Exponential growth/decay rule with general function is:<span>y=y(0)<span>e<span>kt</span></span></span>
with k is growth/decay constant rate.
(1) Deer population function
y(0) = 1253
k
= 3%
t
= 6 (years)
y(6) = 1253 . e^(0.03*6) ~ 1500 (deers)
: 1496 deers
(2) Growth factor b is rate 9.5% = 0.095
5 is Your answer,5 factors into 10 but none of the other choices do
Nolur acil lütfen yalvarırım yalvarırım lütfen
Answer: (a)
P - Value = 0.0981 is high, this indicates stronger evidence that we should fail to reject the null hypothesis: H0: pD = pR (There is no significant difference between the proportion of Democrats who plan to vote for the Democratic candidate in the upcoming election and the proportion of Republicans who plan to vote for the Republican candidate in the upcoming election). P - Value = 0.0981 is the probability of obtaining results at least as extreme as the observed results of the Hypothesis Test, assuming that the null hypothesis is correct.
(b)
Since P - Value = 0.0981 is greater than \alpha = 0.05, the difference is not significant. Fail to reject null hypothesis.
(c)
Since in the Hypothesis Test, we have failed to reject null hypothesis, we could have made: Type II Error: Failure to reject a false null hypothesis. One potential consequence of this error is as follows:
Suppose in reality there is significant difference between the proportion of Democrats who plan to vote for the Democratic candidate in the upcoming election and the proportion of Republicans who plan to vote for the Republican candidate in the upcoming election. But the political pollster wrongly concludes that there is no significant difference between the proportion of Democrats who plan to vote for the Democratic candidate in the upcoming election and the proportion of Republicans who plan to vote for the Republican candidate in the upcoming election. Type II Error is committed in this situation. The consequence of this Type II Error is that the political pollstar will that the political parties are loyal and will not do any follow up work whereas in reality it is not so.
Step-by-step explanation:
got this from chegg!!!
Answer:
0.18431525 = 18.4%
Step-by-step explanation:
General Formula :
total trials Cn⋅p(success)^n⋅p(fail)^total−n
1198144* (.0218)^3 * (1-.0218)^191
