Las Vegas has seen increased competition from Singapore and Macau for customers in the casino resort industry. One measurement of success is the average length of stay by visitors. The data in this file show the number of days a random sample of visitors stayed at each location. a. Using α = 0.05 to determine if there is a difference in the average length of stay by visitors for the three locations. Follow the steps as outlined in the exercises. b. If warranted, perform a multiple comparison test to determine which pairs are different using α = 0.05. c. Verify your results using Excel. The table displayed provides data comparing three locations: Singapore, Macau, and Las Vegas. The structure of the table includes three columns, each representing one of the specified locations. The rows beneath these headings contain numerical values as follows:- **Singapore:** 7, 4, 4, 3, 7- **Macau:** 2, 4, 3, 1, 1- **Las Vegas:** 3, 6, 3, 4, 5Each row compares corresponding numerical values across the three locations. This table might represent quantitative data such as ratings, scores, or other metrics relevant to the context of the educational content in which it is presented.

Name: Las Vegas has seen increased competition from Singapore and Macau for
Uploaded: 2024-03-20T07:06:16.000Z
Channel: Bartleby
Description: Las Vegas has seen increased competition from Singapore and Macau for customers in the casino resort industry. One measurement of success is the average length of stay by visitors. The data in this file show the number of days a random sample of vi

Given Information : Las Vegas has seen increased competition from Singapore and Macau for customers in the casino resort industry. One measurement of success is the average length of stay by visitors. The data in this file show the number of days a random sample of visitors stayed at each location . We can use a statistical technique which can compare these three treatment samples and depict how different these samples are from one another. Such a technique, which compares the samples on the basis of their means, is called ANOVA. Analysis of variance (ANOVA) is a statistical technique that is used to check if the means of two or more groups are significantly different from each other. ANOVA checks the impact of one or more factors by comparing the means of different samples. Steps to perform One - way ANOVA : Step 1: Input your data into columns or rows in Excel. For example, if three groups of students for music treatment are being tested, spread the data into three columns. Step 2: Click the “Data” tab and then click “Data Analysis.” If you don’t see Data Analysis, load the ‘Data Analysis Toolpak’ add-in. Step 3: Click “ANOVA Single Factor” and then click “OK.” Step 4: Type an input range into the Input Range box. For example, if the data is in cells A1 to C10, type “A1:C10” into the box. Check the “Labels in first row” if we have column headers, and select the Rows radio button if the data is in rows. Step 5: Select an output range. Step 6: Choose an alpha level. For most hypothesis tests, 0.05 is standard. Step 7: Click “OK.” The results from ANOVA will appear in the worksheet. Output : Interpretation : Here, we can see that the F-value is greater than the F-critical value for the alpha level selected (0.05). Therefore, we have evidence to reject the null hypothesis and say that at least one of the three samples have significantly different means and thus belong to an entirely different population. P-value approach : If the p-value is less than the alpha level selected (which it is, in our case), we reject the Null Hypothesis.Post - hoc Test : Now to check which samples had different means we will take the Bonferroni approach and perform the post hoc test in Excel. Step 8: Again, click on “Data Analysis” in the “Data” tab and select “t-Test: Two-Sample Assuming Equal Variances” and click “OK.” Step 9: Input the range of Singapore column in Variable 1 Range box, and range of Macau column in Variable 2 Range box. Check the “Labels” if you have column headers in the first row. Step 10: Select an output range. Step 11: Perform the same steps (Step 8 to step 10) for Columns of Macau – Las Vegas and Singapore – Las Vegas. Output : Result : Here, we can see that the p-value of (Singapore vs Macau) and (Singapore vs Las Vegas) is less than the alpha level selected (alpha = 0.05). This means that groups Singapore and Macau & groups Singapore and Las Vegas have less than 5% chance of belonging to the same population. Whereas for (Macau vs Las Vegas) it is much greater than the significance level. This means that Macau and Las Vegas belong to the same population. So, it is clear that Singapore belongs to an entirely different population. Or we can say that the Singapore had a significant effect on the measurement of success i.e. is the average length of stay by visitors.