Python can be used to implement central of tendencies such as mean, median and mode using the statistic module
The program in Python, where comments are used to explain each line is as follows:
#This imports the statistics module
import statistics
#This defines the function that calculates the mode
def calcMode(myList):
#This prints the mode
print(statistics.multimode(myList))
#This defines the function that calculates the median
def calcMedian(myList):
#This prints the median
print(statistics.median(myList))
#The main method begins here
#This initializes the list
myList = []
#The following iteration gets input for the list
for i in range(10):
myList.append(int(input()))
#This calls the calcMode method
calcMode(myList)
#This calls the calcMedian method
calcMedian(myList)
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299,792,458 metres per second
Answer:
same as above....................
Answer:
In most programming languages "" are required around text.
Explanation:
Python: print("text")
HTML: <p>text</p>
C++: int Main() {
cout << "text" << endl;
}
Lua: print("text")
Answer:
The correct Answer is 0.0571
Explanation:
53% of U.S. households have a PCs.
So, P(Having personal computer) = p = 0.53
Sample size(n) = 250
np(1-p) = 250 * 0.53 * (1 - 0.53) = 62.275 > 10
So, we can just estimate binomial distribution to normal distribution
Mean of proportion(p) = 0.53
Standard error of proportion(SE) = 
= 
= 0.0316
For x = 120, sample proportion(p) = 
= 
= 0.48
So, likelihood that fewer than 120 have a PC
= P(x < 120)
= P( p^ < 0.48 )
= P(z < 
) (z=
)
= P(z < -1.58)
= 0.0571 ( From normal table )
