Answer:
see below
Step-by-step explanation:
We can use point slope form
y - y1 = m(x-x1)
where m is the slope and ( x1,y1) is a point on the line
y-12 = 3(x-12)
If we want it in slope intercept form
Distribute
y-12 = 3x-36
Add 12 to each side
y-12+12 = 3x-36+12
y = 3x-24
ANSWER
As given in question
plant’s height = 37 centimeters
it grows at a rate of 0.004 centimeter per hour of sunlight
Andrea conducts a science experiment and observes that the height of a plant depends on the amount of sunlight it receives.
the number of hours of sunlight = s
Than the equation become in the form
f(s) = 0.004s + 37
this equation shows the height of the plant .
Hence proved
Answer:
<em> (1). x = 14 ; (2). 70°</em>
Step-by-step explanation:
<em>(1).</em> m∠ACD = m∠A + m∠B
6x + 2 = (2x + 1) + (3x + 15)
6x - 5x = 14
<em>x = 14</em>
<em>(2).</em> m∠ABC = 180° - m∠CBD = 140°
<em>m∠A</em> = m∠C = 140° ÷ 2 = <em>70°</em>
Answer:
approximately Normal, mean 8.1, standard deviation 0.063.
Step-by-step explanation:
Previous concepts
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".
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".
Let X the random variable weights of 8-ounce wedges of cheddar cheese produced at a dairy. We know from the problem that the distribution for the random variable X is given by:
We take a sample of n=10 . That represent the sample size.
What can we say about the shape of the distribution of the sample mean?
From the central limit theorem we know that the distribution for the sample mean
is also normal and is given by:
approximately Normal, mean 8.1, standard deviation 0.063.