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Difference Between Robotic Systems and Static Shelves Essay

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Difference between robotic systems and static shelves

The robotic systems are more productive than the static shelves. One of the most

significant differences between these two systems is portability. Static shelves are not built

for mobility, unlike the robot system. When using the robotic system, the products are

delivered to the post of the employees faster than in a static shelving system. This makes the

robotic system more effective as it saves time, and the production rate is increased.

Furthermore, It is reported that the robotic system's efficiency is twice that of the static

shelves. The working environment is much conducive to using robotic systems since there is

no noise compared to the static systems.

Additionally, robotic systems are less tiresome to the employees since they move

around unlike in the case of static shelves where employees have to carry products to their

work station. The robotic system can easily be adapted to meet the user's needs. Static

shelves do not utilize space to their optimum capacity, like the robotic system. The service

delivery to the customers is at a higher speed and with minimum expenses compared to the

traditional static shelves. Also, energy saving with the robotic system is easier.

A robotic system has higher economic benefits compared to the static shelves. When

using the robotic system, a company can use a workforce that is half of the one using the

static shelves. This reduces the production cost of the shoes in the company. Robotic systems

are safer and the security of the products compared to static shelves where a company may

experience accidents every week. Moreover, it increases the productivity of the worker by

double compared to the static system. Inventory accuracy is significantly higher at almost

100%, while the defect rate is nearly 0%. Generally, the robotic systems are more efficient

and effective than the static shelve and friendly to the users.

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SNHU Week 8 Technology Financial & Energy Sectors ETFs Discussion

8-2 Jupyter Notebook (Discussion Prep)External Learning ToolThis activity will take you to the Jupyter Notebook contain ...

SNHU Week 8 Technology Financial & Energy Sectors ETFs Discussion

8-2 Jupyter Notebook (Discussion Prep)External Learning ToolThis activity will take you to the Jupyter Notebook containing the Python scripts for your Module Eight discussion. It is highly recommended that you read through the discussion prompt before completing your work in this notebook. When you are finished completing and running the Python scripts, begin work on your initial discussion post.Note: This task is not graded, but you will be required to attach your completed Jupyter notebook to your discussion post in the next activity. 8-3 Discussion: One-Way ANOVADiscussion Topic Starts Jun 12, 2021 8:59 PMUse the link in the Jupyter Notebook activity to access your Python script. Once you have made your calculations, complete this discussion. The script will output answers to the questions given below. You must attach your Python script output as an HTML file and respond to the questions below.In this discussion, you will apply the statistical concepts and techniques covered in this week's reading about one-way analysis of variance (ANOVA). An investment analyst is evaluating the 10-year mean return on investment for industry-specific exchange-traded funds (ETFs) for three sectors: financial, energy, and technology. The analyst obtains a random sample of 30 ETFs for each sector and calculates the 10-year return of each ETF. The analyst has provided you with this data set. Run Step 1 in the Python script to upload the data file.Using the sample data, perform one-way analysis of variance (ANOVA). Evaluate whether the average return of at least one of the industry-specific ETFs is significantly different. Use a 5% level of significance.In your initial post, address the following items: Define the null and alternative hypothesis in mathematical terms and in words. Report the level of significance. Include the t3st statistic and the P-value. See Step 2 in the Python script. Provide your conclusion and interpretation of the t3st. Should the null hypothesis be rejected? Why or why not? Does a side-by-side boxplot of the 10-year returns of ETFs from the three sectors confirm your conclusion of the hypothesis test? Why or why not? See Step 3 in the Python script. In your follow-up posts to other students, review your peers' results and provide some analysis and interpretation: What does a post-hoc t3st (like Tukey's HSD t3st) contribute after one-way ANOVA is performed? Comment on your peers' results and compare them with your own. Remember to attach your Python output and respond to all questions in your initial and follow-up posts. Be sure to clearly communicate your ideas using appropriate terminology. Reply to Student John Latulippe posted Jun 21, 2021 3:57 PM Subscribe Ho: u1 = u2 = … = uk Ha: ui ? uj, for some i ? j Level of significance = 0.05 or 5% Test statistic, F = 55.07 P-value = 0.0 Yes. The null hypothesis, Ho should be rejected since the p-value of 0.0 is less than the significant level of 0.05 sufficient evidence exists to reject the null hypothesis, Ho for the alternative hypothesis, Ha. 5. Yes. The one-way ANOVA compares the means of three or more groups of one predictor variable. There are at least two groups with unequal means. If you examine the box plot you can see that the energy ETF and technology ETF mean are unequal to the financial ETF mean. Both ETF's have a higher mean than the financial ETF.

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4 pages

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