Just differentiate it with time or with whatever respect you want ! mainly it is time !
Answer:
- Q1. 42 liters
- Q2. Php. 330
Step-by-step explanation:
Question 1
<u>Use ratios to solve:</u>
- 12/100 = x/350
- x = 12*350/100
- x = 42 liters
Question 2
- 1 basket → 5 1/2 kg ⇒ 2 baskets → 2(5 1/2) = 11 kg
- 1 kg → 30 ⇒ 11 kg → 11*30 = 330
Mutya earned Php. 330
5t = 25+2r
t = (25+2r)/5 or
t = 5 + (2/5)r
Answer:
x-intercepts = 1,2, and 4, y-intercept = -8
Step-by-step explanation:
x^3 - 7x^2 - 14x - 8 in factored form is equal to (x-1)(x-2)(x-4).
Solving for x-intercepts:
- We are actually able to solve for all x-intercepts without the given factor. But since we are given one of the factors, our job becomes much easier.
- Using synthetic division, or long division, we factor out the x-intercept 4. Which leaves us with the polynomial x^2 - 3x + 2.
- From here we can separate the polynomial into two binomials.
- x^2 - 3x + 2 = (x-1)(x-2). Giving us all 3 x-intercepts.
- Using Descartes' rules we can identify before even starting the problem how many real x-intercepts there are (Not needed for this problem).
Solving for y-intercept:
- The y-intercept is always the coefficient that does not have any assigned x-variables.
- The coefficient is -8, thus the y-intercept.
- If unsure of the y-intercept, you can always plug in x = 0. Solving for the y-intercept will give you the value of f(0).
- If there is no coefficient, the y-intercept is equal to zero.
Independent variable is the predictor variable which is the height and dependent variable is the response variable which is weight in this scenario.
The square of correlation coefficient gives the coefficient of determination. It is denoted by R² (R squared).
We are given:
R = 0.75
So,
R² = 0.75²
R² = 0.5625
R² = 56.25 %
The coefficient of determination tells how much of the trend of dependent data can be explained by the independent data using the linear regression model. So in the given case, Height can explain 56.25% of the trend in the weight.
