Exercise 1 Refer To The Database In A17e316 Below
Exercise 1refer To The Database In A17e316 Below That Contains Monthl
To complete this assignment, you will analyze a given retail sales database spanning from 1992, performing various statistical, visualization, and data extraction tasks using Excel functions and tools.
First, you are required to create a relative frequency distribution of the percentage change data in Column E by constructing BINs and calculating their frequencies with arrays. Then, plot this distribution as a horizontal histogram using the specified data range and labelings. Subsequently, you will identify the five largest percentage changes, determine their rows via the MATCH function, and look up corresponding year information with VLOOKUP.
Next, filter the dataset to isolate records from December using the Data-Advance Filter feature, and forecast December sales using the TREND function in an array. You will also extend this forecast across future years, utilizing TREND again for projections until the specified range.
This assignment necessitates working with dynamic data filtering, array formulas, chart creation, and advanced lookup functions to analyze sales variability, identify key sales changes, and project future sales based on historical trends.
Paper For Above instruction
The comprehensive analysis of retail sales data from 1992 onwards aims to elucidate sales patterns, variability, and forecasting models through the application of Excel functionalities. This process encompasses constructing a relative frequency distribution, visual representation of data, extraction of key sales fluctuations, targeted data filtering, and trend-based forecasting. Such an analytical approach not only enhances understanding of sales dynamics but also equips decision-makers with predictive insights vital for strategic planning.
To commence, constructing the frequency distribution involves segmenting the percentage change data into bins to understand the distribution and variability comprehensively. The bins are created based on specified ranges, and the associated frequencies are calculated using array formulas with the FREQUENCY function. This methodological approach facilitates a succinct representation of data spread, highlighting the occurrence of various percentage change intervals.
The visualization stage entails plotting the relative frequency distribution as a horizontal histogram within designated cell ranges, labeling axes appropriately, and setting the chart title to contextualize the data. This visual tool enables quick assessment of the distribution shape, identifying predominant change ranges and potential outliers.
Further, the analysis of the top five percentage changes requires identifying the highest values using the LARGE function, which allows ranking of data points. The corresponding row positions are then located via the MATCH function, enabling linkage to specific records. To enrich the analysis, VLOOKUP retrieves the year associated with each row, integrating temporal context into sales fluctuations.
Subsequently, the dataset undergoes filtering to extract only December sales records, employing Excel’s Data-Advance Filter feature. This targeted dataset serves as the basis for precise forecasting using the TREND function, which estimates future sales based on linear trends. Forecasts are generated for December in forthcoming years as well as extended projections, aiding strategic planning and inventory management.
Through systematic application of these techniques—frequency analysis, visualization, record extraction, and trend forecasting—the exercise demonstrates how Excel's array formulas, filtering, and analysis tools collectively facilitate comprehensive sales data insights. This multi-faceted analysis provides actionable intelligence on sales variability, key fluctuation points, and future sales trajectories, essential for informed business decisions.
References
- Bamber, D., & Pienaar, J. (2015). Excel Data Analysis: Your visual guide to statistical methods. Peachpit Press.