So convert to improper fracitons (improper=x/y where x>y and the current one is mixed where it is in t s/f form) so
40 and 4/5=(40 times 5)/5 and 4/5=200/5 and 4/5=204/5
50 and 7/8=(50 times 8)/8 and 7/8=400/8 and 7/8=407/8
area=legnth times width
legnth =407/8
width=204/5
multiply 407/8 and 204/5
407/8 times 204/5=(407 times 204)/(8 times 5)=83028/40=2075.7 square feet
the answer is 2075.7 ft^2 of seed
Answer:
The inequality that comes from this equation is -2 < x < 0
Step-by-step explanation:
In order to solve this equation, we need to start by solving for the absolute value portion of the equation.
-5l2x + 2l + 7 > -3
-5l2x + 2l > -10
l2x + 2l < 2
Now we need to split the equation into two different portions. One with the absolute value symbol taken away. Then we do it again with the symbol flipped and the answer negated.
2x + 2 < 2
2x < 0
x < 0
And the negated version.
2x + 2 > -2
2x > -4
x > -2
Hi there!
Your question:
Sales fall from 300 per week to 270 per week what's the percentage change?
My answer:
The formula for calculating percent change is as follows:
[(y2 - y1)/y1]*100=your percent change
y2= first value
y1=second value
Plug the numbers in:
[(300-270)/300]*100
[30/300]*100
0.1*100
10
Therefore, the percent change is 10%
Hope this helps! Let me know if it's incorrect so I can fix it:)
The answer to you question is B for number 1 and for 2 it is C. Hope this helps
The linear regression method seeks to predict values of a(n) dependent variable based on values of a(n) independent variable.
According to the statement
we have to explain the linear regression method and explain the way by which this method is used to predict the values.
So, For this purpose we know that the
Linear regression is the most basic and commonly used predictive analysis. Regression estimates are used to describe data and to explain the relationship.
And
Linear regression analysis is used to predict the value of a variable based on the value of another variable. The variable you want to predict is called the dependent variable. The variable you are using to predict the other variable's value is called the independent variable.
from these definitions it is clear that the there is a presence of two types of variables which are dependent and independent variables.
So, The linear regression method seeks to predict values of a(n) dependent variable based on values of a(n) independent variable.
Learn more about Linear regression here brainly.com/question/25987747
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