Distribute. -3(-2x - 1)
2 answers:
You might be interested in
Answer:
1)
2)
3) A Type I error happens when we reject a null hypothesis that is true. In this case, that would mean that the conclusion is that there is evidence to support the claim that the greater the incentive, the more puzzles are solved, but that in reality there is no significant difference.
4) A Type II error happens when a false null hypothesis is failed to be rejected. In this case, that would mean that there is no enough evidence to support the claim that the greater the incentive, the more puzzles are solved, but in fact this is true.
5) The probability of a Type I error is equal to the significance level, as this is the chance of having a sample result that will make the null hypothesis be rejected.
Step-by-step explanation:
As the claim is that the greater the incentive, the more puzzles were solved, the null hypothesis will state that this claim is not true. That is that there is no significant relation between the incentive and the amount of puzzles that are solved. In other words, the mean amount of puzzles solved for the different incentives is equal (or not significantly different):
The research (or alternative hypothesis) is that the greater the incentive, the more puzzles were solved. That means that the mean puzzles solved for an incentive of 50 cents is significantly higher than the mean mean puzzles solved for an incentive of 25 cents and this is significantly higher than the mean puzzles solved for an incentive of 5 cents.
A Type I error happens when we reject a null hypothesis that is true. In this case, that would mean that the conclusion is that there is evidence to support the claim that the greater the incentive, the more puzzles are solved, but that in reality there is no significant difference.
A Type II error happens when a false null hypothesis is failed to be rejected. In this case, that would mean that there is no enough evidence to support the claim that the greater the incentive, the more puzzles are solved, but in fact this is true.
The probability of a Type I error is equal to the significance level, as this is the chance of having a sample result that will make the null hypothesis be rejected.
Answer:
Step-by-step explanation:
Gotta love these motion problems!
d = rt is what we need here to solve this, along with some logic.
If the EB (eastbound) train left at noon then at the end of its travels, at 8pm to be specific, it was traveling for 8 hours. Therefore, for the EB train, t = 8.
If the WB train left at 4 pm then at the end of its travels, also at 8pm, it was traveling for 4 hours. Therefore, for the WB train, t = 4.
The distance between the trains is given as 400 miles. That 400 mile distance is due to the fact that each train traveled a distance of rate*time. The distance the WB train traveled + the distance the EB train traveled = 400 miles. Now we just need to find out the distance each traveled in its respective time frame.
For the EB train. We already know that t = 8. We do not know how fast it's going, so rate is just r. In the distance formula, d = rt:
For the WB train. We already know that t = 4. We do not know this rate either, but we do know that it is traveling 10 mph faster than the EB train, so rate is r + 10. In the distance formula, d = rt:
and
We have already determined that
so
4r + 40 + 8r = 400 and
12r + 40 = 400 and
12r = 360 so
r = 30
That means that the EB train is traveling 30 mph and the WB train then has to be traveling 40 mph.
These are quite difficult...I get it. They drive all my students, regardless of what math level they are in, absolutely batty!!!