<u>Explanation:</u>
1. a) Null hypothesis: There is <em>no</em> statistically significant relationship between the mouse grimace scale and the amount of pain felt by mouse.
b) Alternate hypothesis: There is a statistically-significant relationship between the mouse grimace scale and the amount of pain felt by mouse.
2. Yes, because a statistically significant data implies that there is sufficient evidence to believe the study, based on the results of the findings.
3. No, since the variables are different in this case. Here we are dealing with a non-painful solution so there may be no sample correlation as extreme as that found in the original study.
4. Possibly, because every hypothesis is an assumption until it is proven. Thus, in every statistical research, there may be different findings.
Answer:
Step-by-step explanation:
Pi*radius^2 gives you the circumference of the circle, add the rest of the equation and it’ll give you volume
$425 is the awnser for this one have a great day
Step-by-step explanation:
Given
GPA = NO + B1Study + B2work + B3leisure + B4sleep + u
1. No it makes no sense. There is an intercorellation between these explanatory variables. Changing study while holding the rest variables constant or fixed would not make sense. If study us changed then one or more of the other predictors should be changed so that they can still be equal to 168
2. Study is a perfect linear function of work, leisure and sleep. There is the problem of multicollinearity among these independent variables. One assumption of the MLR is no multicollinearity.
3. To reformulate model, you have to drop the variable that is having the issue. Let's say that leisure is dropped from the model. After this the assumption is satisfied.
GPA = b0 + B1Study + b2sleep + b3work + u
