Objective probability refers to the chances or odds that an event will occur based on the analysis of concrete measures rather than hunches or guesswork. Each measure is derived from recorded observations, hard facts, or a long history of collected data. The probability estimate is computed using mathematical equations that manipulate this data to determine the likelihood of an independent event occurring. An independent event is one whose outcome is not influenced by prior events.
In contrast, subjective probability might utilize some method of data analysis but also injects guesstimates or intuition to determine the chances of a specific outcome.
Objective vs. Subjective Probability
Objective probabilities provide a more accurate way to determine the probability of a given outcome than subjective probability. The latter is largely based on human judgment and experiences, whereas objective probability allows the observer to gain insight from historical data and then assess the likelihood of a given outcome.
Key Takeaways
- Objective probability assesses the likelihood an event will occur using recorded observations or a long history of collected data.
- Subjective probability allows the observer to gain insight from personal experience and educated guesses.
- In finance, utilizing objective probabilities for decision-making is preferable to relying on subjective stories, personal experiences, or anecdotal evidence.
Subjective probability lets an observer leverage their own experiences and learned insights, producing estimations or intuitive assessments rather than basing conclusions solely on hard data and facts. On the other hand, objective probability focuses more rigorously on empirical evidence, utilizing statistics, experiments, and mathematical measurements, devoid of emotional influences or anecdotal justifications. In the financial realm, employing objective probability is crucial to avoid emotionally swayed investment decisions.
Examples of Objective Probability
The Flipping Coin Experiment
Consider determining the objective probability that a coin will land ‘heads’ up by flipping it 100 times and recording each observation. This experiment would likely yield a result of the coin landing on ‘heads’ approximately 50% of the time, showcasing a purely objective probability.
Predicting Weather Patterns
Comparatively, an example of subjective probability might be when an informed individual assesses weather patterns using barometric pressure, wind shear, and ocean temperature to predict a hurricane’s direction based on previous experience and intuition. While data provides a foundation, the ultimate prediction remains subject to the individual’s guesstimated probabilities.
Analyzing probabilities or conducting any statistical analysis necessitates that each observation stands as an independent event, free from bias or manipulation. The fewer biases in observations, the less biased the resulting probability will be, making a compelling case for objective over subjective probabilities.
Objective methodologies, anchored in hard data, mathematical models, and experiments supplant guesswork, hunches, and intuition, offering a trustable blueprint for understanding future probabilities.
Related Terms: subjective probability, independent events, data analysis, experiment, historical data.
