The appropriate expression to identify the amount of formalin is: x = 3200 ÷ 100 × 44%
<h3>How to identify the amount of formalin?</h3>
To calculate the amount of formalin in this substance we must perform the following mathematical operation:
- 3200 ÷ 100 = 32
- 32 × 44% = 1,408
According to the above, the mathematical expression would be:
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|3.5| = 3.5
Any negative or positive number will always have an absolute value that is positive.
For example, | -3.5| = 3.5
3.5 can also be expressed a fraction.
3.5 * 2/2 = 7/2
Step-by-step explanation:
the slope of a line is the ratio y/x.
that means, when going from one point to the other, how many units y changes, when x changes a certain number of units.
the sign indicates the direction of the change (+ for larger and - for smaller).
so, here x changes by 6 units (from -3 to 3), and y changes by -2 units (from 4 to 2).
therefore, the slope is
-2/6 = -1/3
Depending on your dependent/outcome variable, a negative value for your constant/intercept should not be a cause for concern. This simply means that the expected value on your dependent variable will be less than 0 when all independent/predictor variables are set to 0. For some dependent variables, this would be expected. For example, if the mean value of your dependent variable is negative, it would be no surprise whatsoever that the constant is negative; in fact, if you got a positive value for the constant in this situation, it might be cause for concern (depending on your independent variables).Even if your dependent variable is typically/always positive (i.e., has a positive mean value), it wouldn't necessarily be surprising to have a negative constant. For example, consider an independent variable that has a strongly positive relationship to a dependent variable. The values of the dependent variable are positive and have a range from 1-5, and the values of the independent variable are positive and have a range from 100-110. In this case, it would not be surprising if the regression line crossed the x-axis somewhere between x=0 and x=100 (i.e., from the first quadrant to the fourth quadrant), which would result in a negative value for the constant.The bottom line is that you need to have a good sense of your model and the variables within it, and a negative value on the constant should not generally be a cause for concern. Typically, it is the overall relationships between the variables that will be of the most importance in a linear regression model, not the value of the constant.
