Answer:
5.23 LAB: Adjust values in a list by normalizing When analyzing data sets, such as data for human heights or for human weights, a common step is to adjust the data. This can be done by normalizing to values between 0 and 1, or throwing away outliers.
Explanation:
Answer:
Option b (a digitized handwritten signature) would be the right option.
Explanation:
- Another photograph of such a handwritten signature was used to digitally sign transcripts that would be perceived to have become a "digitized signature."
- Those same kinds of signature verification may take a glance official, but they don't protect against widespread fraud, a vital component of every other internet signature.
The latter available options weren’t connected to the type of situation in question. So the response above would be the correct one.
Answer:
weight_pounds=float(input("Enter the weight in pounds:\n"))#taking input of weight.
height_inches=float(input("Enter the height in inches:\n"))#taking input of thye height.
bmi=(weight_pounds/(height_inches**2))*703#calculating the bmi.
print('The body mass index is '+str(bmi))#printing the result.
Ouput:-
Enter the weight in pounds:
207.8
Enter the height in inches
:
72
The body mass index is 28.163395061728398
Explanation:
The above written program is in python.First I have taken input from the user of the weight in pounds then taking input of the height in inches.Then calculating the bmi and storing it in the variable bmi.Then printing the bmi in the end.
Answer:
Distribute - will put all of the layers in a straight line across the image
