91影视

The figure is :

A simple random sample (SRS) of size $n$ is made up of $n$ people chosen from the population with an equal chance of being the sample that is actually chosen.

Output is

The pattern in the scatter plot is linear and positive, according to the provided scatter plot. In addition, there are no outliers in the plot and the points do not deviate from the main trend. As a result, the weekly sales revenue may be considered to be proportional to the length of the house given to the brand of house.

The general equation of the regression line is,

$\stackrel{铃�}{y}=a+bx$

The dependent variable (X) is shelf length, and the dependent variable (Y) is sales, according to the query. The constant value is $317.94$, and the coefficient of the variable "Shelf length" is $317.94,$ according to the provided output.

Thus, $a=318.16and152.680$

Putting the values of $a$ and $b$ in the regression line. Thus:

$$\begin{gathered} \overline{y}=a+bx \\ =317.94+152.680x \end{gathered}$$

Thus, the regression line is$\stackrel{铃�}{y}=317.94+152.680x$

The most accurate prediction of weekly sales income is:

$$\begin{gathered} \stackrel{铃�}{y}=317.94+152.680x \\ =317.94+152.68\left(5\right) \\ =1081.34 \end{gathered}$$

Thus, the best estimate is$\$1081.34$

$s$ is $22.9212$ in the output. It demonstrates that the expected sale of the week is likely to be $\$22.9212$ off from the actual or genuine sale on average.

The coefficient of determination reveals how much variance in the response variable is explained by the predictor variable. The coefficient of determination in this case is $98.2\%$ As a result, the least square line may account for $98.2$ percent of the variation in the response variable.

The data range is between 3 and 6 feet, as can be observed. As a result, stating that the shelf's length is 0 would be incorrect. As a result, he should provide the right response.