A 90 percent confidence interval for the slope of a regression line is determined to be (-0.181, 1.529). Which of the following statements must be true?

a. The correlation coefficient of the data is positive.
b. The sum of the residuals for the data based on the regression line is positive.
c. A scatterplot of the data would show a linear pattern.
d. The slope of the sample regression line is 1.348.
e. The slope of the sample regression line is 0.

Respuesta :

Answer: a. The correlation coefficient of the data is positive.

Step-by-step explanation:

Estimated slope of sample regression line  = [tex]\dfrac{Upper \ limit + lower\ limit}{2}[/tex]

Here , confidence interval :  (-0.181, 1.529)

Estimated slope of sample regression line  = [tex]\dfrac{-0.181+1.529}{2}[/tex]

[tex]=\dfrac{1.348}{2}\\\\=0.674\ \ \ \ [\text{ positive}][/tex]

⇒Correlation coefficient(r) must be positive, So a. is true.

But, d. and e. are wrong(0.674 ≠ 0 or 1.348).

We cannot check residuals or its sum from confidence interval of slope of a regression line, so b is wrong.

We cannot say that scatterplot is linear as we cannot determine it from interval, so c. is wrong

So, the correct option : a. The correlation coefficient of the data is positive.

The true statement is (a) the correlation coefficient of the data is positive.

The 90% confidence interval of the slope of the regression line is given as:

Interval = (-0.181, 1.529)

The mean of the 90% confidence interval is:

[tex]\mu =\frac{-0.181 + 1.529}{2}[/tex]

[tex]\mu =0.674[/tex]

Given that, the mean value is positive, then the correlation coefficient is positive.

Hence, option (a) is true

Read more about confidence intervals at:

https://brainly.com/question/17097944