# Emotional State analysis with Yoga Practice

Published: 26 February 2024| Version 1 | DOI: 10.17632/vygp3d5xv9.1
Contributor:
Sunil Maria Benedict

## Description

Statistical analysis for the visual representation involves examining the trends and relationships within the data. Here, we're dealing with a conceptual model rather than real-world data, so the analysis is more qualitative. However, we can perform some basic analysis and provide interpretations: 1. Decay Constant (k): • The decay constant affects the rate at which emotional state decreases over time. Higher values of k will result in faster emotional decay. 2. Yoga Effect (alpha): • The yoga effect is a linear term that represents the positive impact of yoga practice on emotional well-being. A higher alpha implies a more significant positive effect of yoga. 3. Time (independent variable): • Time is the independent variable representing the duration of the emotional evolution. 4. Emotional Evolution (dependent variable): • Emotional Evolution is the dependent variable representing the emotional state over time. Analysis: • The plot shows an initial exponential decay in emotional state, representing a natural decline over time. • The positive linear term (alpha * yoga_effect * time) introduces a positive impact of yoga. As time progresses, the effect of yoga becomes more prominent, contributing to an increase in emotional well-being. • Key points (Start Yoga, Determination, Equanimity) are highlighted, emphasizing the potential positive milestones in the emotional well-being journey through yoga practice. Interpretation: • The model suggests that the emotional state naturally declines over time, but this decline is mitigated and even reversed by the positive impact of yoga. • The effectiveness of yoga is demonstrated by the increasing emotional state as time elapses, especially during key periods like the initiation of yoga practice, determination to continue, and achieving equanimity.

## Steps to reproduce

import numpy as np import matplotlib.pyplot as plt # Parameters k = 0.1 # decay constant alpha = 0.33 # coefficient for yoga effect time = np.linspace(0, 10, 100) # time points # Emotional evolution model (exponential decay with yoga effect) emotional_state = 1.0 # initial emotional state yoga_effect = 1 # binary variable (0 or 1) for yoga practice emotional_evolution = emotional_state * np.exp(-k * time) + alpha * yoga_effect * time # Plot emotional evolution over time plt.plot(time, emotional_evolution, label='Emotional State') plt.axhline(0, color='black', linestyle='--', label='Zero Emotional State') # Highlight key points plt.scatter([2, 5, 8], [emotional_state, 0.5 * emotional_state, 0], color='red', zorder=5) plt.text(2, emotional_state, 'Start Yoga', fontsize=10, color='red', verticalalignment='bottom') plt.text(5, 0.5 * emotional_state, 'Determination', fontsize=10, color='red', verticalalignment='bottom') plt.text(8, 0, 'Equanimity', fontsize=10, color='red', verticalalignment='bottom') # Labeling and legend plt.title('Emotional Evolution with Yoga Practice') plt.xlabel('Time') plt.ylabel('Emotional State') plt.legend() plt.grid(True) # Show the plot plt.show()

## Institutions

CMR Group of institutions

## Categories

Well-Being, Yoga, Emotional Development, Employee Well-Being, Emotional Detachment