Answer:
each side of the patio measures ft.
Step-by-step explanation:
To me yes.
Algebra is mostly memorization. If you know the formulas and know how to apply it, you should do good.
I say use this. Algebra topics are like building on top each other.
Heart of Algebra:
- Review what the purpose of x in algebra.
- Then learn things like combining like terms, and solving for x.
- Since you know the basics of x, you can then review linear equations( imo, a big content of algebra). Stuff like slope, different linear forms, graphs of linear equations, and mostly linear equation word problems
- Then you can review system of equations. since you know how to manipulate linear equations, etc.
Then move on to other algebra topics dealing with algebra like
- functions, and different types of them
- exponents, and radicals rules
- inequalities.
- sequences.
- These aren't the heart of algebra but study them they are useful and it important to know them.
Since you learned different function rules, we can move on to learning exponetial functions, graphs, and word problems.
Then finally, learn most hard thing in Algebra: Quadratics.
Pratice,practice, and practice and you will pass.
Try to memorize the formulas and know when to apply it.
Good Luck
The unit rate would be 3 trucks per 1 hour you can find this by dividing 18 and 6 by 6
Answer:
T + V = 50
2T + (3/2) * V = 90
2T + 1.5V = 90
T = 50 * 1.5 - 90 * 1 / 1 * 1.5 - 2*1 = 30
V = 1 * 90 - 2 * 50 / 1 * 1.5 - 2 * 1 = 20
Step-by-step explanation:
T = 30
V = 20
Answer:
e) The mean of the sampling distribution of sample mean is always the same as that of X, the distribution from which the sample is taken.
Step-by-step explanation:
The central limit theorem states that
"Given a population with a finite mean μ and a finite non-zero variance σ2, the sampling distribution of the mean approaches a normal distribution with a mean of μ and a variance of σ2/N as N, the sample size, increases."
This means that as the sample size increases, the sample mean of the sampling distribution of means approaches the population mean. This does not state that the sample mean will always be the same as the population mean.
