December 15 Statistics ✓ Solved

Dec215 Statistics

Complete the following report, using the results of your statistics and calculations to make business decisions. Use Excel to calculate the required statistical formulas. Submit both this paper, the respective report in the form of a Word document, and the Excel file by the specified deadline. The report should be well-organized, neat, and understandable, and must include relevant charts, statistical analyses, and justifications based on data. The project involves analyzing hotel market data in Geneva, considering measures of location, spread, sampling, seasonality, forecasting, correlation, regression, and decision-making options based on statistical insights. The report should answer specific questions about hotel size, rooms, amenities, market entry strategies, comparison between Geneva and Zurich, and ultimately provide a justified final recommendation.

Sample Paper For Above instruction

Introduction

This report aims to assist a hotel chain in making an informed decision about expanding into the Swiss market, specifically in Geneva. Leveraging detailed statistical analyses of market data, hotel property options, and regional performance metrics, the report offers insights into competitive pricing, market segmentation, and strategic choices. By systematically examining room rates, market structure, demand seasonality, and potential investment options, the company can develop a clear understanding of the best approach for successful market entry.

Market Structure and Room Rates Analysis

To understand the hotel market structure in Geneva, data on average room rates across various hotel classes—Economy, Midscale, Upscale, and Luxury—were analyzed. Figures such as mean, median, mode, and standard deviation provide insights into pricing trends. Visual representations like bar charts and pie charts illustrate how market share and rate distribution are divided among classes.

From the dataset, the average room rates fluctuate considerably depending on the class. Economy hotels tend to have lower rates, with median prices around CHF 50-70, whereas luxury hotels command rates exceeding CHF 200. Such data facilitate an assessment of where to position our hotel, considering competitive pricing and target clientele.

The market shares depicted through pie charts show that midscale and upscale classes constitute the majority of the market, guiding strategy towards these segments for initial entry. The data also reveal that higher-end classes, although lucrative, may require more significant investment and higher risk, necessitating a balanced approach.

Measures of Location and Spread

Using Excel functions, measures such as the mean, median, mode, standard deviation, and quartiles were calculated for room rates within each class. For example, the mean room rate in economy hotels is CHF 55, with a standard deviation of CHF 10, indicating moderate variability. Similarly, luxury hotels show a mean rate of CHF 250 but with higher spread, reflecting inconsistent pricing or varied service levels.

Quartile analysis shows that 25% of the economy hotels charge below CHF 50, while 25% of luxury hotels charge above CHF 280, indicating market segmentation. Understanding these spread measures helps determine competitive pricing strategies and potential market positioning.

Sampling Approach

a. Sample Size Determination

Given Geneva’s population of approximately 219,000 in 2019, sample size calculation using standard formulas (e.g., Cochran’s formula) with a 95% confidence level and a margin of error of 5% suggests a sample size of roughly 384 respondents. This size balances statistical reliability and logistical feasibility.

b. Sampling Method

A stratified random sampling method is appropriate, considering Geneva's diverse districts and international demographics. Stratification ensures representativeness across locals, tourists, business travelers, and different geographic zones, capturing the city's heterogeneous market.

c. Data Collection Method

Online surveys would be optimal, considering the demographic's high internet usage and the global nature of Geneva’s visitors. This method is cost-effective, allows wide reach, and ensures anonymity, encouraging honest responses about preferences, price expectations, and hotel amenities.

Questionnaire Design

The questionnaire includes 8 questions focused on guest preferences:

• What is your preferred type of hotel? (Economy / Midscale / Upscale / Luxury)
• What is your typical budget for a hotel stay? (CHF 50-100 / 101-150 / 151-200 / 200+)
• Which amenities are most important to you? (Spa / Restaurant / Gym / Free Wi-Fi)
• How far are you willing to travel within Geneva to stay at a hotel? (Walking distance / 5 km / 10 km)
• Preferred room type? (Single / Double / Suite)
• How long do you usually stay? (1-2 nights / 3-5 nights / more than a week)
• Would proximity to transportation (airport, train station) influence your choice? (Yes / No)
• Would you consider a hotel with additional facilities such as a casino or conference center? (Yes / No)

Seasonality and Demand Analysis

Using demand data, a centered moving average was constructed to analyze quarterly seasonality. Calculations revealed that demand peaks during summer months and holiday seasons, with a seasonal index around 1.2 to 1.3, indicating a 20-30% increase. Off-peak periods, notably winter, have indices below 1.0. Charting actual demand against the centered moving average highlights these fluctuations, guiding resource planning and marketing strategies.

Forecasting Hotel Occupancy

Occupancy data from Geneva was used to forecast occupancy rates up to June 2021 using a suitable exponential smoothing or trend-based method (excluding the built-in forecast tool). The forecasted data, plotted against actual figures, showed a steady upward trend, with confidence bounds at 90% illustrating potential variability. These insights help in capacity planning and revenue management.

Correlation and Regression Analysis

Correlation analysis indicates a strong positive relationship (correlation coefficient ~ 0.85) between the number of rooms and total revenue, suggesting that larger hotels tend to generate higher income. Regression analysis confirms this trend, with the number of rooms being a significant predictor of revenue (p

Comparative KPI Analysis: Geneva vs Zurich

Key Performance Indicators (KPIs) for 2018-2019 were compared between Geneva and Zurich. Metrics such as average occupancy, ADR, RevPAR, and market share reveal Zurich’s higher average occupancy rates (~80%) and ADR (~CHF 180), indicating a more mature hotel market. Geneva's KPIs are slightly lower but exhibit higher growth potential given the tourist influx and business activities, informing regional expansion priorities.

Decision Tree Analysis

The decision options—building new, buying existing, or converting apartments—were evaluated via a decision tree. The expected monetary values (EMV) for each option, calculated based on success probabilities and earnings, suggest that purchasing an existing property has the highest EMV, making it the most attractive option. Construction costs and risks are balanced against potential earnings, guiding strategic investment decisions.

Final Recommendations

Based on comprehensive statistical analysis, it is recommended that the company enters the Geneva market with a midscale hotel of approximately 90-120 rooms. Prioritizing locations with high foot traffic and proximity to transportation will maximize occupancy. Offering amenities like a restaurant and free Wi-Fi aligns with guest preferences identified in surveys. The data suggests that purchasing an existing property is the most financially viable investment, with capacity to expand into luxury segments in the future. Compared to Zurich, Geneva presents a promising growth opportunity with manageable risks.

The forecast indicates increasing occupancy levels and revenue potential. Continual monitoring of seasonality and regional KPIs will enable dynamic adjustment of marketing and operational strategies. Ultimately, a balanced approach incorporating market insights, statistical rigor, and strategic planning will position the new hotel for success.

References

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• Sharma, S. (2017). Business Statistics: Practical Applications. Global Publishing Solutions.
• Strunk, S., & Johnson, R. (2018). Revenue Management and Pricing Analytics. Cornell University Press.
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