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Dovator [93]
3 years ago
10

What is the next fraction of 1/3, 2/9, 4/27, 8/81

Mathematics
2 answers:
amm18123 years ago
7 0
24/243 cuz keft side gets doubled and right side gets trippled
Basile [38]3 years ago
5 0
 The answer would be 16/243; since the numerator is being multiplied by 2 every time and the denominator is being multiplied by 3 each time.
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KengaRu [80]

Answer:

2112

Step-by-step explanation:

4752÷36= 132

132×16=2112

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A data set is made up of these values.
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I think that the answe my be b
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Jared has total of 16 coins in his piggy bank consisting of only quarters and dimes the total value of all those coins is $3.10
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The answer to the question

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3 years ago
How to solve f(4) = x^2+7x-22
geniusboy [140]

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2 years ago
The effect of a monetary incentive on performance on a cognitive task was investigated. The researcher predicted that greater mo
riadik2000 [5.3K]

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.

4 0
3 years ago
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