Fullfillment

Published: 17 November 2023| Version 1 | DOI: 10.17632/6gjfzhnnkg.1
Contributor:
Sunil Maria Benedict

Description

This is the dataset that was prepared for the study of integration of mathematical models with the study of human behaviour. This serves as a powerful tool in deciphering complex systems and unraveling patterns that might otherwise remain obscured. These models offer structured frameworks, facilitate predictive analysis, and encourage interdisciplinary collaboration. However, their effectiveness is enhanced when coupled with qualitative insights and an appreciation of the inherent complexity of human behaviour. Therefore, while mathematical models provide invaluable insights, they are most potent when complemented by a nuanced understanding of the multifaceted nature of human actions and interactions.

Files

Steps to reproduce

import pandas as pd # Generate the time values t_values = np.linspace(0, 10, 100) # Calculate the integral of F'(t) integral_values = integral_F_prime(t_values) # Calculate F(t) using the formula F_values = np.exp(integral_values) # Create a DataFrame data = {'Time': t_values, 'Fulfillment/Satisfaction': F_values} df = pd.DataFrame(data) # Export DataFrame to an Excel file df.to_excel('fulfillment_data.xlsx', index=False)

Institutions

CMR Group of institutions

Categories

Psychology, Mathematics, Calculus

Licence