Below is a correlation matrix for variables related to the annual salary for 30 employees at a company. The variables are gender (1 for female; 0 for male), age, number of years of relevant work experience prior to employment at the company, number of years of employment at the company, the number of years of post-secondary (college) education, and annual salary. Which variable has the strongest linear relationship with salary? Which two variables have the weakest linear relationship? Interpret the negative correlation between gender and salary The image displays a correlation matrix illustrating the relationships between six variables: Gender, Age, Birthdate, Years at Company, Education, and Salary. Each cell in the matrix shows the correlation coefficient between two variables, with values ranging from -1 to 1. A value of 1 indicates a perfect positive correlation, while a value of -1 indicates a perfect negative correlation. A value of 0 indicates no correlation.Here is the correlation matrix:- **Gender** - Gender: 1.000 - Age: 0.111 - Birthdate: 0.251 - Years at Company: -0.358 - Education: 0.020 - Salary: 0.154- **Age** - Gender: 0.111 - Age: 1.000 - Birthdate: 0.800 - Years at Company: 0.514 - Education: 0.618 - Salary: 0.976- **Birthdate** - Gender: 0.251 - Age: 0.800 - Birthdate: 1.000 - Years at Company: 0.587 - Education: 0.884 - Salary: 0.335- **Years at Company** - Gender: -0.358 - Age: 0.514 - Birthdate: 0.587 - Years at Company: 1.000 - Education: 0.472 - Salary: 0.570- **Education** - Gender: 0.020 - Age: 0.618 - Birthdate: 0.884 - Years at Company: 0.472 - Education: 1.000 - Salary: 0.017- **Salary** - Gender: 0.154 - Age: 0.976 - Birthdate: 0.335 - Years at Company: 0.570 - Education: 0.017 - Salary: 1.000This matrix can be used for statistical analysis to assess the degree of association between these variables in the dataset. Higher absolute values of the correlation suggest a stronger relationship.

The extent of linear relation between two variables is known as correlation. It is denoted by r. Range of correlation for positive correlation is 0<r<1. Values between 0.7 and 1 indicates strong positive correlation. Range of correlation for positive correlation is -1<r<0. Values between -1 and -0.7 indicates strong negative correlation.Salary is having strongest linear relationship with variable Age. As correlation between these two variables is 0.923. This number indicates that, there strong positive correlation between variables Salary and Age. From correlation matrix it is observed that, variables Education and gender have weakest linear relationship. As value of correlation coefficient between these two variables is -0.039. Correlation coefficient between Salary and Gender is -0.154. Since this coefficient is in the range -1 to 0, is concluded that there is negative correlation between variables Salary and Gender, but this is not strong negative correlation as -0.154 is greater than -0.7.