Question

We counted the number of people who entered our store across the span of a week in the morning, afternoon, and evening. What is the simplest test to see if there is any difference in the frequency of people coming to our store at different times across days?

Answer 1

To check if more people come to the store at different times, use a Chi-square test for independence. First, arrange the counts in a contingency table, then apply the test to find significant differences in frequencies.

Step-by-step explanation:

To determine if there is a difference in the frequency of customers coming to the store at different times of the day, the simplest test would be a Chi-square test for independence. This test assesses whether observations across different categories (morning, afternoon, evening) are distributed differently from what would be expected under the null hypothesis, which is typically the assumption of no association between the categories and days. You will first need to organize the count data into a contingency table with days as rows and time sessions as columns. Then, you can apply the Chi-square test to check for significant differences in the frequencies.

For your two related questions - on average, how many minutes elapse between two successive arrivals, and the average time for three customers to arrive when the store first opens - other statistical measures and tests may be more appropriate. For instance, calculating the mean inter-arrival time would address the first query, and for the second, you would be looking at the cumulative arrival distribution.

Answer 2

Answer and explanation:

The simplest form to identify a difference in the frequency of the customers who visited the sore is by recording the number of people coming into the shop is well established time frames during the morning, afternoon, and night. After performing the report for at least a couple of weeks, a comparison should be made among the opening days and time frames during a day to find out what days are the heaviest in clientele and during what time.