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Viktor [21]
3 years ago
13

Please help me I will give you the brain thing and extra points. 5/5 :D

Mathematics
2 answers:
jeyben [28]3 years ago
4 0

Answer: Hey The Answer is C

Step-by-step explanation:

egoroff_w [7]3 years ago
4 0
The Cuh-rect answer is C as in Cuh
Cuhhhhhh
You might be interested in
Verona is solving the equation –3 + 4x = 9. In order to isolate the variable term using the subtraction property of equality, wh
frutty [35]

Answer:

subtract  -3

Step-by-step explanation:

–3 + 4x = 9

Add 3 to each side

This is the same as subtracting -3

-3 + 4x - (-3) = 9 - (-3)

4x = 9 +3

4x = 12

8 0
3 years ago
Read 2 more answers
Given g(x) = -x + 3, solve for x when g(x) = -1.
cluponka [151]

Answer:

4

Step-by-step explanation:

It's ok! This is simple. Simply plug in your given values. Since g(x) = -1, plug that into the equation.

g(x) = -x + 3

g(-1) = -(-1) + 3

=1+3

=4

7 0
3 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
Is 21:15 equivalent to 7:5
Vera_Pavlovna [14]

Answer:

Yes

Step-by-step explanation:

21/3=7

15/3=5

3 0
3 years ago
Read 2 more answers
There are 8 orange candies and 4 blue candies you select one candy eat it and then select another find P(you select first an ora
Savatey [412]
Orange first = 9/13 

Blue next = 4/12 

<span>P(both) = (9/13)*(4/12) </span>
<span>P(both) = 3/13 ~ 0.23</span>
4 0
3 years ago
Read 2 more answers
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