are used, and data are collected in different times. This is done because, reproducibility of the observations is important in scientific work.
Observations are affected by various parameters. For example, observation is done with senses. Our senses are limited, and they are subjected to errors. For example, optical illusions can give the wrong idea from an observation. Humans have developed various technological instruments like telescopes, tape recorders, thermometers, microscopes etc., to make observation easier. These equipments enhance the power of observation of humans and reduce the errors in observation too.
Not only for humans, careful observation is important for animals too. A predator finds its prey through observing for hours. Also, a prey is always keeping its senses open for an attack from a predator.
Inference is drawing logical conclusions from available data. To make inferences, known set of data should be available or there should be information to make valid assumptions. Inferences are made from both qualitative and quantitative data.
A raw set of data is useless, if the inferences are not made with them. Inference shows the overall picture of an experiment. Therefore, even without looking at methodology, data and other information, the most important outcome of the experiment can be observed by looking at the inference. An incorrect inference is known as a fallacy. Biases in human reasoning can cause fallacy.
How humans draw conclusions and details about human inference is usually studied within the field of cognitive psychology, and artificial intelligence. Other than the traditional way of human inference, now researchers have developed automated inference systems.
Observation vs Inference
- Observation is receiving data from the external environment while inference is making a conclusion using those observed information.
- Inference is affected by observations. Without observation, there won’t be any inference.
- Inference gives validity to observed data.
- For observation senses are used. Intelligence is used, to make inferences.