Question

Please answer the question briefly and clearly.

1. The best model to describe a linear relationship between two variables is the _______.

2. An assumption of linear regression states that for each value of X, there is a group of Y values that are statistically (Independent) and (normally distributed) about the regression line.

3. If the slope of a regression line is zero, the orientation of the regression line is (Flat, or Constant), which indicates a lack of a relationship.

4. For an inverse relationship between two variables, the sign of the correlation coefficient is __________.

5. The standard error of the estimate measures the scatter or dispersion of the observed values around a (Mean of Observed value which is a predicted value ).

Answer 1

In question no .2,3 and 5 it is not mentioned clearly that what is being asked. Hence, i am answering question nos. 1 and 4.

Answer 1. For describing linear relationship you can assume model

Y= a + bX

This type of relation may be described by a straight line. The intercept that the line makes on the Y-axis is given by 'a' and the slope of the line is given by 'b'. It gives the change in the value of Y for very small change in the value of X. For estimating a and b, you can make the use of least squares principle.

Answer 2. For an inverse relationship between two variables, the correlation coefficient r<0, hence its its sign has to be negative. This type of relation is shown on a scatter diagram as having a downward sloping line and the variables move in opposite directions.