Answer:
D
Step-by-step explanation:
The equation of a line in point- slope form is
y - b = m(x - a)
where m is the slope and (a, b) a point on the line
here m = - 6 and (a, b) = (- 9, - 3), so
y - (- 3) = - 6(x - (- 9)), that is
y + 3 = - 6(x + 9)
Answer:
Volume of the cylinder is 75.43
Step-by-step explanation:
Volume of Cylinder is
where r is base radius = 2 and h is the height = 6
(22/7) × 2² × 6
= (22/7) × 4 × 6
= (22/7) × 24
= 528/7
= 75.43
n = 2
distribute and simplify left side of equation
50 - 10n - 1 = 29
49 - 10n = 29 ( subtract 49 from both sides )
- 10n = 29 - 49 = - 20
n = = 2
Answer:
The two diameters that separate the top 5% and the bottom 5% are 5.51 and 5.65 respectively.
Step-by-step explanation:
We are given that the diameters of bolts produced in a machine shop are normally distributed with a mean of 5.58 millimeters and a standard deviation of 0.04 millimeters.
<em>Let X = diameters of bolts produced in a machine shop</em>
So, X ~ N()
The z score probability distribution is given by;
Z = ~ N(0,1)
where, = mean diameter = 5.58 millimeter
= standard deviation = 0.04 millimeter
<u>Now, we have to find the two diameters that separate the top 5% and the bottom 5%.</u>
- <u>Firstly, Probability that the diameter separate the top 5% is given by;</u>
P(X > x) = 0.05
P( > ) = 0.05
P(Z > ) = 0.05
<em>So, the critical value of x in z table which separate the top 5% is given as 1.6449, which means;</em>
= 1.6449
= 5.58 + 0.065796 = 5.65
<u />
- <u>Secondly, Probability that the diameter separate the bottom 5% is given by;</u>
P(X < x) = 0.05
P( < ) = 0.05
P(Z < ) = 0.05
<em>So, the critical value of x in z table which separate the bottom 5% is given as -1.6449, which means;</em>
= -1.6449
= 5.58 - 0.065796 = 5.51
Therefore, the two diameters that separate the top 5% and the bottom 5% are 5.51 and 5.65 respectively.
The margin of error is 0.97849
we are given
mean=235
so,
standard deviation =7.5
so,
we know that
ME=2*standard error
and
If confidence level is 95%, then we can multiply by 1.96
so, we can multiply by 2 to get ME
now, we can use marginal error formula
now, we can plug values
and we get