Business Mathematics & Statistics Quiz

1. The regression equation should only used:

When there is significant linear correlation

When there is significant mluticorrelation

When there is significant quadratic correlation

When there is significant simple correlation

The regression equation should only be used when there is a significant linear correlation between the variables. This means that there is a strong relationship between the independent and dependent variables that can be described by a straight line. If there is no linear correlation or if the correlation is not significant, using a regression equation may not provide accurate or meaningful results.

Explanation

The regression equation should only be used when there is a significant linear correlation between the variables. This means that there is a strong relationship between the independent and dependent variables that can be described by a straight line. If there is no linear correlation or if the correlation is not significant, using a regression equation may not provide accurate or meaningful results.

2. If strength of the association between X and Y is very weak, then r = ?

R = - 1

R = 0

R = 1

R = 2

If the strength of the association between X and Y is very weak, it means that there is no linear relationship between the two variables. In other words, the correlation coefficient (r) would be close to zero. A correlation coefficient of 0 indicates that there is no linear relationship between X and Y, and they are not related to each other in any way.

Explanation

If the strength of the association between X and Y is very weak, it means that there is no linear relationship between the two variables. In other words, the correlation coefficient (r) would be close to zero. A correlation coefficient of 0 indicates that there is no linear relationship between X and Y, and they are not related to each other in any way.

3. The variance of the 3, 3, 3, 3, 3 is:

Zero

One

Twice the standard standard deviation

Half of the range

The variance of a set of numbers measures how spread out the numbers are from the average. In this case, all the numbers in the set are the same (3), so there is no variation or spread. Therefore, the variance is zero.

Explanation

The variance of a set of numbers measures how spread out the numbers are from the average. In this case, all the numbers in the set are the same (3), so there is no variation or spread. Therefore, the variance is zero.

4. My estimated regression line is Y = 17 + 4X. The intercept is equal to:

17

4

21

13

Y represents the dependent variable
X represents the independent variable
a represents the Y-intercept
(i.e. the value of Y when X is equal to zero)
b represents the slope of the line
(i.e. the value of the tan , where  represents the angle between the line and the horizontal axis)

Explanation

Y represents the dependent variable
X represents the independent variable
a represents the Y-intercept
(i.e. the value of Y when X is equal to zero)
b represents the slope of the line
(i.e. the value of the tan , where  represents the angle between the line and the horizontal axis)

5. The point where a straight line cuts the x-axis is called:

Slope

Starting point

Y-intercept

X-intercept

The x-intercept is the point at which a straight line intersects the x-axis. It represents the value of x when y is equal to zero. In other words, it is the x-coordinate of the point where the line crosses the x-axis. The y-intercept, on the other hand, represents the value of y when x is equal to zero. The slope refers to the steepness of the line, while the starting point is not a commonly used term in relation to the x-axis.

Explanation

The x-intercept is the point at which a straight line intersects the x-axis. It represents the value of x when y is equal to zero. In other words, it is the x-coordinate of the point where the line crosses the x-axis. The y-intercept, on the other hand, represents the value of y when x is equal to zero. The slope refers to the steepness of the line, while the starting point is not a commonly used term in relation to the x-axis.