1 Justify the regression model you have used2 Report the results of your regression including what is economically significant and statistically significant3 Using the results that you have found just

(1) The regression model used is justified based on its ability to capture the relationship between the independent variables (team composition factors) and the dependent variable (performance in multi-player mode). A linear regression model is often appropriate when examining the impact of multiple variables on a continuous outcome variable, which aligns with our objective of determining the optimal team composition.

(2) The results of the regression analysis reveal both economically significant and statistically significant factors. Economically significant factors refer to variables that have a substantial impact on the outcome variable and are meaningful from a practical standpoint. Statistically significant factors, on the other hand, indicate that the relationship between the independent variables and the dependent variable is unlikely to have occurred by chance.

To report the results, we would list the coefficients of the independent variables along with their corresponding p-values. The coefficients represent the estimated impact of each variable on the outcome variable, while the p-values indicate the statistical significance. We would focus on variables with significant coefficients (p-value < 0.05) as these have a robust relationship with performance in multi-player mode. Additionally, we may examine the R-squared value of the regression, which indicates the proportion of the variability in the dependent variable that can be explained by the independent variables.

(3) Based on the regression results, we can justify the optimal team composition for multi-player mode by identifying the variables with the most significant positive coefficients. These variables indicate factors that have a strong positive impact on performance. For example, if the regression analysis reveals that having a high level of teamwork and communication skills has a statistically and economically significant coefficient, we can conclude that these factors are crucial for optimal team composition. Similarly, if certain character attributes or roles have significant positive coefficients, they should be considered when forming a team.

It is important to note that the choice of optimal team composition may also depend on other factors such as game dynamics, player preferences, and strategic considerations. Therefore, the regression results should be interpreted in conjunction with other relevant information to make a well-informed decision