please do as it is mentioned

Business Question Addressed

What ticket sale trends exist that may help us increase attendance?

This assignment focuses on understanding how attendance and capacity utilization have changed across 2023, 2024, and 2025 for the Battle of the Badges hockey event.

Important Context for This Assignment (Read Carefully)

Although the Battle of the Badges event is held at the same venue each year, attendance performance is best evaluated relative to total capacity, not just raw ticket counts.

Raw ticket counts tell us how many tickets were sold or distributed, but they do not indicate how full the arena was or how effectively available capacity was used. Percentages, on the other hand, provide a normalized measure of attendance performance, allowing for clearer comparison across years and clearer communication with decision-makers.

For this reason, analysts often examine both counts and percentages:

  • Counts show absolute volume
  • Percentages show utilization and performance relative to capacity

This assignment asks you to compare both views and evaluate which is more informative for understanding attendance trends over time.

Purpose

In this assignment, you will:

  • Create Excel charts using ticket counts and ticket percentages
  • Compare attendance patterns across multiple years
  • Evaluate which metric (counts or percentages) is more appropriate for year-to-year comparison
  • Interpret your charts in the context of a real business decision

The goal is to connect data structure visualization choice business reasoning.

Data for This Assignment

You will use the Event Audit / Summary sections from:

  • 2023 Final Ticket Sales.xlsx
  • 2024 Ticket Sales Report.xlsx
  • 2025 Final Tickets.xlsx

From each file, you will extract:

  • Sold
  • Comps
  • Opens
  • Corresponding percentages (when available)

Part A: Multi-Year Ticket Counts Chart (4 points)

Step 1: Extract Ticket Counts

From each years Event Audit summary, record the following:

Year Sold Comps Opens
2023 ___ ___ ___
2024 ___ ___ ___
2025 ___ ___ ___

Step 2: Create the Chart

  1. Select the table above.
  2. Go to Insert Column Chart Clustered Column
    (This is commonly referred to as a bar chart.)
  3. Add:
    • Chart Title:
      Ticket Counts by Year and Ticket Type
    • X-axis label: Year
    • Y-axis label: Number of Tickets
  4. Add data labels so the counts appear on top of each bar.

Part B: Multi-Year Ticket Percentages Chart (4 points)

Step 1: Extract Ticket Percentages

From each Event Audit summary, record the ticket percentages:

Year Sold % Comps % Opens %
2023 ___ ___ ___
2024 ___ ___ ___
2025 ___ ___ ___

(If percentages are not explicitly provided in the report, calculate them using the totals shown.)

Step 2: Create the Chart

  1. Select the percentage table.
  2. Insert a column chart.
  3. Add:
    • Chart Title:
      Ticket Distribution by Year (Percentage of Capacity)
    • X-axis label: Year
    • Y-axis label: Percentage of Capacity
  4. Add data labels showing the percentages on top of each bar.

Part C: Interpretation Questions (2 points)

Answer the following in complete sentences.

Question 1

Which chart (counts or percentages) is more appropriate for comparing attendance across years?
Explain why, focusing on what each metric reveals about attendance performance.

Question 2

If you were presenting these results to Dartmouth Health leadership, which visualization would you emphasize when discussing attendance performance? Why?

Submission Instructions

  • Submit one Excel file that includes:
    • Your two data tables
    • The counts chart
    • The percentage chart
  • Charts must include:
    • Clear titles
    • Labeled x- and y-axes
    • Data labels on bars
  • Use professional formatting.
  • Submit one Word document that includes the answers to your Questions from Part C.

Reminder

This assignment is about thinking like an analyst, not just using Excel. Your explanations should be:

  • Grounded in the charts you created.
  • Aware of the difference between absolute ticket counts and percentage-based measures of attendance performance.
  • Clearly written and logically argued.

Homework Rubric: Visualizing Attendance Trends Across Years

Total Points: 10

Part A: Multi-Year Ticket Counts Chart (4 points)

Criteria Excellent (Full Credit) Partial Credit Points
Correct data extraction (counts) Sold, Comps, and Opens counts correctly extracted for all three years One or more values incorrect or missing 1
Appropriate chart type Clustered column (bar) chart correctly used to compare ticket types across years Chart type used but not ideal for comparison 1
Chart labeling & formatting Clear, descriptive title; x- and y-axes labeled correctly Missing or unclear title/axis labels 1
Data labels displayed Ticket counts clearly displayed on top of each bar Data labels missing or incomplete 1

Part B: Multi-Year Ticket Percentages Chart (4 points)

Criteria Excellent (Full Credit) Partial Credit Points
Correct data extraction (percentages) Sold, Comps, and Opens percentages correctly extracted or calculated for all years One or more values incorrect or missing 1
Appropriate chart type Clustered column (bar) chart appropriately used for percentage comparison Chart type used but limits interpretability 1
Chart labeling & formatting Clear, descriptive title; axes labeled with correct units (percentage) Missing or unclear labels 1
Data labels displayed Percentages clearly displayed on top of each bar Data labels missing or incomplete 1

Part C: Interpretation & Business Reasoning (2 points)

Criteria Excellent (Full Credit) Partial Credit Points
Comparison of counts vs. percentages Clearly explains why percentages are more appropriate for year-to-year comparison given changing arena capacity Mentions difference but explanation is vague or incomplete 1
Connection to business context Interpretation explicitly references the SNHU Arena capacity difference (e.g., 2024 upper bowl not opened) and ties insights to attendance strategy Business context mentioned but not clearly integrated 1

Requirements: as mentioned

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