Data analysis Project

Select one dataset from the datasets provided in the bellow link.

For 28 Data Analysis Projects to Boost Your Skills [2023 Guide]:

https://www.springboard.com/blog/data-analytics/data-analysis-projects/

For more free public datasets for EDA:

https://www.tableau.com/learn/articles/free-public-data-sets

• After the dataset is selected (or assigned), analyze the data using Microsoft Excel to discover the structure of data, trends, patterns, or any anomalies in the data based on your own hypothesis.
• Perform the following six tasks.
• You should use visualization to aid your answers.

Your project will include two main parts:

• The final project report must incorporate all the following 6 tasks and be written using the provided template.
• A presentation that illustrates your 6 tasks completed in the project.

==========================================================

Task 1: Understand and describe the nature and structure of the selected dataset. (2 marks)

• Describe the dataset. Your description should answer the following questions: is it reliable? how was it collected? What its size?
• Identify the features of dataset.
• Propose hypothesis / assumptions (between 2 numerical variables) to validate.

Task 2: Check if your selected features have any of the following issues. Describe how you conducted the tests and how you addressed the issues. Support your answers with screenshots of the issues before and after the fixes.

• Missing values (fix and screenshot)
• Duplicate values
• Data outliers
• Any noise or irregularities

Task 3: Provide descriptive statistics for the selected features using statistical method to understand the dataset more and answer the following analysis questions:

• Include any of the measures of central tendency such as the mean, median, and mode.
• Describe the spread of your data. This may include the measure of variance, standard deviation, skewness, and kurtosis.

(You are encouraged to impose other analysis questions based on any trend you notice in the dataset).

Task 4: Validate the hypothesis in Task 1 by investigating the relationship between two quantitative variables you have chosen using correlation, regression and R-squared with possible conclusions.

Task 5: Show a visual representation of your analysis (hint: use the right chart/graph for your data analysis).

Task 6: Build an active Dashboard that summarizes the most crucial factors (variables) that will help in the decision-making process, and then demonstrate the effectiveness of your selection of those factors in the decision-making process.