Answer:
void mn(int m, int n){
int sum = 0;
int count = 0;
if(m<n){
for(int i = m;i<=n;i++){
sum+=i;
}
}
else{
for(int i = n;i<=m;i++){
sum+=i;
}
}
count = abs(m - n)+1;
cout<<"Sum: "<<sum<<endl;
cout<<"Average: "<<(float)sum/count;
}
Explanation:
This line defines the method
void mn(int m, int n){
This initializes sum and count to 0
int sum = 0;
int count = 0;
This checks if m is less than n
if(m<n){
This iterates from m to n and calculates the sum of numbers between this interval
<em> for(int i = m;i<=n;i++){</em>
<em> sum+=i;</em>
<em> }</em>
<em> }</em>
If otherwise,
else{
This iterates from n to m and calculates the sum of numbers between this interval
<em> for(int i = n;i<=m;i++){</em>
<em> sum+=i;</em>
<em> }</em>
<em> }</em>
This calculates the range from m to n using absolute function
count = abs(m - n)+1;
This prints the calculated sum
cout<<"Sum: "<<sum<<endl;
This calculates and prints the average
cout<<"Average: "<<(float)sum/count;
}
<em>See attachment for complete program that includes the main (in c++)</em>
<span>The encapsulation unit on the presentation layer of the OSI model is the Data link layer (2).</span>
Answer:
Explanation:
The following is written in Python and uses exception handling to do exactly as requested. It then goes adding all of the integer values to an array called num_list and finally adding them all together when the function ends.
def in_values():
num_list = []
while True:
try:
num = input("Input non-zero floating point: ")
num = int(num)
if num == 0:
break
else:
num_list.append(num)
except ValueError:
print("No valid integer! Please try again ...")
try:
num = input("Input non-zero floating point: ")
num = int(num)
break
except ValueError:
break
sum = 0
for number in num_list:
sum += number
return sum
A linear regression model is used to show the relationship between variables on a scatter plot
The equation of the linear regression model is:
and the correlation coefficient is 0.8034
<h3>How to determine the equation of the
linear regression</h3>
The question is incomplete. So, I will make use of a dataset that has the following calculation summary (from a graphing calculator)
- Sum of X = 45
- Sum of Y = 83
- Mean X = 4.5
- Mean Y = 8.3
- Sum of squares (SSX) = 82.5
- Sum of products (SP) = 128.5
- The value of R is 0.8034.
The equation of the linear regression model is:

See attachment for the scatter plot
Read more about linear regression model at:
brainly.com/question/26347582