https://github.com/compcode1/slq-exercise-dataset-analysis

The initial SLQ analysis findings indicate that this dataset is unreliable and unworthy of further analysis.
https://github.com/compcode1/slq-exercise-dataset-analysis

Last synced: 10 months ago
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The initial SLQ analysis findings indicate that this dataset is unreliable and unworthy of further analysis.

• Host: GitHub
• URL: https://github.com/compcode1/slq-exercise-dataset-analysis
• Owner: Compcode1
• License: gpl-3.0
• Created: 2024-08-02T11:25:54.000Z (over 1 year ago)
• Default Branch: main
• Last Pushed: 2024-08-02T11:36:14.000Z (over 1 year ago)
• Last Synced: 2024-08-02T13:02:32.821Z (over 1 year ago)
• Language: Jupyter Notebook
• Size: 153 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

          
# slq-exercise-dataset-analysis

### **Introduction**

In this small project, we aim to explore and analyze a dataset 'Exercise and Fitness Metrics Dataset' ( https://www.kaggle.com/datasets/aakashjoshi123/exercise-and-fitness-metrics-dataset/data?select=exercise_dataset.csv) containing various metrics related to exercise, including exercise type, heart rate, age, and exercise intensity. The primary goal is to uncover relationships between these variables to better understand the data and its potential utility.  By employing SQL queries within a Jupyter Notebook environment, we load the dataset, perform data analysis, and investigate the integrity and validity of the dataset. Specifically, we focus on evaluating average exercise intensity per exercise category, average heart rate per exercise category and the relationship between age and heart rate during exercise. 

Upon analysis, several key findings quickly revealed a dataset of little utility. The analysis of average exercise intensity across different exercise categories showed very minimal variance which is highly unusual.  Ten diffrent exercises should elicit a much greater variance as is consistent in the established science. The evaluation of average heart rate per exercise category also displayed very little variance again in a very unusual fashion as compared to well esatablished expectations.  Finally, the examination of the relationship between age and heart rate revealed no significant decrease in heart rate as a function of age, contradicting the well-established physiological expectation that heart rate typically decreases with age during exercise. This is a well established study expectation. These combined findings indicate that this dataset is unreliable and unworthy of time investment for further analysis.