In this People Analytics project, the focus was on understanding the factors that influence employee performance. The project involved analyzing various factors, including gender, age, and other relevant variables, to determine their impact on employee performance.

To achieve this, statistical techniques such as chi-square analysis, factor analysis, one-way ANOVA, and regression analysis were employed. Chi-square analysis was used to examine the association between categorical variables like gender and performance levels. Factor analysis helped identify underlying factors that contribute to employee performance. One-way ANOVA was performed to compare performance across different age groups or other relevant categories. Regression analysis was utilized to establish relationships and quantify the impact of multiple factors on employee performance.

Through the application of these statistical techniques and hypothesis testing, valuable insights were gained regarding the significant factors influencing employee performance. The project provided a comprehensive understanding of how variables such as gender, age, and other factors impact employees' overall performance, enabling organizations to make informed decisions and implement strategies to enhance employee productivity and engagement.