Answer:
C. t=$8, s=$12
Step-by-step explanation:
3($8)+4($12)=$72
4($8)+1($12)=$44
where are the numbers am not seeing them
Answer:
p = 0.07
p-hat = 0.035
p0 = 0.07
p-value = 0.003
Step-by-step explanation:
p = population parameter, in this case, the rate of infestations across all trees in the forest
p-hat = test statistic, in this case, the rate of infestations found in the sample of trees, i.e. those in Doug's backyard
p0 = the null hypothesis, in this case, the rate of infestations within the forest is correctly evaluated at 0.07 or 7%
p-value = the likelihood any difference between p and p-hat is down to chance
In this case 0.003 as the p-value means there is only 0.3% probability of our statistic value of 0.035 being down to variability and chance meaning it is 99.7% likely that there is some reason behind this difference;
We would accept the alternative hypothesis which says the current parameter value, 0.07, is in fact incorrect (either too high or too low, in this case, likely too high).
Answer:
Anne is the best hitter as she has the best hitting average of 0.406
Step-by-step explanation:
Anne hits 65 bases out of 160 at - bats.
Beth's betting average = 0.399
Collin's hit = 40%
Now, we need to convert all the three hitting rates into same parameters to compare them with each other.
Average hit rate of Anne = 

⇒The betting average of Anne = 0.406
Now, The hit - rate of Collin = 40%
Converting the percentage rate into decimal, we get the hit rate of Collin
= 
Hence, we get that Hitting Average of :
<u>Anne = 0.406</u>, Beth = 0.3999 and Collin = 0.400
Hence, from the above data Anne is the best hitter as she has the best hitting average of 0.406.
Answer:
Here:
Step-by-step explanation: