Step-by-step explanation:
- tujh vitamin ve j hhhjuhhujuhhgggggggggggg
I believe the correct answer from the choices listed above is the last option. The equation that would represent the height of the sunflower plants would be H = 4w + 36 where the initial height of 36 signifies the b in the equation. and the rate 4 is the slope m.
Hope this answers the question. Have a nice day.
Answer:
a) 0.3125 per hour
b) 2.225 hours
c) 8.9 hours
d) 12.1 hours
e) 80%
Step-by-step explanation:
Given that:
mean time = 3.2 hours, standard deviation (σ) = 2 hours
The mean service rate in jobs per hour (λ) = 2 jobs/ 8 hour = 0.25 job/hour
a) The average number of jobs waiting for service (μ)= 1/ mean time = 1/ 3.2 = 0.3125 per hour
b) The average time a job waits before the welder can begin working on it (L) is given by:

c) The average number of hours between when a job is received and when it is completed (Wq) is given as:

d) The average number of hours between when a job is received and when it is completed (W) is given as:

e) Percentage of the time is Gubser's welder busy (P) is given as:

Answer:
H0: The distribution of players featured on the cards is 0.30 rookies, 0.60 veterans, and 0.10 All-Stars.
Ha: At least one of the proportions in the null hypothesis is false.
Step-by-step explanation:
On this case we need to apply a Chi squared goodness of fit test, and the correct system of hypothesis would be:
H0: The distribution of players featured on the cards is 0.30 rookies, 0.60 veterans, and 0.10 All-Stars.
Ha: At least one of the proportions in the null hypothesis is false.
And in order to test it we need to have observed and expected values. On this case we can calculate the Expected values like this



The observed values are not provided. The statistic on this case is given by:

And this statistic follows a chi square distribution with k-1 degrees of freedom on this case k=3, since we have 3 groups.
We can calculate the p valu like this:

And if the p value it's higher than the significance level we FAIL to reject the null hypothesis. In other case we reject the null hypothesis.