Answer: 12 weeks
Step-by-step explanation:
343-115=228
228/19=12
Let's solve this problem step-by-step.
STEP-BY-STEP EXPLANATION:
We will be using simultaneous equations to solve this problem.
The sum of angles on a straight line is 180°.
( R ) and ( 2x + 5 ) are both on the same straight line.
Therefore:
Equation No. 1 -
R + 2x + 5 = 180
R = 180 - 2x - 5
R = 175 - 2x
Vertically opposite angles are equivalent to each other.
( R ) is vertically opposite ( 3x + 15 ).
Therefore:
Equation No. 2 -
R = 3x + 15
Substitute the value of ( R ) from the first equation into the second equation to solve for ( x )
R = 3x + 15
175 - 2x = 3x + 15
- 2x - 3x = 15 - 175
- 5x = - 160
x = - 160 / - 5
x = 160 / 5
x = 32
Next we will substitute the value of ( x ) from the second equation into the first equation to solve for ( R ).
Equation No. 2 -
R = 175 - 2x
R = 175 - 2 ( 32 )
R = 175 - 64
R = 111
FINAL ANSWER:
Therefore, the answer is:
R = 111
x = 32
Hope this helps! :)
Have a lovely day! <3
well, it's isosceles so use base angles theorem
the top angle is also x
90 + 2x = 180
subtract 90 from both sides
2x = 90
divide both sides by 2
x = 45 degrees
Answer:
D. No, because the sample size is large enough.
Step-by-step explanation:
The central limit theorem states that "if we have a population with mean μ and standard deviation σ and take sufficiently large random samples from the population with replacement, then the distribution of the sample means will be approximately normally distributed. This will hold true regardless of whether the source population is normal or skewed, provided the sample size is sufficiently large".
Normal distribution, is a "probability distribution that is symmetric about the mean, showing that data near the mean are more frequent in occurrence than data far from the mean".
If the sample size is higher than 30, on this case the answer would be:
D. No, because the sample size is large enough.
And the reason is given by The Central Limit Theorem since states if the individual distribution is normal then the sampling distribution for the sample mean is also normal.
From the central limit theorem we know that the distribution for the sample mean
is given by:
If the sample size it's not large enough n<30, on that case the distribution would be not normal.