nuriancg/project-da-promo-H-module-3-team-1

Repositorio para proyecto modulo-03 (equipo 1)

(English information at the end of this page)

Optimización de Talento de ABC Corporation

La Iniciativa de Optimización de Talento de ABC Corporation tiene como objetivo abordar diferentes aspectos relacionados con los recursos humanos de su empresa. Para ello, han contratado los servicios de nuestra empresa, Data Gadgets.

Data Gadgets es una empresa formada por un grupo de analistas de datos que utilizamos metodología ágil para cumplir eficientemente con los objetivos propuestos en tiempo récord.

Equipo Data Gatgets: 📈🔍

Names	GitHub_link_user_name
Patricia González	https://github.com/Patri-EGG
Paola Sánchez	https://github.com/paolasanchezsolorzano
Fernanda Marti	https://github.com/fernandaMarti
Nuria Cano	https://github.com/nuriancg
Raquel Castellanos	https://github.com/RachelCaste

Descripción del Cliente 👨‍💻

ABC Corporation, fundada en 1980 en California, es una firma de consultoría tecnológica especializada en proporcionar soluciones de inteligencia artificial (IA) y aprendizaje automático a empresas de diversas industrias.

Objetivo: 🎯

Identificar factores clave que influyen en la satisfacción de sus empleados y, en última instancia, en la retención de los mismos. Presentar los resultados del análisis exploratorio de datos, diseñar un experimento A/B para probar hipótesis críticas y analizar los resultados para proporcionar a ABC Corporation información valiosa y veraz.

Documentación Inicial 📌

En esta sección, encontrarás la descripción de cada una de las columnas del documento original.

Diccionario:

Nombre de la columna	Descripción
Age	The employee’s age.
Attrition	Indicates whether the employee has left the company (“No” means they haven’t left, and “Yes” means they have).
BusinessTravel	Describes the frequency of work-related travel for the employee (e.g., “Travel_Rarely” for infrequent travel).
DailyRate	The employee’s daily rate.
Department	The department in which the employee works (e.g., “Research & Development,” “Sales,” etc.).
DistanceFromHome	The distance from the employee’s home to their workplace.
Education	The employee’s education level (usually on a scale from 1 to 5).
EducationField	The field of education or specialization for the employee.
EmployeeCount	A counter (usually set to 1) used for counting employees.
EmployeeNumber	A unique identification number for the employee.
EnvironmentSatisfaction	Employee satisfaction level related to their work environment, ranging from 1 to 4 (with 4 being the highest satisfaction).
Gender	The employee’s gender (where 0 corresponds to “male” and 1 to “female”).
HourlyRate	The employee’s hourly rate.
JobInvolvement	The level of employee involvement in their work.
JobLevel	The employee’s hierarchical level within the company.
JobRole	The employee’s job role or position.
JobSatisfaction	Employee satisfaction level with their job.
MaritalStatus	The employee’s marital status (e.g., “Single,” “Married,” etc.).
MonthlyIncome	The employee’s monthly income.
MonthlyRate	The employee’s monthly rate.
NumCompaniesWorked	The number of companies where the employee has worked.
Over18	Indicates whether the employee is over 18 years old.
OverTime	Indicates whether the employee works overtime (“Yes” or “No”).
PercentSalaryHike	The percentage of salary increase for the employee.
PerformanceRating	Employee performance rating.
RelationshipSatisfaction	Employee satisfaction level in interpersonal relationships.
StandardHours	Standard working hours.
StockOptionLevel	Employee stock option level.
TotalWorkingYears	Total years of work experience for the employee.
TrainingTimesLastYear	Number of times the employee received training last year.
WorkLifeBalance	Balance between work and personal life for the employee.
YearsAtCompany	Number of years the employee has worked at the current company.
YearsInCurrentRole	Number of years the employee has been in their current role.

Fases del Proyecto 🔄

Para completar el desarrollo de este proyecto y garantizar la integridad de los datos proporcionados por el cliente, se llevaron a cabo cinco fases:

• Fase 1: Exploración y Limpieza de Datos
• Fase 2: Transformación de Datos
• Fase 3: Diseño e Implementación de la Base de Datos
• Fase 4: Pruebas A/B
• Fase 5: Creación de ETL (Extracción, Transformación y Carga)
• Fase 6: Generación de Informes

Requisitos para Ejecutar el Proyecto 🐍 y 🐬

Para trabajar o abrir este proyecto, necesitarás tener instaladas versiones de Python y MySQL.

Librerías a Importar: 📚

Librerías para comenzar a trabajar:

1. Manipulación de Datos 🧮 🐼

   • Pandas
   • Numpy

2. Imputación de datos 🕵️‍♂️

   • Scikit-learn -SimpleImputer: Imputa valores faltantes en un conjunto de datos utilizando estrategias simples como la media, la mediana o la moda, entre otras. -IterativeImputer: Utiliza técnicas iterativas, especialmente útiles cuando las relaciones entre variables son complejas. -KNNImputer: Estima valores faltantes utilizando el método de los vecinos más cercanos (K-Nearest Neighbors).

3. Visualización de datos 📊 -Seaborn: Proporciona una interfaz de alto nivel para crear gráficos estadísticos atractivos e informativos. -Matplotlib: Es una biblioteca de visualización de datos en Python que permite crear gráficos estáticos de alta calidad adecuados para publicaciones e informes.

4. Estadísticas y Pruebas 🧪 -Scipy: Proporciona funciones estadísticas y pruebas de hipótesis (por ejemplo, pruebas t, pruebas de chi-cuadrado, etc.)

5. Conexión a la Base de Datos ⚡ -mysql.connector: Conector para MySQL que permite establecer conexiones y realizar operaciones en bases de datos MySQL desde Python.

Estructura de la Base de Datos 📁

En este repositorio encontrarás una estructura en forma de estrella, que simplifica las consultas analíticas y es útil para el análisis de grandes volúmenes de datos.

Estructura

Descripción de la Información en la Base de Datos Final 📌

En este desplegable, encontrarás la descripción y distribución de cada una de las columnas del documento final. 😊

Diccionario:

Nombre de la columna	Descripción
Age	The employee’s age.
Age_Group	Referring to categorizing employees based on their age range. There are five labels: (18-25), (26-35), (36-45), (45-55) and (56-65).
Attrition	Indicates whether the employee has left the company (“False” means they haven’t left, and “True” means they have).
Business_Travel	Describes the frequency of work-related travel for the employee (e.g., “Travel_Rarely” for infrequent travel).
Daily_Rate	The employee’s daily rate.
Department	The department in which the employee works.
Distance_From_Home	The distance from the employee’s home to their workplace.
Education	The employee’s education level.(On a scale from 1 to 5)
Education_Field	The field of education or specialization for the employee.
Employee_Number	A unique identification number for the employee.
Environment_Satisfaction	Employee satisfaction level related to their work environment.( Ranging from 1 to 4, with 4 being the highest satisfaction)
Gender	The employee’s gender.(Where ‘M’ corresponds to “male” and ‘F’ to “female”).
Hourly_Rate	The employee’s hourly rate.
Job_Involvement	The level of employee involvement in their work.(On scale from 1 to 5).
Job_Level	The employee’s hierarchical level within the company, (On scale from 1 to 5).
Job_Role1	The employee’s position.
Job_Satisfaction	Employee satisfaction level with their job.(Ranging from 1 to 4, with 4 being the highest satisfaction).
Marital_Status	The employee’s marital status.(Accepts these values ‘Married’, ’Divorced’, and 'Unknown').
Monthly_Rate	The employee’s monthly rate.
Num_Companies_Worked	The number of companies where the employee has worked.
Over_Time	Indicates whether the employee works overtime.(Accepts these values “True”, “False” and 'Unknown').
Percent_Salary_Hike1	The percentage of salary increase for the employee.(Accepts values between 0 - 1)
Performance_Rating	Employee performance rating.(On scale from 1 to 5).
Relationship_Satisfaction	Employee satisfaction level in interpersonal relationships.(On scale from 1 to 5).
Stock_Option_Level	Employee stock option level.(On a scale from 0 to 4).
Total_Working_Years	Total years of work experience for the employee.
Training_Times_Last_Year	Number of times the employee received training last year.
Work_Life_Balance	Balance between work and personal life for the employee.(On scale from 1 to 5).
Years_At_Company	Number of years the employee has worked at the current company.
Years_Since_Last_Promotion	Years since the employee’s last promotion.
Years_With_Curr_Manager	Years under the supervision of the current manager.
Date_Birth	The employee’s birth year. (considering data collected in 2023).
RemoteWork	Whether the employee can work remotely or not.

Resolución del Objetivo 🎯🎯

• Para abordar nuestro objetivo, se llevó a cabo un análisis estadístico con el propósito de determinar si existe una diferencia significativa en la tasa de rotación de los empleados según su nivel de satisfacción en la empresa. Para ello, se dividió a los empleados en dos grupos según su nivel de satisfacción, y posteriormente se calculó la tasa de rotación para cada uno de estos grupos.

Grupo	Categoría	Descripción
Grupo A	Satisfechos	Empleados con un nivel de satisfacción en el trabajo igual o superior a 3 en una escala de 1 a 5.
Grupo B	Descontentos	Empleados con un nivel de satisfacción en el trabajo inferior a 3 en una escala de 1 a 5.

• Se establecieron dos hipótesis:

Hipótesis	Descripción
Hipótesis Nula (H0)	Afirmamos que no hay diferencia; la tasa de rotación no afecta al nivel de satisfacción.
Hipótesis Alternativa (H1)	Afirmamos que sí hay diferencia, el nivel de satisfacción afecta significativamente a la tasa de rotación.

• Test: 📈📝

Tipo de prueba	Descripción
ttest_ind()	Es una prueba estadística que se utiliza para comparar dos grupos y determinar si hay una diferencia significativa entre ellos en términos de una variable que estamos midiendo.
ztest()	Indica si el resultado observado está lejos del valor esperado bajo la hipótesis nula mediante la desviación estándar.
chi2()	La prueba chi cuadrado se utiliza para determinar el comportamiento de cierta variable y también para evaluar si dos o más variables son estadísticamente independientes

Analisis completo Tasa de Rotación

De toda la información que tenemos, extraemos la tasa de rotación. Es el indicador que mide la frecuencia con la que los empleados dejan la organización y son reemplazados por otros nuevos en el período de tiempo del que tenemos datos.**.

• La tasa de rotación en el Grupo A (con una satisfacción media y alta) es de 0.16%.
• La tasa de rotación en el Grupo B(satisfaccion baja) es de 0.24%.

Según estos datos, vemos que el descontento o la insatisfacción laboral está asociada con una mayor propensión a dejar la empresa.

Test:_📈📝

Realizamos diferentes test para comparar nuestros dos grupos y seguir explorando si hay una diferencia significativa o no en la tasa de rotación según la satisfacción.

• El t-test de Student:

  • Con p_value de: (0.004), indica que SÍ hay diferencia significativa entre los dos grupos. Por lo tanto, en este estudio se rechaza la H0.

• Z-test:

  • Con un stadistic de -2.94 y un p-value de 0.0032. Indica que la proporción de personas que dejaron la empresa en el Grupo A (empleados satisfechos) es menor que en el Grupo B (empleados descontentos). Esto refuerza la idea de que una mayor satisfacción laboral está asociada con una menor rotación de empleados. Así que de nuevo se rechaza la H0. Este valor es negativo, lo que indica que la proporción de personas que dejaron la empresa en el Grupo A (empleados satisfechos) es menor que en el Grupo B (empleados descontentos). El valor absoluto que es mayor que 2 sugiere que la diferencia es significativa, pero la dirección de la diferencia es contraria a la del incremento numérico en los datos (es decir, hay menos rotación donde podríamos esperar más, o viceversa).

• Chi2 test:

  • Chi-squared Test Statistic: con un valor de 8.2479 y un p-value: 0.0041, que nos indica nuevamente que existe una diferencia significativa en los niveles de satisfacción y la tasa de rotación. Hay evidencia suficiente para rechazar la hipótesisi nula.

Pruebas adicionales

Llevamos a cabo nuevas pruebas para conocer en mayor profundidad las razones por las que hay empleados descontentos.

Buscamos la corelación entre nuestras diferentes variables, y extraemos las siguientes conclusiones:

1. A más nivel de desempeño, más aumenta el porcentaje de subida de los salarios. Es señal de prácticas saludables de la empresa, que recompensan a los empleados que se esfuerzan y sacan el trabajo adelante.

Como se puede apreciar en la siguiente gráfica, la presencia de outliers en ambos valores (3 y 4), más notorios en el 3, denotan ciertas excepciones en la política de aumento de salario de la empresa para los empleados que tienen un nivel de desempeño medio. Esto podría ser un tema que despertase diferentes sentimientos entre los empleados, por lo que podría ser interesante realizar estudios al respecto. En base a ambas conclusiones, por ahora no podemos establecer motivos de descontento.

2. A más años trabajados, más aumenta el cargo de las personas empleadas. Lo que indica que la empresa promociona a sus personas trabajadoras a medida que pasa el tiempo. Esto también es una buena práctica y no se puede asociar con un motivo de descontento.

3. A más años trabajados y a más años en la empresa, más años con el/la actual manager. Esto podría indicar que los/las managers mantienen su puesto de trabajo, es decir que hay cierta estabilidad. En principio también podría considerarse una buena práctica de la empresa, aunque podría estudiarse en mayor profundidad. No encontramos motivos de descontento.

   

4. A más edad, más experiencia en diferentes empresas. Los empleados entre 40 y 44 años han trabajado en más empresas que los empleados más jóvenes que ellos. Esto tiene sentido y no debería ser motivo de descontento.

5. A más estudios, mayor cargo en la empresa. Esto también tiene sentido y no debería ser un problema para los empleados/as.

Conclusión: ✅

Basándonos en los resultados obtenidos, podemos inferir que la empresa implementa prácticas favorables hacia sus empleados, como aumentos salariales o ascensos. Sin embargo, el descontento de los empleados podría estar relacionado con otras variables que no se han estudiado en la actualidad.

Por lo tanto, recomendamos llevar a cabo encuestas dirigidas a los empleados, permitiéndoles expresar los motivos de su insatisfacción. Esto proporcionaría una visión más completa y ayudaría a abordar cualquier problema subyacente de manera efectiva

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English

ABC Corporation's Talent Optimization!!!

ABC Corporation's Talent Optimization Initiative aims to respond to different aspects related to the human resources of their company. For which he has hired the services of our company Data Gatgets.

Data Gatgets is a company formed by a group of data analysts who use agile methodology to meet each proposed objective efficiently and in record time.

Data Gatgets Team: 📈🔍

Names	GitHub_link_user_name
Patricia González	https://github.com/Patri-EGG
Paola Sánchez	https://github.com/paolasanchezsolorzano
Fernanda Martí	https://github.com/fernandaMarti
Nuria Cano	https://github.com/nuriancg
Raquel Castellanos	https://github.com/RachelCaste

Client Description: 👨‍💻

ABC Corporation, founded in 1980 in California, is a technology consulting firm specializing in providing artificial intelligence (AI) and machine learning solutions to companies in various industries.

Target: 🎯

Present the results of exploratory data analysis, design an A/B experiment to test critical hypotheses, and analyze the results to provide ABC Corporation with valuable and truthful information.

Initial Documentation: 📌

In this dropdown, you will find the description of each of the columns of the original document. 😊

Dictionary:

Column_Name	Description
Age	The employee’s age.
Attrition	Indicates whether the employee has left the company (“No” means they haven’t left, and “Yes” means they have).
BusinessTravel	Describes the frequency of work-related travel for the employee (e.g., “Travel_Rarely” for infrequent travel).
DailyRate	The employee’s daily rate.
Department	The department in which the employee works (e.g., “Research & Development,” “Sales,” etc.).
DistanceFromHome	The distance from the employee’s home to their workplace.
Education	The employee’s education level (usually on a scale from 1 to 5).
EducationField	The field of education or specialization for the employee.
EmployeeCount	A counter (usually set to 1) used for counting employees.
EmployeeNumber	A unique identification number for the employee.
EnvironmentSatisfaction	Employee satisfaction level related to their work environment, ranging from 1 to 4 (with 4 being the highest satisfaction).
Gender	The employee’s gender (where 0 corresponds to “male” and 1 to “female”).
HourlyRate	The employee’s hourly rate.
JobInvolvement	The level of employee involvement in their work.
JobLevel	The employee’s hierarchical level within the company.
JobRole	The employee’s job role or position.
JobSatisfaction	Employee satisfaction level with their job.
MaritalStatus	The employee’s marital status (e.g., “Single,” “Married,” etc.).
MonthlyIncome	The employee’s monthly income.
MonthlyRate	The employee’s monthly rate.
NumCompaniesWorked	The number of companies where the employee has worked.
Over18	Indicates whether the employee is over 18 years old.
OverTime	Indicates whether the employee works overtime (“Yes” or “No”).
PercentSalaryHike	The percentage of salary increase for the employee.
PerformanceRating	Employee performance rating.
RelationshipSatisfaction	Employee satisfaction level in interpersonal relationships.
StandardHours	Standard working hours.
StockOptionLevel	Employee stock option level.
TotalWorkingYears	Total years of work experience for the employee.
TrainingTimesLastYear	Number of times the employee received training last year.
WorkLifeBalance	Balance between work and personal life for the employee.
YearsAtCompany	Number of years the employee has worked at the current company.
YearsInCurrentRole	Number of years the employee has been in their current role.

Phases: 🔄

To complete development of this project and ensure the integrity of the data provided by the client, five phases were carried out.

• Phase 1: Data Exploration and Cleaning

• Phase 2: Data Transformation

• Phase 3: Database Design and Implementation

• Phase 4: A/B Testing

• Phase 5: ETL Creation

• Phase 6: Reporting

To play this project on your computer: 🐍 and 🐬

For the project you will need to have a version of Python and MySQL and get to work.

Libraries to Import: 📚

Libraries to start working:

1. Data Manipulation 🧮 🐼

   • Pandas
   • Numpy

2. Imputación de datos 🕵️‍♂️

   • Scikit-learn
     • SimpleImputer:Imputes missing values in a dataset using simple strategies such as mean, median, mode, and others.
     • IterativeImputer:Utilizes iterative techniques, especially useful when relationships between variables are complex.
     • KNNImputer:Uses the K-Nearest Neighbors method to estimate missing values.

3. Data visualization 📊 -Seaborn: Provides a high-level interface for creating attractive and informative statistical graphics. -Matplotlib:Allows the creation of high-quality static plots suitable for publications and reports.

4. Stadistics and tests 🧪

   • Scipy:Provides statistical functions and hypothesis tests (e.g., t-tests, chi-square tests, etc.).

5. Database Connection ⚡

   • mysql.connector:A connector for MySQL that allows establishing connections and performing operations on MySQL databases from Python.

BBDD Structure: 📁

In this repository you will find a star-shaped structure, which simplifies analytical queries and is useful for the analysis of large volumes of data.

Structure

Description of the information you will find in the final BBDD: 📌

In this dropdown, you will find the description and distribution of each of the columns of the final document. 😊

Dictionary:

Column_Name	Description
Age	The employee’s age.
Age_Group	Referring to categorizing employees based on their age range. There are five labels: (18-25), (26-35), (36-45), (45-55) and (56-65).
Attrition	Indicates whether the employee has left the company (“False” means they haven’t left, and “True” means they have).
Business_Travel	Describes the frequency of work-related travel for the employee (e.g., “Travel_Rarely” for infrequent travel).
Daily_Rate	The employee’s daily rate.
Department	The department in which the employee works.
Distance_From_Home	The distance from the employee’s home to their workplace.
Education	The employee’s education level.(On a scale from 1 to 5)
Education_Field	The field of education or specialization for the employee.
Employee_Number	A unique identification number for the employee.
Environment_Satisfaction	Employee satisfaction level related to their work environment.( Ranging from 1 to 4, with 4 being the highest satisfaction)
Gender	The employee’s gender.(Where ‘M’ corresponds to “male” and ‘F’ to “female”).
Hourly_Rate	The employee’s hourly rate.
Job_Involvement	The level of employee involvement in their work.(On scale from 1 to 5).
Job_Level	The employee’s hierarchical level within the company, (On scale from 1 to 5).
Job_Role1	The employee’s position.
Job_Satisfaction	Employee satisfaction level with their job.(Ranging from 1 to 4, with 4 being the highest satisfaction).
Marital_Status	The employee’s marital status.(Accepts these values ‘Married’, ’Divorced’, and 'Unknown').
Monthly_Rate	The employee’s monthly rate.
Num_Companies_Worked	The number of companies where the employee has worked.
Over_Time	Indicates whether the employee works overtime.(Accepts these values “True”, “False” and 'Unknown').
Percent_Salary_Hike1	The percentage of salary increase for the employee.(Accepts values between 0 - 1)
Performance_Rating	Employee performance rating.(On scale from 1 to 5).
Relationship_Satisfaction	Employee satisfaction level in interpersonal relationships.(On scale from 1 to 5).
Stock_Option_Level	Employee stock option level.(On a scale from 0 to 4).
Total_Working_Years	Total years of work experience for the employee.
Training_Times_Last_Year	Number of times the employee received training last year.
Work_Life_Balance	Balance between work and personal life for the employee.(On scale from 1 to 5).
Years_At_Company	Number of years the employee has worked at the current company.
Years_Since_Last_Promotion	Years since the employee’s last promotion.
Years_With_Curr_Manager	Years under the supervision of the current manager.
Date_Birth	The employee’s birth year. (considering data collected in 2023).
RemoteWork	Whether the employee can work remotely or not.

Target Resolution 🎯🎯

A statistical analysis was carried out in order to determine if there is a significant difference in the rotation rate of employees according to their level of satisfaction in the company.To do this, employees were divided into two groups according to their level of satisfaction, and then the rotation rate for each of these groups was calculated.

Group	Category	Description
Group A	Satisfied	Employees with a job satisfaction level equal to or greater than 3 on a scale of 1 to 5.
Group B	Discontents	Employees with a job satisfaction level of less than 3 on a scale of 1 to 5.

• Two hypotheses were established:

Hypothesis	Description
_ Null hypothesis (H0)_	Affirm that there is no difference; Turnover rate does not affect the level of satisfacción.
_ Alternative hypothesis (H1)_	Affirmthere is a difference, the level of satisfaction significantly affects the rate of rotación.

Test: 📈 📝

Test Type	Description
ttest_ind()	It is a statistical test used to compare two groups and determine if there is a significant difference between them in terms of a variable we are measuring.
ztest()	Indicates how many standard deviations the observed result deviates from the expected value under the null hypothesis.
chi2()	The chi-squared test is used to determine the behavior of a certain variable and also to evaluate whether two or more variables are statistically independent

Full Rotation Rate Analysis

Of the information we have, we extract the rotation rate. It is the indicator that measures how often employees leave the organization and are replaced by new ones in the time period being analyzed.

• Rotation rate in Group A (with medium and high satisfaction) is 0.16%.
• Rotation rate in Group B (low satisfaction) is 0.24%.

Based on this data, we see that job dissatisfaction or dissatisfaction is associated with a greater propensity to leave the company.

Test:_📈📝

• ttest:

  • With a p-value of 0.004, it indicates that there is a significant difference between the two groups. Therefore, in this study, we reject the null hypothesis (H0).

• Z-test:

  • With a statistic of -2.94 and a p-value of 0.0032, it indicates that the proportion of people who left the company in Group A (satisfied employees) is lower than in Group B (dissatisfied employees). This reinforces the idea that higher job satisfaction is associated with lower employee turnover. Therefore, we once again reject the null hypothesis. The negative value suggests that the proportion of people who left the company in Group A (satisfied employees) is lower than in Group B (dissatisfied employees). The absolute value, greater than 2, implies that the difference is significant, but the direction of the difference contradicts the numerical increase in the data (i.e., there is less turnover where we might expect more, or vice versa).

• Chi2 test:

  • A value of 8.2479 with a p-value of 0.0041 indicates once again that there is a significant difference in satisfaction levels and turnover rate. There is sufficient evidence to reject the null hypothesis.

ADDITIONAL TESTS

We made new tests to aquire a deeper understanding of the reasons why employees are dissatisfied; we looked for correlations among the different variables and extracted the following conclusions:

1. The higher the performance level, the greater the percentage increase in salaries. This is a sign of healthy company practices that reward employees who put in effort on their work.

In the following chart, the presence of outliers in both values (3 and 4), major in 3, indicates certain exceptions in the company’s salary increase policy for employees with a medium performance level. This could be a topic that evokes different feelings among employees, so it might be interesting to make future studies to explore this topic further.

Based on both conclusions, we cannot currently establish reasons for discontent.

2. The longer employees work, the higher their position within the company. This indicates that the company promotes its employees over time. This practice is also positive and cannot be associated with discontent.

3. The longer an employee has worked and the longer they have been with the company, the more years they spend with their current manager. This could indicate that managers maintain their positions, suggesting a certain level of stability. Initially, this could also be considered a good practice by the company, although it might warrant further study. We don’t find any reasons for discontent.

4. As employees get older, they accumulate more experience across different companies. Employees between 40 and 44 years old have worked in more companies than their younger counterparts. This makes sense and should not be a cause for discontent.

5. The higher the level of education, the more senior the position within the company. This also makes sense and should not be a problem for employees.

Conclusion: ✅

Based on the results obtained, we can infer that the company implements favorable practices for its employees, such as salary increases or promotions. However, employee dissatisfaction may be related to other variables that have not been studied currently.

Therefore, we recommend conducting surveys targeted at employees, allowing them to express the reasons for their dissatisfaction. This would provide a more comprehensive view and help address any underlying issues effectively.