the correct option is B

The residuals have to be distributed about equally among positive and negative values

That shows that the line of best fit goes through the middle of the data and is not to one side. This is the only residual plot that shows this.

I found an answer from reference.wolfram.com

Chapter **4 Fitting Data** to Linear **Models** by Least-Squares Techniques

**It** means that the **model** being **fit** is linear in the parameters to which we are **fitting**
... The **best**-known and most widely used method is least-squares regression,
which ... **it** to give a totally misleading **summary** of the relationship between y and
x . ... Then for each **data** point the **residual** is defined as the **difference** between
the ...

For more information, see Chapter **4 Fitting Data** to Linear **Models** by Least-Squares Techniques

I found an answer from www.britannica.com

Statistics - **Residual** analysis | Britannica

If the error term in the regression **model** satisfies the **four** assumptions noted ...
**These residuals**, computed from the available **data**, are treated as estimates. ... **it**
often suggests ways in which the **model** can be modified to obtain **better** results.
... how much or how many; qualitative variables **represent types** or categories.

For more information, see Statistics - **Residual** analysis | Britannica

I found an answer from stanford.edu

Visualizing regression **models** — seaborn 0.11.1 documentation

Many **datasets** contain multiple quantitative variables, and the goal of an analysis
is ... draw a **scatterplot** of two variables, x and y , and then **fit** the regression **model**
y ~ x ... **dataset** is the **same**, but the **plot** clearly shows that this is not a **good**
**model**: ... **It fits** and removes a simple linear regression and then **plots** the
**residual** ...

For more information, see Visualizing regression **models** — seaborn 0.11.1 documentation