Answer:
It allows for Non-linear editing
Answer:
The probability that among three randomly selected Internet users, at least one is more careful about personal information when using a public Wi-Fi hotspot is 0.964
If the survey subjects <em>volunteered</em> to respond , then those with the strongest opinions are most likely respond. The survey sample is then not randomly selected, the survey may have a <em>response bias.</em>
Explanation:
Let P(at least one is more careful about personal information when using a public Wi-Fi hotspot) denote the probability that among three randomly selected Internet users, at least one is more careful about personal information when using a public Wi-Fi hotspot, then we have the equation
P(at least one is more careful about personal information when using a public Wi-Fi hotspot) = 1 - P(none of the selected users is more careful about personal information when using a public Wi-Fi hotspot)
- If 67% of Internet users are more careful about personal information when using a public Wi-Fi, then 33% of them are not.
P(none of the selected users is more careful about personal information when using a public Wi-Fi hotspot) =
≈ 0.036
P(at least one is more careful about personal information when using a public Wi-Fi hotspot) = 1 - 0.036 = 0.964
Answer: a. intrapersonal and short-term goals
Explanation:
Intrapersonal goals are those that we set for ourselves in our minds to accomplish. The students that are finishing their homework after school most probably set that goal in their minds and so meeting it would mean meeting their intrapersonal goals.
Homework is not a long term project but rather a short one that is usually meant to be completed within days. Completing it is therefore a short term goal.
The students who finish their homework after school are therefore accomplishing both their intrapersonal and short-term goals.
Answer:
import re
with open("../../Downloads/Tweets.txt","r", encoding="utf-8") as tweets:
myfile = tweets.readlines()
for item in myfile:
item = item.rstrip()
mylist = re.findall("^RT (.*) ", item)
if len(mylist) !=0:
for line in mylist:
if line.count("#") >=1:
ln = line.split("#")
dm = ln[1]
print(f"#{dm}")
Explanation:
The python source code filters the document file "Tweets" to return all tweets with a hashtag flag, discarding the rest.