In the small town of Middleton, there are only two restaurants that serve pizza- a small family-owned Italian restaurant and a new franchise pizza restaurant. In a recent review of the franchise, a food critic reported that the pizza was delicious as promised. The only negative review that the franchise received from the critic was about the inaccurate delivery time quoted during the order process. In response to the article, the franchise owner used a program to analyze the online pizza orders that took place during the week before the review. He chose to track the orders at 6 pm each day. He recorded his results in the frequency table below.
Monday Tuesday Wednesday Thursday Friday
On-Time ||| ||
Late | ||| ||||
In two or more complete sentences, explain whether or not the franchise owner is collecting data that will be representative of the critic’s online pizza order.
Rewrite the scenario above, with provisions to improve the outcome of the owner’s collected data. Do not alter the actual data in the frequency table.
Analyze the new scenario, including your provisions for improvement. Do your provisions give the owner’s data the maximum possible validity? Use complete sentences to explain your answer.
Based on the scenario and the data provided in the frequency table, what conclusion can you make concerning the late deliveries and the promises made by the online ordering system? Use complete sentences to explain your answer.
In the given scenario, the franchise owner is collecting data that may not be fully representative of the critic's online pizza order. This is because the owner is only tracking the orders at 6 pm each day, which may not capture the full range of delivery times throughout the day. It is possible that delivery times could vary at other times of the day, and by only focusing on a specific time, the owner may not be capturing an accurate representation of the critic's experience.
To improve the outcome of the owner's collected data, a provision could be made to track orders at different times throughout the day, rather than just at 6 pm. This would provide a more comprehensive view of the delivery times and would increase the likelihood of capturing data that is representative of the critic's online pizza order. Additionally, the owner could also track the delivery times over a longer period of time to account for any variations in delivery performance.
With the provisions for improvement stated above, the owner's data would have a higher level of validity. By tracking orders at different times throughout the day and over a longer period of time, the owner would have a better understanding of the delivery performance and would be able to make conclusions based on a more representative sample of data.
Based on the given scenario and the data provided in the frequency table, we can conclude that there have been instances of late deliveries according to the critic's review. The critic mentioned inaccurate delivery time quotes during the order process, and the frequency table shows that there were some orders that were categorized as "late" on Tuesday and Friday. However, without additional information or a larger sample of data, we cannot determine the extent or severity of the late deliveries or whether they are consistent issues.
The franchise owner is collecting data that may not be representative of the critic's online pizza order. This is because the owner is only tracking orders at 6 pm each day, which may not reflect the overall experience of the customers throughout the day. It is possible that there are different patterns of deliveries and accuracy of the online ordering system at different times of the day.
To improve the outcome of the owner's collected data, provisions can be made to track the orders at various times throughout the day. This will provide a more comprehensive view of the accuracy of the delivery time quoted during the order process. Additionally, the owner can also consider tracking data for multiple weeks rather than just one week to take into account any weekly variations in the delivery process.
These provisions will improve the validity of the owner's data by capturing a broader range of customer experiences and accounting for any fluctuations or inconsistencies that may occur at different times or over different weeks.
Based on the provided scenario and frequency table, the conclusion that can be made is that there were more instances of late deliveries (7) compared to on-time deliveries (3) during the week before the review. This suggests that the online ordering system may have been inaccurate in quoting the delivery time, as highlighted by the critic's negative review. However, it is important to note that this conclusion is based on a limited timeframe and specific time of tracking, so it may not fully represent the overall performance of the franchise's delivery system.