Answer:
its already in its simplest form.
Answer: The answer to your question is -1 because 16 is -1 to 15.
Answer:
the answer is 
Step-by-step explanation:
Try using Symbolab, I use it all the time it gives the correct answer and it gives good explanations.
Answer:
Step-by-step explanation:
1234
Answer:
With a 0.01 significance level and samples of 50 and 40 cofee drinkers, there is enough statistical evidence to state that the mean daily consumption of regular-coffee drinkers is less than that of decaffeinated-coffee drinkers.
The test is a one-tailed test.
Step-by-step explanation:
To solve this problem, we run a hypothesis test about the difference of population means.

The appropriate hypothesis system for this situation is:

Difference of means in the null hypothesis is:


![$$The calculated statistic is Z_c=\frac{[(4.35-5.84)-0]}{\sqrt{\frac{1.20^2}{50}+\frac{1.36^2}{40}}}=-5.43926\\p-value = P(Z \leq Z_c)=0.0000\\\\](https://tex.z-dn.net/?f=%24%24The%20calculated%20statistic%20is%20Z_c%3D%5Cfrac%7B%5B%284.35-5.84%29-0%5D%7D%7B%5Csqrt%7B%5Cfrac%7B1.20%5E2%7D%7B50%7D%2B%5Cfrac%7B1.36%5E2%7D%7B40%7D%7D%7D%3D-5.43926%5C%5Cp-value%20%3D%20P%28Z%20%5Cleq%20Z_c%29%3D0.0000%5C%5C%5C%5C)
Since, the calculated statistic
is less than critical
, the null hypothesis should be rejected. There is enough statistical evidence to state that the mean daily consumption of regular-coffee drinkers is less than that of decaffeinated-coffee drinkers.