Graded Summary Report New Perspectives Excel 2019 Module 6

Graded Summary Reportnew Perspectives Excel 2019 Module 6 Sam Proje

Analyze and format departmental data for Oval Lake Hospital using Excel 2019. Your tasks include unfreezing panes, sorting data, inserting total rows, applying conditional formatting to identify duplicate values, formatting ranges as tables, adding records, creating subtotals, removing duplicates, changing data visualization formats, writing summary formulas, and preparing tables for future data input. Follow each step methodically to enhance data readability, accuracy, and presentation for hospital analysis.

Paper For Above instruction

Oval Lake Hospital, located in South Florida, relies heavily on precise and well-structured data management to facilitate effective decision-making within its various departments. The use of Excel 2019 provides an essential tool for organizing, analyzing, and presenting healthcare data efficiently. This report demonstrates how to perform a series of advanced data management tasks in Excel, focusing on departmental datasets related to patient admissions across different hospital units.

The first step involves working with the "Cancer Center" worksheet. By unfreezing the top row, the data becomes easier to navigate, especially when dealing with lengthy datasets. Sorting the data first by "Admission" in ascending order and then by "Service" facilitates an organized view that groups similar service types together, enabling quick identification of patterns or anomalies. Adding a total row to this table allows for immediate calculation of the total admissions for 2021, 2022, and 2023, critical for trend analysis over these years.

Next, applying conditional formatting to the range C4:C11 helps identify duplicate service names, ensuring the hospital staff can assess whether redundancies are impacting operational efficiency. This visual cue—Light Red Fill with Dark Red Text—helps in quick recognition of duplicate entries, which might warrant further data cleansing or process adjustments.

Switching attention to the "Cardiac Care" worksheet, the first column is frozen to facilitate comparison across the dataset. The data range A3:F10 is then formatted as a table with headers, using the "Gold, Table Style Medium 5" style. Naming this table as "CardiacCare" simplifies referencing in formulas and further data manipulations. Adding a new record to this table involves entering data at the end, which is a common task in maintaining up-to-date records.

The "Maternity" worksheet presents a scenario where data needs to be summarized using subtotals. After sorting the data by "Admission," the table is converted into a range for flexibility. Subtotals are inserted to display the sum of admissions, including specific year totals for 2021, 2022, and 2023. This approach enhances understanding of departmental workload variations over time and supports resource allocation decisions.

In the "Psychiatric" worksheet, duplicate records based on "Admission" and "Service" are removed to ensure data accuracy. Additionally, the data bars in columns D to F are reformatted to use solid green fill, improving clarity and readability of visual data representations, especially when dealing with extensive numerical data.

Furthermore, on the "All Departments" worksheet, total admissions for each year are calculated using structured references in formulas. These totals underpin hospital-wide analysis, providing a snapshot of patient activity annually. Preparing the table for upcoming 2024 data involves adding a new column at the end, which will simplify future data input and maintaining data integrity.

Throughout these tasks, Excel tools such as sorting, formatting, table creation, subtotaling, conditional formatting, formula writing, and data management are employed to enhance data clarity, facilitate analysis, and support decision-making processes across hospital departments. Implementing these techniques allows hospital administrators and staff to maintain an organized, accessible, and insightful dataset, ultimately supporting the hospital's operational efficiency and strategic planning efforts.

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