Applications of Bernoulli Distribution in Business Statistics
1. Quality Control: In manufacturing, every product undergoes quality checks. Bernoulli Distribution helps assess whether a product passes (success) or fails (failure) the quality standards. By analysing the probability of success, manufacturers can evaluate the overall quality of their production process and make improvements.
2. Market Research: Bernoulli Distribution is useful in surveys and market research when dealing with yes/no questions. For instance, when surveying customer satisfaction, responses are often categorised as satisfied (success) or dissatisfied (failure). Analysing these binary outcomes using Bernoulli Distribution helps companies gauge customer sentiment.
3. Risk Assessment: In the context of risk management, the Bernoulli Distribution can be applied to model events with binary outcomes, such as a financial investment succeeding (success) or failing (failure). The probability of success serves as a key parameter for assessing the risk associated with specific investments or decisions.
4. Marketing Campaigns: Businesses use Bernoulli Distribution to measure the effectiveness of marketing campaigns. For instance, in email marketing, success might represent a recipient opening an email, while failure indicates not opening it. Analysing these binary responses helps refine marketing strategies and improve campaign success rates.