First we define the varible to use:
x = represent the number of cookies
Cameron:
The amount of cookies he made was:
x
Deyonne:
We can rewrite the amount in different ways:
x + 0.25x
1.25x
Then, the total revenue is:
0.50 * (x + (x + 0.25x))
We rewrite:
0.50 * (x + 1.25x)
0.50 * (2.25x)
Answer:
The following expressions represent possible revenue from the sales:
F. 0.50 (2.25x
C. 0.50 (x + 1.25x)
A. 0.50 [x + (x + 0.25x)]
Answer:
Not factorable with rationable numbers
Step-by-step explanation:
You cannot factor this expression with rationable numbers.
Answer and Step-by-step explanation: Scaterplot is a type of graphic which shows the relationship between to variables. In this question, you want to determine if there is a linear relationship between overhead widths of seals and the weights. So, the hypothesis are:
H₀: no linear correlation;
H₁: there is linear correlation;
In this hypothesis test, to reject H₀, the correlation coefficient r of the data set has to be bigger than the critical value from the table.
With α = 0.05 and n = 6, the critical value is 0.811.
The linear correlation is calculated as:
r = n∑xy - ∑x.∑y / √[n∑x² - (∑x)²] [n∑y² - (∑y)²]
r = 
r = 0.9485
Since r is bigger than the critical value, H₀ is rejected, which means there is enough evidence to conclude that there is linear correlation between overhead widths and the weights.
In the attachments is the scaterplot of the measurements, also showing the relationship.
So you add 7 every time so,
28+7=34
34+7=41
if he continues his pattern he will have done 41 sit-ups on Friday