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## reasearch

In this report paper, you will explore in detail one of the statistical learning techniques or data mining (if you have the background) approaches to research discussed in the course, applying it in the context of a specific application or methodological study. This will help you gain a deeper understanding of your chosen topic as well as gain experience in translating these ideas into practice.

Find a data set, generate your topic based on the type of dataset and what questions you want to answer from the dataset. The following task need to be performed:

• Data Selection.
• Data Exploration and visualization
• Data Analysis (Explain the Statistical methods) (MS Excel)
• Discussion and Summarization of the work and results

Your report is base on the hands-on project.

Data Selection:(Select anyone)

https://www.kaggle.com/vjchoudhary7/customer-segmentation-tutorial-in-python/kernels?sortBy=hotness&group=everyone&pageSize=20&datasetId=42674&language=R

Example:

Topic: The impact on student learning in small class sizes in the United States

Dataset: dataset_Star.csv

Resource File: R_The impact on student learning and small class sizes in the United States.pdf

**Must be APA formatted**

•Title Page •Document body with citations •Reference Page

Section 1: Discuss Topic Background (Citations are required)

Section 2: Data Analysis

•Describe the fields of the dataset. •Create a summary of stats for the dataset. •Discuss the Min, Max, Median, and Mean of the continuous fields. •Discuss the Counts and Percentages of the categorical fields. (ex. Pie Chart) •Discuss any missing data elements.

Section 3: Data Visualizations (SPSS, MS Excel, R Studio – R language – Library: ggplot2)

•Graphs: Bar Plot, Box Plot, Scatter Plot, and Histogram •Label: X-Axis, Y-Axis, and Titles •Discuss: Plot, Breakout, Drilldown, and Position (only Bar Plot) •Findings: What story is presented in the visualizations?

Section 4: Discuss Findings

•Compare (Similar) •Contrast (Difference) •Conclusion of the findings

Section 5: Reference List

•At least 2 References