The difference between 11.0 and 12.5 is 1.5 and same with 12.5 and 14.0, so 1.5 is what the hair increases by every THREE months but if you want to find PER month, you are going to divide 1.5 by those 3 months to get .5 inches per month, so your slope will be 1/2
Answer:
If the null hypothesis is true in a chi-square test, discrepancies between observed and expected frequencies will tend to be small enough to qualify as a common outcome.
Step-by-step explanation:
Here in this question, we want to state what will happen if the null hypothesis is true in a chi-square test.
If the null hypothesis is true in a chi-square test, discrepancies between observed and expected frequencies will tend to be small enough to qualify as a common outcome.
This is because at a higher level of discrepancies, there will be a strong evidence against the null. This means that it will be rare to find discrepancies if null was true.
In the question however, since the null is true, the discrepancies we will be expecting will thus be small and common.
It seemed like it should have been so simple. There was nothing inherently difficult with getting the project done. It was simple and straightforward enough that even a child should have been able to complete it on time, but that wasn't the case. The deadline had arrived and the project remained unfinished.
Answer:
A) allows the population effect on log earnings of being married to depend on gender
Step-by-step explanation:
The regression equation of a dependent variable based on two or more independent variables is of the form:
Here,
<em>Y</em> = dependent variable
and = independent variables
= interaction term
= regression coefficients.
If there is a significant interaction effect present then this implies that the effect of one independent variable ( or ) on the dependent variable (<em>Y</em>) differs every time with different value of the other independent variable ( or ) .
The provided regression equation is:
= dependent variable
and = independent variables
In this case the interaction term is defined as follows:
The effect of being married on log earnings is dependent on different values of the variables , i.e. the gender of the person.
Thus, the correct option is (A).