Pros And Cons Of Observation In Research

Cons
• One problem with observation is that it can be very resource intensive. It might involve great amounts of time and energy, which can be a problem if those resources are not available in adequate quantity. If there is less time for the research to be carried out it might lead to hurried observation which dilutes the quality of the data collection process and thus has an adverse impact on the analysis
• Since observation is being carried out by a human being, there exists a risk of observer bias. It is not necessary that the observer will always be unbiased and thus there will always be a question mark over the sanctity of the data collected.
• Another problem with observation is the effect of the observer on the behavior of those being

It is normally available for free or at low cost and can save a researcher a lot of time, effort and money.
• There may be situations where the researcher needs to focus on collecting both primary data and secondary data. Secondary data being available with relative ease allows a researcher to focus his/her energies on the collection of primary data.
• Secondary data is normally collected in the best possible manner and thus can be used as a means of measuring the quality of the primary data. This will allow the researcher to focus on finding out the qualitative and quantitative gaps if any and figure out how to fill in the

This gives the researcher an opportunity to be better focused on the problem in hand and better identify the analytical process to be used thereof.
Cons
• One risk associated with secondary data is the fact that its accuracy is sometimes not assured no matter how good the quality of the source. We may not have information about how such data was collected or the scope of the survey. This has a direct impact on the usefulness of the secondary data to one’s own research.
• Secondary data is not possible or useful in every situation. For example, if there is a research program being conducted on a market research, the existing secondary data may not be applicable since the market is a constantly changing environment and unpredictable. Secondary data is more useful in predictive environments than in other environments.
• Secondary data may be outdated. It may not be a true reflection of the current reality. There may have existed factors in the past that are not present today. It is not necessary that every factor has been taken into consideration and thus, there is no assurance that the secondary data is relevant as of