Week 4 Written Assignment: Week 4 Problems And Exercises

Week 4 Written Assignment Week 4 Problems Analyticsexercises From

Find an example or article from business or science regarding parameter estimation. Write a brief report describing this study and how the researcher used this tool for estimation. What are the benefits of this estimation?

Paper For Above instruction

Parameter estimation is a core component of statistical analysis that enables researchers and analysts to infer population characteristics from sample data. It involves using sample data to estimate underlying parameters, such as means, proportions, or variances. This process is fundamental in both business and scientific investigations because it provides a basis for decision-making, hypothesis testing, and predictive modeling. An illustrative example of parameter estimation comes from the field of healthcare, where researchers aim to estimate the average blood pressure level of a population to assess cardiovascular health risk.

In a recent scientific study published in the "Journal of Clinical Medicine," researchers sought to estimate the mean systolic blood pressure (SBP) across a large urban population. Due to the impracticality of measuring the SBP for every individual, the researchers collected a random sample of 1,000 adults. Using this sample data, they applied the sample mean as an estimator of the population mean SBP. The sample mean was calculated to be 125 mm Hg, with a standard deviation of 15 mm Hg. The researchers used this sample mean as a point estimate of the population parameter under study.

This estimation process exemplifies the use of statistical tools to infer characteristics of a larger group from a manageable subset. The researchers also constructed a confidence interval around the point estimate, providing a range within which the true population mean is likely to lie with a specified level of confidence (e.g., 95%). This interval was calculated to be approximately 124.2 mm Hg to 125.8 mm Hg, indicating the precision of the estimate.

The use of parameter estimation in this context offers several benefits. First, it allows the researchers to make informed inferences about the entire population without the need for exhaustive data collection, thereby saving resources and time. Second, it provides a quantitative measure of uncertainty through confidence intervals, enhancing the interpretability of the findings. Third, parameter estimation supports evidence-based decision-making, such as evaluating the effectiveness of public health interventions aimed at reducing blood pressure levels.

In business, parameter estimation is similarly vital. For example, a retail company might sample customer satisfaction scores to estimate the average satisfaction level of its entire customer base. By employing techniques such as the sample mean and confidence intervals, managers can gauge overall customer sentiment and determine whether improvements are needed. This information guides strategic decisions, like enhancing service quality or adjusting marketing strategies. Moreover, parameter estimation facilitates risk assessment and resource allocation, critical components of effective business management.

Overall, the application of parameter estimation enhances operational efficiency and decision accuracy. It simplifies complex data analysis by providing reliable estimates with known levels of uncertainty. The core advantage lies in its ability to use limited sample data to accurately represent larger populations, thereby enabling better planning, policy formulation, and scientific understanding across various fields.

References

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