Data · dataset · 2024
Exploring Saint Thomas Aquinas' Insights on Women's Social Support
Listed in Teesside University Research Data Repository
This Python code generates simulated data to explore the relationship between emotional intelligence, resilience, and the perceived "Glory in Living." Here's a detailed description of the code: Simulated Data Generation: The code starts by setting a random seed for reproducibility.
Description
It generates a time series with 100 time points ranging from 0 to 1. Components of emotional intelligence (sensitivity, understanding, effectiveness) are simulated with random values.
Emotional intelligence is then calculated as a weighted sum of these components. Simulating Falls and Total Opportunities: The code simulates the occurrence of falls and total opportunities with random integers. Resilience is calculated as the complement of falls divided by total opportunities.
Read the rest (3 more)
Calculating Glory in Living: Glory in living is calculated as the product of emotional intelligence and resilience. Creating a DataFrame: A pandas DataFrame is created to organize and analyze the generated data, including time, emotional intelligence, resilience, and glory in living. Visualizing the Data: The seaborn pair plot is used to visualize relationships between different variables, providing a quick overview of correlations and distributions.
Statistical Analysis: The code calculates the correlation matrix to quantify linear relationships between variables. Linear regression is performed to predict glory in living based on emotional intelligence and resilience. The R-squared value is printed, indicating the proportion of variance in glory in living explained by the linear regression model.
Output: The correlation matrix and the R-squared value are printed to provide insights into the strength and direction of relationships between variables.
Links
Where it is published
- DOI doi.org/10.17632/fyycjkbyw3.1 ↗
DOI / persistent id · from researchdata tees ac uk
Catalogue records · 1
- OAI-PMH record data.mendeley.com/oai?verb=GetRecord&metadataPrefix=oai_dc&identifier=oai%3Adata… ↗
metadata API · from researchdata tees ac uk
Topics
- From keywords
- Earth & Environmental Science · Engineering · Humanities · Life Sciences · Social Science
- Inferred from text
- Specialist studies in education 70%
Provenance · 1 source records, 11 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| Teesside University Research Data Repository | oai:data.mendeley.com/fyycjkbyw3.1 | 10 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| access_level | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].anzsrc:group:3904 | enrichment · researchdata tees ac uk | taxonomy-embedding@1.0.0 | title+keywords+description (70%) |
| concepts[field].local:field:earth-environmental | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:engineering | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:humanities | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:life-sciences | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:social-science | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| description | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | /metadata/dc/description |
| license | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | /metadata/dc/rights |
| publication_date | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| title | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | /metadata/dc/title |