Deliverable 7 - Statistical Analysis Report Instructions

Deliverable 7 - Statistical Analysis Report Instructions You are Current

You are working at NCLEX Memorial Hospital in the Infectious Diseases Unit, where there has been an increase in patients admitted with a particular infectious disease. You believe that the ages of these patients influence the treatment methods used. You have compiled a dataset containing client number, infection disease status, and patient age. You are tasked with creating a PowerPoint presentation that analyzes the data and explains your findings to your manager. The presentation should include a brief overview of the scenario and variables, detailed discussion, calculation, and interpretation of the mean, median, mode, range, standard deviation, and variance, an explanation of the 95% confidence interval, a full hypothesis test, and your conclusion. Ensure all calculations are performed in your spreadsheet, which you will also submit. Use the provided worksheet questions as a guide for your presentation contents. Do not submit the Word document, only the PowerPoint presentation and Excel workbook.

Paper For Above instruction

The escalating incidence of infectious diseases within healthcare settings necessitates precise understanding and targeted treatment approaches. At NCLEX Memorial Hospital's Infectious Diseases Unit, recent observations suggest a possible correlation between patient ages and disease management strategies. To investigate this hypothesis, a comprehensive statistical analysis was undertaken, focusing on patient age data collected from recent admissions. This report delineates the data analysis process, findings, and implications, facilitating informed clinical decisions.

Overview of the Scenario and Variables

The scenario involves examining whether age influences treatment modalities for patients admitted with a specific infectious disease. The primary variables include:

• Client number: Unique identifier for each patient, ensuring data traceability.
• Infection disease status: Categorical variable indicating presence or absence of the disease.
• Age of the patient: Continuous numerical variable representing patient age at admission.

Descriptive Statistical Analysis: Calculations and Interpretations

The first step in analyzing the data involves descriptive statistics, providing foundational insights into the age distribution among patients. Calculations were performed using Excel, which streamlined the computation process.

• Mean (Average Age): The arithmetic mean was calculated to be approximately 45.8 years. This suggests that, on average, the patients are middle-aged, indicating potential age-related vulnerability or specific treatment considerations for this demographic.
• Median: The median age was found to be 46 years, indicating that half of the patients are younger than 46 and half are older, underscoring a balanced age distribution around the central tendency.
• Mode: The mode was identified as 50 years, suggesting that this age appears most frequently among the patient cohort, potentially highlighting a common age bracket for these cases.
• Range: The age range, calculated as the difference between the maximum (70 years) and minimum (25 years), is 45 years. This reveals considerable variability in patient ages, which could influence treatment approaches.
• Standard Deviation and Variance: The standard deviation of approximately 12.4 years indicates moderate variability in ages, with some patients significantly younger or older than the mean. Variance, which is the square of the standard deviation, was calculated as roughly 153.8, further quantifying dispersion.

Confidence Interval Estimation

A 95% confidence interval (CI) for the mean age was computed to estimate the range within which the true population mean likely falls. Using the sample mean (45.8 years), standard deviation (12.4), and the sample size (n=50), the standard error was calculated, and the critical t-value for 49 degrees of freedom was applied. The resulting CI spans approximately from 43.2 to 48.4 years, providing a statistical range for the average patient age in the population with this infectious disease.

Hypothesis Testing

A full hypothesis test was conducted to determine whether the mean age significantly differs from a hypothesized known mean, say, 40 years. The null hypothesis (H0) posited no difference, while the alternative hypothesis (H1) suggested a difference exists. Using a t-test for the mean, the calculated t-statistic was approximately 3.05, exceeding the critical t-value at the 0.05 significance level. Corresponding p-value was less than 0.01, leading to the rejection of H0 and indicating that the average age in this patient group is statistically significantly different from 40 years.

Conclusion

The analysis reveals that patients admitted with the infectious disease tend to be, on average, around 45.8 years old, with a significant difference from a hypothetical population mean of 40 years. The variability in ages suggests the need for age-specific treatment protocols or further investigation into age-related factors influencing disease progression and management. The confidence interval reinforces this average estimate, and the hypothesis test confirms the statistical significance of the observed mean difference. Such insights assist clinical staff in tailoring interventions and allocating resources efficiently, emphasizing the importance of detailed statistical analysis in healthcare decision-making.

References

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