There isn't any piece of data during Taylor's experiment which can be taken as qualitative. Thus, correct choice is: Option D: None are qualitative.
<h3>What is qualitative data?</h3>
Qualitative data tells about the quality or characteristic. It is tough to express it numerically or not at all expressible numerically. They are usually catagorical.
In contrast, there is quantitative data which can be expressed numerically.
The problem is missing its option, which are:
- mass of the cars
- degree of the ramp incline
- time in seconds
- none are qualitative
Mass can be measured (in kgs, grams etc), degree of inclination can be measured (in radians, degree etc), time can be measured (in seconds, minutes etc).
Thus, there isn't any piece of data during Taylor's experiment which can be taken as qualitative. Thus, correct choice is: Option D: None are qualitative.
Learn more about qualitative and quantitative data here:
brainly.com/question/12929865
Answer:
x = 3.53 ft
y - 3.53 ft
z = 3.53 ft
Step-by-step explanation:
given details
volume = 44 ft^3
let cardboard dimension is x and y and height be z
we know that area of given cardboard without lid is given as
A = xy + 2xy + 2yz
xyz = 44 ft^3
To minimize area we have
A = xy + 2x (44/xy) + 2y(44/xy)
A = xy + (44/y) + (44/x)
we have
................1
..............2
from 1 and 2
xy(y-x) = 0
xy = 0 or y = x
from geometry of probelem
x ≠ 0 and y ≠ 0
so y = x
x^3 = 44
x = 3.53 ft = y
z = 44/xy = 3.53
If you find the discriminant it will tell you the number and types of roots. The discriminant is the value b^2 -4ac.
a = 1
b = 1
c = 1
1^2 - 4*1*1
1-4 = -3
Since this is a negative number there will be 2 complex roots.
Answer:
One-sixth times StartFraction 2 over 1 EndFraction
<span>Defective rate can be expected
to keep an eye on a Poisson distribution. Mean is equal to 800(0.02) = 16,
Variance is 16, and so standard deviation is 4.
X = 800(0.04) = 32, Using normal approximation of the Poisson distribution Z1 =
(32-16)/4 = 4.
P(greater than 4%) = P(Z>4) = 1 – 0.999968 = 0.000032, which implies that
having such a defective rate is extremely unlikely.</span>
<span>If the defective rate in the
random sample is 4 percent then it is very likely that the assembly line
produces more than 2% defective rate now.</span>
