Reference no: EM132565123

BUSS B 2012 Research Methods, Data Analytics and Project Planning - Middle East College

Learning Outcome 1. Design a project plan for business improvement.

Learning Outcome 2. Execute reliable research on business processes and other phenomenon.

Learning Outcome 3. Distinguish the different distributions in statistics.

Learning Outcome 4. Present research findings and opportunities for improvement.

Learning Outcome 5. Be able to summarize, explain and apply basic principles of good project management.

Assignment Objective

After finishing this assignment, student should be able to present research findings and opportunities for improvement. Further students also should be able to summarize, explain and apply basic principles of good project management.

Assignment Tasks

This assignment is an individual assignment.

The assignment has 4 different parts and each part should be answered.
• Part 1: Literature Review / Report Structure
• Part 2: Descriptive Statistics and Data Analysis
• Part 3: Order Profile and Walking Distances in a Warehouse Project
• Part 4: Correlation, Regressions and Probability Distributions
In the report it is important to show both the results and the way the results were achieved, just a couple of answers will not suffice. Where possible results should be supported by graphs.

Please do not print out entire Excel files as an appendix. All graphs and tables should have a correct and appropriate layout.
The report must have the following structure
• Introduction about the module. Application of module learning outcome in industries.
• Categories of Research / Research Methodology.
• One each literature review on the following five topics
a. Qualitative Research or Quantitative Research
b. Excel Data Analysis
c. Project Management / Project Planning
d. Logistics and Supply Chain
e. Warehousing or Transportation
• Summarizing MOOC Lecture.
• Descriptive Statistics and Data Analysis
• Order Profiles and Walking Distances in a Warehouse
• Correlations, Regressions and Probability Distributions
• Conclusion
• References

Learning goals:

Part 1:
Goal of this assignment is to learn explore the research with the help of various literatures, research structure.

Part 2:
Goal of this assignment is to learn to deal with the cleaning of data sets based on the correct criteria and to analyse these data sets using tables, standards, and visualizations.

Part 3:
This question is meant to apply knowledge achieved during the statistics lectures to a number of daily logistical problems.

Part 4:
The goal of this assignment is to apply statistical knowledge, acquired during the Statistics course, to problems faced during daily logistics operations.

Part 1: Literature Review / Report Structure
Create a report with the following information. Introduction about the module. Application of module learning outcome in industries.

• Introduction about the module. Application of module learning outcome in industries.
• Categories of Research / Research Methodology.
• Literature Review
• Summarizing MOOC Lecture

• Conclusion, References.

Apart from the above information, the report also must include the answers of Part 2, Part3 and Part 4 of the assignments.

Part 2: Descriptive Statistics and Data Analysis
Note : Use the "Data Analysis" Worksheets for solving Part 2.

a) Clean the data using the below steps:

• Check the data set for contamination.
• Filter any bad data from the data set.
• Show what data have been filtered based on what criteria and state which percentage has been filtered out.

For the rest of the assignment work with the cleaned data set (unless stated differently).

b) Make a frequency table of the brand showing:
• Frequency
• Relative frequency
• Cumulative frequency
• Cumulative relative frequency

c) Make a bar chart for the absolute frequency of the brand.

d) Make a histogram of the number of weight per article and no. of replenishment lines per day.

e) Determine mode, median, and average of the number of sold pieces present year.

f) Check is there any significant difference between no of pieces sold present year and No of pieces sold previous year. Assume Unequal variances. Find out which year sale performance is better.

Part 3: Order profiles and walking distances in a warehouse

The company wants to increase the efficiency of their warehouse. The warehouse manager is considering relocating stock in the warehouse. The following groups are given:

a) Make a graph showing the ABC-analysis (see book: "Introduction into Logistics") for the articles of the selected logistic company. In the graph the y-axis shows the cumulative percentage of orderliness and the x-axis shows the cumulative percentage of SKUs.

b) Per group (AA, A, B, C) determine the number and percentage of SKUs, the number, and percentage of order lines and the number and percentage of used storage locations. Show this in a table.

c) What is the average number of order lines per order?

On the next page two lay-outs are shown. These lay-outs are also given in the data file. To simplify the problem all stock is placed on ground level locations. A pallet location has a width of 0.9m and a depth of 1.2m. Between two pallet locations there is a space of 0.2m. The lines given in the lay-outs to separate the areas (e.g. AA and A) are indicative.

d) Based on the number of used locations per group (AA, A, B, and C) determine the exact allocation of groups within the two warehouse lay-outs.

Answer the following questions for both warehouse lay-outs:

e) What is the expected walking distance for an AA, A, B, and C article for both lay-outs?

a) Based on the calculations, which warehouse design would you choose?. And why ?

Part 4: Correlation, Regression and Probability Distributions.

Note : Use the "Emergency Orders" Worksheets for solving Part 4.

Using the emergency order data provided, discuss the following with necessary tables, graphs and trend lines.

a) Draw the relationship (Correlation) between each variable (Order Picking, Packaging and Shipping) with separate tables and scatterplots. Discuss each result.

b) Generate 3 valid Regression Equation for predicting any Emergency Order Variables. Discuss the result with line fit plots, normal probability plot and key outcomes.

c) Predict any 6 set of data using the generated regression equations.

d) Apply paired sample t-test for the relevant data and discuss the result.

Attachment:- Data Analytics and Project Planning.rar