How to measure a shoe length millimeter centimenter meter kilometer

Mathematics

1 answer:

Hatshy [7]2 years ago

5 0

Out of those options centimeter because it’s small but not as small as a millimeter is

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Help plz will mark Brainly

irina1246 [14]

Answer:

126 inches

Step-by-step explanation:

If your drawing is on a 1 : 40 scale, to find the scale's height, divide the ride's height by 40.

420 / 40 = 10.5

So the drawing will be 10.5 feet tall.

To convert 10.5 feet to inches, multiply it by 12.

10.5 * 12 = 126 inches

3 0

2 years ago

45% of what number is 63

ollegr [7]

Answer:

140.

Step-by-step explanation:

7 0

3 years ago

The population of kansas city, missouri was 435,000 in 1990 and 482,300 in 2005. if the population is changing linearly, write a

Jlenok [28]

Find the slope of the line connecting (1990,435000) and (2005,482300):

482300-435000 47300
m = ----------------------- = ---------------- = 3153/yr (approx)
2005 - 1990 15 yr

Use the point-slope formula to find the equation of this str. line:

y-435000 = (3153/yr)(x-1990)

The year 2020 is 30 years after 1990. Thus, the expected pop in 2020 is

given by y-435000 = 3153(30) = 94590, so that y = 529590.

4 0

3 years ago

a statistics professor finds that when he schedules an office hour at the 10:30a, time slot, an average of three students arrive

Veseljchak [2.6K]

Answer:

The probability that in a randomly selected office hour in the 10:30 am time slot exactly two students will arrive is 0.2241.

Step-by-step explanation:

Let X = number of students arriving at the 10:30 AM time slot.

The average number of students arriving at the 10:30 AM time slot is, λ = 3.

A random variable representing the occurrence of events in a fixed interval of time is known as Poisson random variables. For example, the number of customers visiting the bank in an hour or the number of typographical error is a book every 10 pages.

The random variable X is also a Poisson random variable because it represents the fixed number of students arriving at the 10:30 AM time slot.

The random variable X follows a Poisson distribution with parameter λ = 3.

The probability mass function of X is given by:

$P(X=x)=\frac{e^{-\lambda}\lambda^{x}}{x!};\ x=0,1,2,3...,\ \lambda>0$