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Helga [31]
3 years ago
6

Calculate the slope of the line shown on the graph at right?

Mathematics
2 answers:
Darina [25.2K]3 years ago
7 0
1/3 is the slope
Find two points that are on a line then calculate the rise over the run
stich3 [128]3 years ago
5 0
The answer is 1/3

The rise is 2 and the run is 6, so 2/6 or 1/3 is the slope of the graph.
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4 pounds covers434 sq ft how many pounds needed for 6944 square feet
Ivenika [448]

Answer:

You would need 64 pounds.

STEP BY STEP EXPLANATION:

4 pounds covers 434 sq ft

434 goes into 6944, 16 times

16 x 4  = 64

I hope this helps :)

Have a nice day!

6 0
3 years ago
I need this answer quick!​
marshall27 [118]

Answer:

Um we can’t see anything it’s just white

Step-by-step explanation:

3 0
3 years ago
Explain what is meant by confounding. what is a lurking variable? what is a confounding variable?
miss Akunina [59]

Explain what is meant by confounding. what is a lurking variable? what is a confounding variable?

Answer:

A Confounding is the variable that is considered in a research study, and could overall influence the relations between the variables in the study. For example, students wanting to join AP English next semester were told to write a six page essay. When the students turned in their papers and teachers say the difference and grades they believed that the variable was the time that the students handed in the paper. They thought that if the student handed in their paper later than another student that they would receive a lower score, but this was not the case. When asking the students how they prepared for the paper, students replied with different answers. Those who outlined and used other literature for reference scored much higher than those who only used prior knowledge to write their essays. In this study, the lurking variable would be the presence of an outline.

Lurking variable: A variable that is not considered in a research study that could influence the relations between the variables in the study

Confounding variable: A variable that is considered in a research study that could influence the relations between the variables in the study

To Know more about Confounding Variable

brainly.com/question/28481575

6 0
2 years ago
Read 2 more answers
Anthony wanted to get a job after school. His
Leto [7]
$8 per hour
Work for 4 hours a day so
$8x 4 =32
So he make $32 a day
4 0
3 years ago
Read 2 more answers
The maximum acceptable level of a certain toxic chemical in vegetables has been set at 0.4 parts per million (ppm). A consumer h
Elodia [21]

Answer:

Null hypothesis : \mu \leq 0.4

Alternative hypothesis: \mu >0.4

And for this case a type of error I for this case would be reject the null hypothesis that the population mean is lower or equal than 0.4 when actually is true.

A Type I error would occur if, in fact, μ ≤ 0.4 ppm, but the results of the sampling lead to the conclusion that μ > 0.4 ppm

Step-by-step explanation:

Previous concepts

A hypothesis is defined as "a speculation or theory based on insufficient evidence that lends itself to further testing and experimentation. With further testing, a hypothesis can usually be proven true or false".  

The null hypothesis is defined as "a hypothesis that says there is no statistical significance between the two variables in the hypothesis. It is the hypothesis that the researcher is trying to disprove".  

The alternative hypothesis is "just the inverse, or opposite, of the null hypothesis. It is the hypothesis that researcher is trying to prove".  

Type I error, also known as a “false positive” is the error of rejecting a null  hypothesis when it is actually true. Can be interpreted as the error of no reject an  alternative hypothesis when the results can be  attributed not to the reality.  

Type II error, also known as a "false negative" is the error of not rejecting a null  hypothesis when the alternative hypothesis is the true. Can be interpreted as the error of failing to accept an alternative hypothesis when we don't have enough statistical power

Solution to the problem

For this case we are trying to check the following hypothesis:

Null hypothesis : \mu \leq 0.4

Alternative hypothesis: \mu >0.4

And for this case a type of error I for this case would be reject the null hypothesis that the population mean is lower or equal than 0.4 when actually is true.

A Type I error would occur if, in fact, μ ≤ 0.4 ppm, but the results of the sampling lead to the conclusion that μ > 0.4 ppm

7 0
4 years ago
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