Answer:
There are two ways in which programs ... count-controlled loops; condition-controlled loops ... Sometimes it is necessary for steps to iterate a specific number of times. ... A count-controlled loop is used when the number of iterations to occur is ... the variable 'count' is used to keep track of how many times the algorithm
Explanation:
Answer:
Option C
Explanation:
All of the following are true about data science and big data except No digital data is stored in traditional databases
Reason -
Data generated in current time is of large size and is also complicated. Traditional data bases such as SQL databases etc. are not capable to store data that is changing at a fast pace and has huge volume, veracity, variety and velocity. But big data platforms such as Hadoop can store big data and process it speedily and easily.
When reading difficult content you should- Survey the chapter.
Surveying the chapter allows you to better interpret the literary text and therefore be able to answer the following questions or summarize.
Hope I helped,
-CSX :)
The file that contains full and incremental back-up information for use with the dump/restore utility is <u>/etc/dumpdates.</u>
<u></u>
<h3>What is dump/restore utility ?</h3>
Dump examines files in a filesystem, determines which ones need to be backed up, and copies those files to a specified disk, tape or other storage medium. Subsequent incremental backups can then be layered on top of the full backup.
The restore command performs the inverse function of dump; it can restore a full backup of a filesystem. Single files and directory subtrees may also be restored from full or partial backups in interactive mode.
Learn more about incremental backups
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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)
Read more about similar programs at:
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