Reestimate: meaning, definitions and examples

Etymology

• The word combines 're-' meaning 'again' and 'estimate' which comes from the Latin 'aestimare', meaning 'to value or appraise'.
• Languages often use prefixes like 're-' to indicate doing something again, showing the action is revisited.
• The usage of 'estimate' has evolved over centuries, originally relating to physical appraisals and now often applied in various fields, including finance and project management.

Business

• In project management, reestimation is common as new data may alter timelines and costs, ensuring more accurate planning.
• Businesses often perform budget reestimates during a fiscal year to adjust for unexpected changes in income or expenses.
• Properly conducted reestimates can lead to better resource allocation, maximizing efficiency and minimizing waste.

Psychology

• Cognitive biases play a role in estimations; individuals may overestimate or underestimate based on prior experiences, emphasizing the need to reestimate for accuracy.
• Reestimating can reduce anxiety over uncertain outcomes, as it reflects adaptability to new information.
• Peer influence can affect how we estimate and reestimate, as discussions can shape our perceptions of likelihood and outcomes.

Science

• In fields such as statistics, reestimation is crucial after gathering additional data to improve the validity of conclusions drawn from research.
• Reestimation helps scientists adapt their hypotheses and experiments in light of new findings, ensuring the progress of knowledge.
• In environmental studies, reestimating impacts based on ongoing data collection can lead to more effective conservation strategies.

Technology

• In software development, sprint planning often involves reestimating tasks as programmers gauge initial estimates against real progress.
• Data analytics tools provide features that support real-time reestimation of predictions based on changing user behavior.
• Machine learning models often need reestimation to fine-tune their predictions based on new sets of training data.