The probability that it also rained that day is to be considered as the 0.30 and the same is to be considered.
<h3>
What is probability?</h3>
The extent to which an event is likely to occur, measured by the ratio of the favorable cases to the whole number of cases possible.
The probability that the temperature is lower than 80°F and it rained can be measured by determining the number at the intersection of a temperature that less than 80°F and rain.
So, This number is 0.30.
Hence, we can say that it was less than 80°F on a given day, the probability that it also rained that day is 0.30.
To learn more about the probability from the given link:
brainly.com/question/18638636
The above question is incomplete.
The conditional relative frequency table was generated using data that compared the outside temperature each day to whether it rained that day. A 4-column table with 3 rows titled weather. The first column has no label with entries 80 degrees F, less than 80 degrees F, total. The second column is labeled rain with entries 0.35, 0.3, nearly equal to 0.33. The third column is labeled no rain with entries 0.65, 0.7, nearly equal to 0.67. The fourth column is labeled total with entries 1.0, 1.0, 1.0. Given that it was less than 80 degrees F on a given day, what is the probability that it also rained that day?
#SPJ4
Answer:
3n^2+9+5n^4+55n
Step-by-step explanation:
Steps
$\left(3n^2+9+5n^4-3n\right)+\left(-9n\left(-7\right)-5n\right)$
$\mathrm{Remove\:parentheses}:\quad\left(a\right)=a,\:-\left(-a\right)=a$
$=3n^2+9+5n^4-3n+9n\cdot\:7-5n$
$\mathrm{Add\:similar\:elements:}\:-3n-5n=-8n$
$=3n^2+9+5n^4-8n+9\cdot\:7n$
$\mathrm{Multiply\:the\:numbers:}\:9\cdot\:7=63$
$=3n^2+9+5n^4-8n+63n$
$\mathrm{Add\:similar\:elements:}\:-8n+63n=55n$
$=3n^2+9+5n^4+55n$
Answer:
1. 50 * 1,000 = 50,000
2. 49,001 + 999 = 50,000
3. 5 * 10,000 = 50,000
4. 100,000/2 = 50,000
5. 20,000 + 30,000 = 50,000
6. 50,000/1 = 50,000
7. 90,000 - 40,000 = 50,000
8. 10 + 49,990 = 50,000
9. 5,000 * 10 = 50,000
10. 1,000,000/20 = 50,000
Answer:
Since we extract n elements in total, the algorithm for the running time for K sorted list is O (n log k+ k) = O (n log k)
Step-by-step explanation:
To understand better how we arrived at the aforementioned algorithm, we take it step by step
a, Construct a min-heap of the minimum elements from each of "k" lists.
The creation of this min-heap will cost O (k) time.
b) Next we run delete Minimum and move the minimum element to the output array.
Each extraction takes O (log k) time.
c) Then insert into the heap the next element from the list from which the element was extracted.
Now, we note that since we extract n elements in total, the running time is
O (n log k+ k) = O (n log k).
So we can conclude that :
Since we extract n elements in total, the algorithm for the running time for K sorted list is O (n log k+ k) = O (n log k)
The answer is 49 i think.
