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ivann1987 [24]
3 years ago
7

Mrs Gutierrez ordered 1 cheese pizza, 1 pepperoni pizza, and 1 sausage pizza. Each pizza is cut into 12 pieces. The students are

10/12 of the cheese pizza, 9/12 of the pepperoni pizza, and 3/12 of the sausage pizza. What fraction of all the pizza is left?
Mathematics
1 answer:
OleMash [197]3 years ago
7 0

Answer:

1 whole or 12/12

Step-by-step explanation:

so you go and subtract and you ad what each one equals

                                       10-12=2

                                         9-12=3

                                         3-12=9

                                      ---------------

                                      =  1 whole OR 12/12

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Add up all the values shown:
64+28+52+56 = 200

This result indicates that there are 200 students total.

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Divide the two values (28 and 200) to get...
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The probability as a decimal value is 0.14 which is saying there's a 14% chance of picking someone who goes to both colleges.
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Read 2 more answers
IMPOSSIBLE PLEASE HELP! ALSO MAKE SURE TO WRITE A LET STATEMENT
madam [21]
Q1 :
x + (x+25) = 131
2x + 25 = 131
2x = 131-25
2x = 106
x = 53
53+25 = 78
Therefore, 53+78=131

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x + (x+14) = 58
2x + 14 = 58
2x = 58-14
2x = 44
x = 22
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Therefore, 22+36=58

Q3 :
let ‘b’ be basketball
b + (3+b) = 27
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12 basketballs and 15 footballs were sold on Saturday

Q4 :
let ‘s’ be soup
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hope it helps somehow!

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The effect of a monetary incentive on performance on a cognitive task was investigated. The researcher predicted that greater mo
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Answer:

1) H_0:\mu_5=\mu_{25}=\mu_{50}

2) H_a:\mu_{50}>\mu_{25}>\mu_{5}

3) A Type I error happens when we reject a null hypothesis that is true. In this case, that would mean that the conclusion is that there is evidence to support the claim that the greater the incentive, the more puzzles are solved, but that in reality there is no significant difference.

4) A Type II error happens when a false null hypothesis is failed to be rejected. In this case, that would mean that there is no enough evidence to support the claim that the greater the incentive, the more puzzles are solved, but in fact this is true.

5) The probability of a Type I error is equal to the significance level, as this is the chance of having a sample result that will make the null hypothesis be rejected.

Step-by-step explanation:

As the claim is that the greater the incentive, the more puzzles were solved, the null hypothesis will state that this claim is not true. That is that there is no significant relation between the incentive and the amount of puzzles that are solved. In other words, the mean amount of puzzles solved for the different incentives is equal (or not significantly different):

H_0:\mu_5=\mu_{25}=\mu_{50}

The research (or alternative hypothesis) is that the greater the incentive, the more puzzles were solved. That means that the mean puzzles solved for an incentive of 50 cents is significantly higher than the mean mean puzzles solved for an incentive of 25 cents and this is significantly higher than the mean puzzles solved for an incentive of 5 cents.

H_a:\mu_{50}>\mu_{25}>\mu_{5}

A Type I error happens when we reject a null hypothesis that is true. In this case, that would mean that the conclusion is that there is evidence to support the claim that the greater the incentive, the more puzzles are solved, but that in reality there is no significant difference.

A Type II error happens when a false null hypothesis is failed to be rejected. In this case, that would mean that there is no enough evidence to support the claim that the greater the incentive, the more puzzles are solved, but in fact this is true.

The probability of a Type I error is equal to the significance level, as this is the chance of having a sample result that will make the null hypothesis be rejected.

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