91影视

$x:$Height of a student.

$y:$Number of steps required to walk the length of a school hallway.

Kiana took $49$ steps to walk down the corridor, despite her height of $67$ inches.

The given OLS regression line is:

$\stackrel{铃�}{y}=113.6鈭�0.921x$

Kiana's projected walk based on her height can be computed as follows:

$$\begin{gathered} \stackrel{铃�}{y}=113..60鈭�0.921\left(67\right) \\ =51.8930 \end{gathered}$$

The residual for Kiana can be calculated as:

$$\begin{gathered} e=y鈭�\stackrel{铃�}{y} \\ =67鈭�51.8930 \\ =15.1070 \end{gathered}$$

The residual is the discrepancy or fluctuation between the true and anticipated value. Here, Kiana's residual is $15.1070$ or about $15$ walks, indicating that the difference between Kiana's actual and anticipated walk is $15$

If Matthew is $10$ inches taller than Samantha, the number of less predicted steps that Matthew will take can be computed as follows:

Samantha 鈥榳alk

$\stackrel{铃�}{y_1}=113.6鈭�0.921x$

Matthew 鈥榳alk

$$\begin{gathered} \stackrel{铃�}{y_2}=113.6鈭�0.921\left(10x\right) \\ =113.6鈭�9.21x \end{gathered}$$

The expected walk is:

$$\begin{gathered} E=y_1-y_2 \\ =113.6鈭�0.921x鈭�113.6+9.21x \\ =8.289x \\ 鈮�8x \end{gathered}$$