When is a linear model not a good fit for a set of data?
when there is not a constant rate of change.
when each input value has only one output value.
when the data set does not go through the origin.
when the data set does not increase.
when there is not a constant rate of change

When there is not a constant rate of change

Step-by-step explanation:

A linear model shows a continuous response variable as a function of one or more predictor variables.

A linear model is a good fit for a set of data when the plotted points show a constant rate of change.

When a plot of values form a scatter plot, it is difficult to identify a linear model because the points will not appear to follow a trend.

To come up with a linear function in this case will require you to identify the line of best fit then extending the line to y-axis intercept so as to be able to find the slope.

set each factor equal to 0

4x-3 = 0

2x-1 = 0

solve for x.

4x-3=0

4x=3

x= 3/4

solve for x. 

2x-1= 0

2x= 1

x= 1/2

eventually after a few more steps, your answer should be 1/2 is less than or equal to x and 3/4 is greater than or equal to x