Week 6

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Arizona State University *

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Jun 10, 2024

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Week 6 Hunter O’Brien Question 1: I currently work as a manager at Chick Fil A and for my linear regression example I would analyze factors that influence daily sales performance. The dependent variable in this scenario would be the total daily sales revenue, which is continuous in nature as it involves monetary values. My three dependent variables: 1. Weather Conditions (Nominal/Categorical) : Weather conditions can significantly impact customer traffic and purchasing behavior. You can categorize weather conditions into different types such as sunny, rainy, cloudy, or snowy. This variable is nominal as it represents distinct categories without any inherent order. 2. Promotional Offers (Nominal/Categorical) : Promotional offers, such as discounts or special menu items, can influence customer spending patterns. You can categorize promotional offers as either present or absent on a given day. Again, this variable is nominal as it indicates different categories without any inherent order. 3. Time of Day (Ordinal) : The time of day can affect customer traffic and preferences. You can categorize time of day into ordinal categories such as morning, afternoon, and evening, or further divide it into specific time intervals. This variable is ordinal as there is a natural order to the categories, with morning preceding afternoon and evening. Which variable might have the greatest impact?

Week 6 Hunter O’Brien Weather conditions could have a significant impact on Chick-fil-A's daily sales. For instance, on rainy days, customers might be less inclined to visit the restaurant, leading to lower sales. Conversely, sunny weather might attract more customers, resulting in higher sales. However, while weather can influence sales, it might not be directly controllable by the restaurant management. Promotional offers could also have a substantial impact on sales. A well- designed promotion can attract more customers and increase spending per transaction. However, the effectiveness of promotional offers may vary depending on factors such as the type of promotion, the target audience, and the timing of the promotion. Time of day is another crucial factor. Chick-fil-A may experience higher sales during peak mealtimes, such as breakfast, lunch, and dinner. Although, this variable's impact may be more predictable and controllable compared to external factors like weather. In conclusion, while all three variables are important, the impact of weather conditions on daily sales at Chick-fil-A might be the most significant due to its potential to directly affect customer traffic. While the effectiveness of promotional offers and the timing of sales throughout the day should not be overlooked, as they also play vital roles in driving sales performance.

Week 6 Hunter O’Brien Question 2: As a Chick Fil A manager, I feel predicting customer satisfaction would be important to employ binary logistic regression. In this case, the binary dependent variable for logistic regression could be whether a customer is satisfied or dissatisfied with their dining experience. My three independent variables: 1. Food Quality Rating (Ordinal): Food quality is a crucial aspect of the dining experience. You can measure food quality using an ordinal scale, where customers rate the quality of their food on a scale (e.g., 1 to 5 stars). This variable is ordinal as there is a natural order to the ratings, with higher ratings indicating better food quality. 2. Speed of Service (Continuous): The speed of service refers to the time it takes for customers to receive their orders. You can measure this variable in minutes or seconds, making it continuous. Faster service times may lead to higher customer satisfaction scores. 3. Friendliness of Staff (Ordinal): The friendliness of staff members can significantly impact customer perceptions. You can measure this variable using an ordinal scale, where customers rate the friendliness of staff on a scale (e.g., 1 to 5 stars). This variable is ordinal as there is a natural order to the ratings, with higher ratings indicating friendlier staff.

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