**Regression Equation**

To find the value of byx, we need to first understand the regression equation. The regression equation is a mathematical formula that represents the relationship between the dependent variable (y) and the independent variable (x) in a linear regression model. It is usually expressed in the form of y = mx + b, where m is the slope and b is the y-intercept.

**Given Equation**

The given equation is 2x + 3y + 50 = 0. We can rearrange this equation to isolate y:

3y = -2x - 50

Dividing both sides by 3:

y = (-2/3)x - 50/3

Comparing this equation with the general form of the regression equation (y = mx + b), we can determine the values of m and b:

m = -2/3
b = -50/3

**Calculation of byx**

The value of byx represents the slope of the regression line when x is the independent variable and y is the dependent variable. It measures the change in y for every unit change in x.

byx = m * (σx/σy)

To calculate byx, we need the standard deviations of x (σx) and y (σy).

**Calculation of Standard Deviations**

The standard deviation is a measure of the dispersion or spread of a dataset. We can calculate the standard deviation using the formula:

σ = √(Σ(x - μ)² / N)

where Σ represents the sum of, x is the data point, μ is the mean, and N is the number of data points.

To calculate σx and σy, we need the values of x and y.

**Assumptions**

Since the values of x and y are not provided in the question, we cannot calculate the standard deviations or the value of byx accurately. However, we can demonstrate the process and explain how the calculation would be done if the data were provided.

**Conclusion**

In conclusion, the value of byx cannot be determined without the values of x and y. However, we have explained the process and steps involved in calculating byx using the regression equation.