How to solve for side

A scuba diver is 240 feet below sea level and descends 50 feet further down to observe the sea life.

taurus [48]

Answer:

The new position is 190 feet below sea

Step-by-step explanation:

240-50=190

8 0

2 years ago

Read 2 more answers

Entertainment Software Association would like to test if the average age of "gamers" (those that routinely play video games) is

lions [1.4K]

Answer:

"30 years or less when, in reality, the average age is more than 30 years"

Step-by-step explanation:

Type I error is produced when conclusion rejects a true null hypothesis.

The null hypothesis is

"The average gamer is more than 30 years old"

(deduced from the wording, not explicitly stated).

Then if the conclusion is "the average gamer is less than or equal to 30 years old" when in reality the average age is more than 30 years, then there is a type I error, since the null hypothesis is rejected.

Answer is D:

"30 years or less when, in reality, the average age is more than 30 years"

8 0

2 years ago

What is the andwer???

djverab [1.8K]

Answer:

3 and 11

Step-by-step explanation:

Given 2 sides with third side x , then

difference of 2 sides < x < sum of 2 sides , that is

7 - 4 < x < 7 + 4

3 < x < 11

Thus the possible values the third side cannot be are 3 and 11

4 0

3 years ago

At the amusement park, Laura paid $6.00 for small cotton candy. Her older brother works at the park, and he told her they mark u

Rudiy27

$2 because 6/%300= 2

3 0

3 years ago

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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