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1. the correlation coefficient for a set of linear data is r = - 0.6. w…

Question

  1. the correlation coefficient for a set of linear data is r = - 0.6. what does this mean?
  2. which equations have no solution? a. - 5.2x + 2 = 8.1 b. 5x = 0 c. x + 3 = x + 1 d. x = x + 10
  3. write a sentence to describe the association. then draw a trend line to represent the data.
  4. name the obvious point on the line y - 6 = 2(x + 13).
  5. graph 8x - 6y = - 24
  6. solve for x. 3 - 2(x - 7)+1 = 4x
  7. create a graph that: is exponential, is decreasing, is discrete, contains (4,2)
  8. evaluate the expression b² - 4ac if a = - 1, b = 6, and c = 8.

Explanation:

1.

Step1: Interpret correlation coefficient

The correlation coefficient $r$ measures the strength and direction of a linear relationship. A value of $r = - 0.6$ indicates a moderate negative linear relationship. That is, as one variable increases, the other variable tends to decrease, and the linear - association is not very weak nor very strong.

Step1: Analyze option A

Solve $-5.2x + 2=8.1$. Subtract 2 from both sides: $-5.2x=8.1 - 2=6.1$. Then $x =-\frac{6.1}{5.2}$, so it has a solution.

Step2: Analyze option B

Solve $5x = 0$. Divide both sides by 5, we get $x = 0$, so it has a solution.

Step3: Analyze option C

Solve $x + 3=x + 1$. Subtract $x$ from both sides, we get $3 = 1$, which is a contradiction. So it has no solution.

Step4: Analyze option D

Solve $x=x + 10$. Subtract $x$ from both sides, we get $0 = 10$, which is a contradiction. So it has no solution.

Step1: Describe association

Looking at the scatter - plot, as the value on the x - axis (Car Cost) increases, the value on the y - axis (Miles per Gallon) seems to decrease. So, there is a negative association between car cost and miles per gallon.

Step2: Draw trend line

To draw a trend line, try to draw a straight line that best fits the data points. Place the line so that approximately half of the data points are above the line and half are below the line.

Answer:

There is a moderate negative linear relationship between the variables in the data - set.

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