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Maru [420]
2 years ago
10

After an office party, 4 1/3 pizzas are left. A day later, there are 1 5/6 pizzas left. How munch pizza was eaten during the day

after the party
Mathematics
1 answer:
IceJOKER [234]2 years ago
8 0

Answer:

15/6 pieces of pizza were eaten. Which is equivalent to 2.5. So 2.5 pizzas were eaten.

Step-by-step explanation:

Just did the math. Convert 4 1/3 to 0/6. So 1 times 2 is 2, and 3 times 2 is 6. Which would give you 4 2/6 which has the same denominator as 1 5/6.

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Following are the prices of 12 tickets listed on the Ticket Racket ticket broker site for a Taylor Swift concert.
Ludmilka [50]

Let me use Python to find the answers

Program.

\tt import\:statistics \:as\:stats

\tt Prices=[75,120,120,145,150,150,150,175,175,200,225,275]

\tt print(stats.mean(Prices))

\tt print(stats.median(Prices))

\tt print(stats.mode(Prices))

Output:;

  • Mean=163.333
  • Median=150.0
  • Mode=150

Console attached

8 0
3 years ago
Read 2 more answers
I need help with this pleasee
Setler [38]
76+20x
factor out 4
4 (19+5x)

so one possible dimensions of the rectangle is 4 by 19+5x
4 0
3 years ago
Read 2 more answers
Please help with 10!
Vladimir [108]

Answer:

x=5

y=4

Step-by-step explanation:

The sides with the 2 bars are equal  so

7x-4 = 31

Add 4 to each side

7x-4+4 = 31+4

7x = 35

Divide each side by 7

7x/7 = 35/7

x =5


The sides with 3 bars are equal

4y+8 = 24

Subtract 8 from each side

4y+8-8 = 24-8

4y = 16

Divide by 4

4y/4 = 16/4

y =4


8 0
3 years ago
If you earn $33 in eight hours at that rate how much would you earn in five hours
Anastaziya [24]
Answer:

11

Step by Step Explanation:

Step 1) Find our how much you make in 5 hours, you make 33 in eight hours so it means 8-3=5

Step 2) So you have 3, simply divide 33 with 3 which equals 11

4 0
3 years ago
Consider the discussion in our Devore reading in this unit involving an important distinction between mean and median that uses
Levart [38]

Answer:

Step-by-step explanation:

A trimmed mean is a method of averaging that removes a small designated percentage of the largest and smallest values before calculating the mean. After removing the specified observations, the trimmed mean is found using a standard arithmetic averaging formula. The use of a trimmed mean helps eliminate the influence of data points on the tails that may unfairly affect the traditional mean.

trimmed means provide a better estimation of the location of the bulk of the observations than the mean when sampling from asymmetric distributions;

the standard error of the trimmed mean is less affected by outliers and asymmetry than the mean, so that tests using trimmed means can have more power than tests using the mean.

if we use a trimmed mean in an inferential test , we make inferences about the population trimmed mean, not the population mean. The same is true for the median or any other measure of central tendency.

I can imagine saying the skewness is such-and-such, but that's mostly a side-effect of a few outliers, the fact that the 5% trimmed skewness is such-and-such.

I don't think that trimmed skewness or kurtosis is very much used in practice, partly because

If the skewness and kurtosis are highly dependent on outliers, they are not necessarily useful measures, and trimming arbitrarily solves that problem by ignoring it.

Problems with inconvenient distribution shapes are often best solved by working on a transformed scale.

There can be better ways of measuring or more generally assessing skewness and kurtosis, such as the method above or L-moments. As a skewness measure (mean ? median) / SD is easy to think about yet often neglected; it can be very useful, not least because it is bounded within [?1,1][?1,1].

i expect to see the optimum point in that process at some value between the mean and median.

3 0
2 years ago
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