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SOVA2 [1]
2 years ago
5

For problem number four on the paper I’m confused I don’t know how to do the table with decimals can someone please explain how

to

Mathematics
1 answer:
Lostsunrise [7]2 years ago
6 0

Answer:

$7.00

Step-by-step explanation:

2.10 \div 6 = 0.35

4a) 1 oz of coffee is equal to 0.35c, which is consistent with everything in the table.

4b)Knowing this, if we have 20 oz of coffee, and we multiply it by 0.35, we will get how much it costs for this cup.

20*0.35 = 7.00

Hope this makes sense and feel free to ask questions!

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Find the volume: A cone with a diameter of 16cm and a height of 16cm.
soldier1979 [14.2K]
<h2><em>The formula for a cone is in the attachment below. Substitute Pie for 3.14.</em></h2><h2><em>3.14 x 8 x 8 x 16/3 = 1071.78667. You can round this up and you get 1072.33.</em></h2><h2><em></em></h2><h2><em>Final Answer: 1072.33cm^3</em></h2><h2><em>Hope this helps and have a nice day! o/</em></h2>

6 0
3 years ago
An automobile manufacturer is considering using robots for part of its assembly process. Converting to robots is an expensive pr
LenKa [72]

Answer:

(a) The correct option is: <em>H₀</em>: <em>p</em> = 0.02 vs. <em>Hₐ</em>: <em>p</em> < 0.02.

(b) Explained below.

(c) The better value of <em>α</em> will be 0.10.

Step-by-step explanation:

An automobile manufacturer is considering using robots for part of its assembly process only if there is strong evidence that the proportion of defective installations is less for the robots than for human assemblers.

To test whether the proportion of defective installations is less for the robots than for human assemblers use a single-proportion <em>z</em>-test.

(a)

The hypothesis can be defined as:

<em>H₀</em>: The proportion of defective installations is same for both the robots and  human assemblers, i.e. <em>p</em> = 0.02.

<em>Hₐ</em>: The proportion of defective installations is less for the robots than for human assemblers, i.e. <em>p</em> < 0.02.

The alternate hypothesis is the claim or the statement that is being tested.

In this case we need to test whether the proportion of defective installations is less for the robots than for human assemblers or not, so that the manufacturer can decide whether they want to apply the conversion.

Thus, the correct option is:

<em>H₀</em>: <em>p</em> = 0.02 vs. <em>Hₐ</em>: <em>p</em> < 0.02.

(b)

A type I error occurs when we discard a true null hypothesis and a type II error is made when we fail to discard a false null hypothesis.

In this case a type I error will be committed if conclude that the proportion of defective installations is less for the robots than for human assemblers when in fact it is not.

And a type II error will be committed if we fail to conclude that proportion of defective installations is less for the robots than for human assemblers.

(c)

The power of the test is the probability of rejecting a false null hypothesis.

The power of the test sis affected by the significance level of the test (<em>α</em>).

Lesser the significance level of the test the lesser is the power of the test.

If the value of <em>α</em> is reduced from 0.05 to 0.01 then the region of acceptance will increase. This implies that there is low probability of rejecting the null hypothesis even when it is false.

So higher the value of <em>α</em> the higher is the probability of making a correct decision.

Thus, the better value of <em>α</em> will be 0.10.

3 0
3 years ago
If prices increase at a monthly rate of 1.2​%, by what percentage do they increase in a​ year?
bazaltina [42]
1.2% x 12 months (1 year) = 14.4%
6 0
3 years ago
The random variable X is exponentially distributed, where X represents the waiting time to be seated at a restaurant during the
erastova [34]

Answer:

The probability that the wait time is greater than 14 minutes  is 0.4786.

Step-by-step explanation:

The random variable <em>X</em> is defined as the waiting time to be seated at a restaurant during the evening.

The average waiting time is, <em>β</em> = 19 minutes.

The random variable <em>X</em> follows an Exponential distribution with parameter \lambda=\frac{1}{\beta}=\frac{1}{19}.

The probability distribution function of <em>X</em> is:

f(x)=\lambda e^{-\lambda x};\ x=0,1,2,3...

Compute the value of the event (<em>X</em> > 14) as follows:

P(X>14)=\int\limits^{\infty}_{14} {\lambda e^{-\lambda x}} \, dx=\lambda \int\limits^{\infty}_{14} {e^{-\lambda x}} \, dx\\=\lambda |\frac{e^{-\lambda x}}{-\lambda}|^{\infty}_{14}=e^{-\frac{1}{19} \times14}-0\\=0.4786

Thus, the probability that the wait time is greater than 14 minutes  is 0.4786.

7 0
3 years ago
The 10 participants in an experiment had the following reaction times ( in milliseconds ) : 778,783,784,786,790,804,807,810,819,
Nata [24]

Answer:

Mean. It includes all data points.

Step-by-step explanation:

-We first need to calculate the mean, median and mode then compare our values:

#Mean:

\bar x=\frac{1}{n}\sum{x_i}\\\\=\frac{1}{10}\sum{778+783+784+786+790+804+807+810+819+823}\\\\=\frac{1}{10}\times \\\\=798.40

#The median is the middlemost data point in a lsit data:

778,783,784,786,790,804,807,810,819,823

-Since our data points is an even number, the median number is calculated as:

median=\frac{1}2}\sum{5^{th}+6^{th}}\\\\=0.5[790+804]\\\\=797.00

#Mode is the data point with the highest frequency:

-Since there's no number appearing more than once, our set has no mode.

#Since our data set has no outliers and is not a skewed distribution, the mean will be the best measure as it includes all data points

8 0
3 years ago
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