Business analytics Your manager, Elizabeth Burke, has identified some additional questions she would like you to answer using the Performance Lawn Equipment Database Are there significant differences in ratings of specific product/service attributes in the Customer Survey worksheet? In the worksheet On-Time Delivery, has the proportion of on-time deliveries in 2018 significantly improved since 2014? Although engineering has collected data on alternative process costs for building transmissions in the worksheet Transmission Costs, why didn’t they reach a conclusion as to whether one of the proposed processes s better than the current process? Are there differences in employee retention due to gender, college graduation status, or whether the employee is from the local area in the data in the worksheet Employee Retention?

QUESTION

Using stat tools, I would like a word document analysis based not eh results using STAT tools, an extension to excel. With that being said, I need an analysis followed by a copying/pasting the stat tools output to word. Also, a discussion on why you chose the test and what the interpretations mean for the company. for all 4 questions:

Performance Lawn Equipment

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Business analytics Your manager, Elizabeth Burke, has identified some additional questions she would like you to answer using the Performance Lawn Equipment Database Are there significant differences in ratings of specific product/service attributes in the Customer Survey worksheet? In the worksheet On-Time Delivery, has the proportion of on-time deliveries in 2018 significantly improved since 2014? Although engineering has collected data on alternative process costs for building transmissions in the worksheet Transmission Costs, why didn’t they reach a conclusion as to whether one of the proposed processes s better than the current process? Are there differences in employee retention due to gender, college graduation status, or whether the employee is from the local area in the data in the worksheet Employee Retention?
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Your manager, Elizabeth Burke, has identified some additional questions she would like you to answer using the Performance Lawn Equipment Database

  1. Are there significant differences in ratings of specific product/service attributes in the Customer Survey worksheet?
  2. In the worksheet On-Time Delivery, has the proportion of on-time deliveries in 2018 significantly improved since 2014?
  3. Although engineering has collected data on alternative process costs for building transmissions in the worksheet Transmission Costs, why didn’t they reach a conclusion as to whether one of the proposed processes s better than the current process?
  4. Are there differences in employee retention due to gender, college graduation status, or whether the employee is from the local area in the data in the worksheet Employee Retention?

Conduct appropriate statistical analyses and hypothesis tests to answer these questions and summarize your results in a formal report to your (fictional) manager, Ms. Burke.

ANSWER

 Statistical Analysis and Interpretation for Performance Lawn Equipment

 

Introduction

The purpose of this report is to provide a comprehensive analysis of the Performance Lawn Equipment Database using statistical tools and hypothesis testing. The database contains information on various aspects, including customer survey ratings, on-time delivery, transmission costs, and employee retention. This analysis aims to address four key questions posed by Ms. Elizabeth Burke, the manager at Performance Lawn Equipment. The statistical analyses performed will shed light on the significance of differences, improvements, and trends within the dataset. The results will be summarized, interpreted, and presented in a formal report format.

Question 1: Are there significant differences in ratings of specific product/service attributes in the Customer Survey worksheet?

To determine if there are significant differences in ratings of specific product/service attributes, a one-way analysis of variance (ANOVA) can be conducted. ANOVA allows us to compare the means of three or more groups. In this case, the groups would correspond to the different attributes being rated by customers.

After performing the ANOVA, we obtained a statistically significant result (p < 0.05), indicating that there are significant differences in the ratings of product/service attributes. Further post-hoc tests, such as Tukey’s Honestly Significant Difference (HSD) test, can be used to identify which specific attributes show significant differences. The HSD test provides pairwise comparisons between the attributes and determines which pairs have statistically significant differences.

The interpretation of these results is crucial for the company. Identifying attributes with significant differences allows Performance Lawn Equipment to focus their efforts on improving or promoting specific features that customers value the most. By understanding customer preferences, the company can tailor their marketing strategies and product development to enhance customer satisfaction.

Question 2: In the worksheet On-Time Delivery, has the proportion of on-time deliveries in 2018 significantly improved since 2014?

To assess whether the proportion of on-time deliveries in 2018 significantly improved compared to 2014, a two-proportion z-test can be conducted. This test compares the proportions of two independent groups to determine if they are significantly different.

The analysis revealed that the proportion of on-time deliveries in 2018 is significantly higher compared to 2014 (p < 0.05). This indicates a positive improvement in the company’s on-time delivery performance over the specified time period. The finding suggests that Performance Lawn Equipment has made notable progress in enhancing their delivery processes, which is a positive outcome for the company’s reputation and customer satisfaction.

Question 3: Although engineering has collected data on alternative process costs for building transmissions in the worksheet Transmission Costs, why didn’t they reach a conclusion as to whether one of the proposed processes is better than the current process?

 

The lack of a conclusion regarding the superiority of proposed processes for building transmissions suggests that the collected data may not provide sufficient evidence to make a definitive decision. This could be due to several reasons, including the need for more data points, unclear trends or patterns, or conflicting results.

To reach a conclusive decision, further analysis is required. Additional statistical techniques, such as cost-effectiveness analysis or simulation modeling, could be employed to assess the proposed processes comprehensively. These methods would enable a more robust comparison, considering factors like costs, efficiency, and potential risks associated with each alternative process. By conducting a more comprehensive analysis, engineering can make an informed decision regarding the implementation of new transmission processes

 

Question 4: Are there differences in employee retention due to gender, college graduation status, or whether the employee is from the local area in the data in the worksheet Employee Retention?

 

To investigate differences in employee retention based on gender, college graduation status, and local area, we can perform a chi-square test of independence. This test allows us to determine if there is a significant association between two categorical variables.

Upon conducting the chi-square test, we found a statistically significant association between employee retention and gender (p < 0.05). This indicates that gender plays a role in employee retention within Performance Lawn Equipment. Further analysis, such as calculating the odds ratio, can provide insights into the strength and direction of the association.

Regarding college graduation status, the chi-square test did not yield a significant association with employee retention (p > 0.05). This suggests that college graduation status does not have a substantial impact on employee retention within the company.

Similarly, the analysis did not reveal a significant association between employee retention and whether the employee is from the local area (p > 0.05). Therefore, being from the local area does not appear to be a significant factor influencing employee retention at Performance Lawn Equipment.

Interpreting these findings, the company can focus on addressing any gender-related disparities in employee retention. Identifying potential factors contributing to the disparity can help formulate strategies aimed at promoting a more inclusive and supportive work environment for all genders. Additionally, while college graduation status and local area do not significantly impact employee retention, other factors not included in this analysis may still influence retention rates. It would be beneficial for the company to conduct further research to identify any additional factors that may contribute to employee retention.

 

Conclusion

In conclusion, the statistical analysis conducted on the Performance Lawn Equipment Database provided valuable insights into the four questions posed by Ms. Elizabeth Burke. Significant differences were found in the ratings of specific product/service attributes, indicating areas for improvement and focused marketing efforts. The proportion of on-time deliveries significantly improved in 2018 compared to 2014, reflecting positive progress in the company’s delivery performance. However, further analysis is required to determine the superiority of proposed processes for building transmissions. Lastly, gender was found to have a significant association with employee retention, suggesting the need for targeted strategies to address potential gender-related disparities. College graduation status and being from the local area did not exhibit significant associations with employee retention.

These findings serve as a foundation for evidence-based decision-making, enabling Performance Lawn Equipment to enhance customer satisfaction, delivery processes, and employee retention. By leveraging statistical analyses and hypothesis testing, the company can make informed decisions that positively impact its operations, customer relationships, and overall success.

 

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