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natita [175]
1 year ago
6

There is a strong positive linear correlation between rainful and the number of apples a tree produces. Does this mean that more

rainfall causes apple trees to produce more fruit
Mathematics
1 answer:
Elan Coil [88]1 year ago
7 0

Answer: Yes, this means more rainfall causes apple trees to produce more fruit.


Step-by-step explanation:

A positive correlation exists when one variable increases as the other variable increases.

Thus, a strong positive linear correlation between rainfall and the number of apples a tree produces definitely means that increase in rainfall will increase the a production of apple fruit.

Thus, a strong positive linear correlation between rainfall and the number of apples a tree produces means that more rainfall causes apple trees to produce more fruit.

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polet [3.4K]

Answer:

Option A) outside

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hope it helps..

have a great day!!!

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1 year ago
Les is measuring the border of her bulletin board. She measures around the entire outside of the bulletin board and finds the di
vagabundo [1.1K]

Answer:

Perimeter.

Step-by-step explanation:

Lee measures around the entire outside of the bulletin board and finds the distance is 32 units.

She is measuring the border of her bulletin board.

The sum of outer covering of any object is called its perimeter. Here, 32 unit shows the perimeter of the bulletin board.

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2 years ago
Justifying an Argument Alissa is analyzing an exponential growth function that has been reflected across the y-axis. She states
Irina18 [472]

The correct answer is C. on edg

6 0
2 years ago
Which system of linear inequalities has the point (2, 1) in its solution set?
AVprozaik [17]
You haven't provided the choices, therefore, I cannot provide an exact answer. However, I will help you with the concept.

For an order pair to be a solution to a system of equations, it has to satisfy <u>BOTH</u> equations. If it satisfies only one equation of the system or satisfy neither of the equations, the, it is not a solutions

<u><em>Examples:</em></u>
<u>System 1:</u>
x = y + 1
2x + 3y = 7
Let's check (2,1)
2 = 1 + 1 ........> equation 1 is satisfied
2(2) + 3(1) = 7 ......> equation 2 is satisfied
<u>(2,1) is a solution to this system</u>

<u>System 2:</u>
y = x + 3
y = x - 1
Let's check (2,1):
1 ≠ 2 + 3 ........> equation 1 isn't satisfied
1 = 2 - 1 ..........> equation 2 is satisfied
<u>(2,1) isn't a solution to this system</u>

<u>System 3:</u>
2y = 9 - 3x
3x + 2y = 9
Let's ceck (2,1):
2(1) ≠ 9 - 3(2) ..........> equation 1 isn't satisfied
3(2) + 2(1) ≠ 9 .........> equation 2 isn't satisfied
<u>(2,1) isn't a solution to this system
</u>
<u><em>Based on the above,</em></u> all you have to do is substitute with (2,1) in the system you have and pick the one where both equations are satisfied

Hope this helps :)
4 0
1 year ago
One of the questions in a study of marital satisfaction of dual-career couples was to rate the statement, "I'm pleased with the
vodka [1.7K]

Answer;

1) The t-distribution is most suitable for this problem.

2) Test statistic = 2.356

3) p-value = 0.0214

4) Alpha = 5% = 0.05

5) The p-value is greater than the significance level at which the test was performed, meaning that we reject the null hypothesis, accept the alternative hypothesis & say that there is enough evidence to conclude that the husbands are happier in dual couple marriages.

Step-by-step Explanation:

Wife's score 2 2 3 3 4 2 1 1 2 4

Husband's score 2 1 2 3 2 1 1 1 2 4

To conduct a hypothesis test at the 5% level to see if the mean difference in the husband's versus the wife's satisfaction level is negative (meaning that, within the partnership, the husband is happier than the wife, we first take the difference in the respomses of wives and husbands

x = (wife's score) - (husband's score)

Wife's score 2 2 3 3 4 2 1 1 2 4

Husband's score 2 1 2 3 2 1 1 1 2 4

Difference | 0 | 1 | 1 | 0 | 2 | 1 | 0 | 0 | 0 | 0

To use the hypothesis test method, we have to make sure that the distribution is a random sample of the population and it is normally distributed.

The question already cleared these two for us that this sample size is randomly selected from the population and each variable is independent from the other.

The question also already explained that the distribution is assumed to be normally distributed.

1) The distribution to use for this test is the t-distribution. This is because the sample size isn't very large and we have no information about the population mean and standard deviation.

For any hypothesis testing, we must first define the null and alternative hypothesis

Since we want to investigate whether the husbands are happier, that the mean difference is negative, that is less than 0,

The null hypothesis, which normally counters the claim to be investigated, would be that there isnt evidence to conclude that the husbands are happier in dual couple marriages. That is, the mean difference in happiness isn't less than 0, that it is equal to or greater than 0.

And the alternative hypothesis, which usually confirms the claim to be tested, is that there is significant evidence to conclude that the husbands are happier in dual couple marriages. That is, the mean difference in happiness is less than 0.

Mathematically, if μ is the mean difference in happiness of wives and husbands,

The null hypothesis is represented as

H₀: μ ≥ 0

The alternative hypothesis is represented as

Hₐ: μ < 0

2) To obtain the test statistic, we need the mean and standard deviation first.

Mean = (sum of variables)/(number of variables) = (5/10) = 0.5

Standard deviation = σ = √[Σ(x - xbar)²/N]

Σ(x - xbar)² = 6(0 - 0.5)² + 3(1 - 0.5)² + (2 - 0.5)² = 1.5 + 0.75 + 2.25 = 4.5

σ = √(4.5/10) = 0.671

we compute the t-test statistic

t = (x - μ)/σₓ

x = sample mean difference = 0.50

μ = 0

σₓ = standard error of the sample mean = (σ/√n)

where n = Sample size = 10,

σ = Sample standard deviation = 0.671

σₓ = (0.671/√10) = 0.2122

t = (0.50 - 0) ÷ 0.2122

t = 2.356

3) checking the tables for the p-value of this t-statistic

Degree of freedom = df = n - 1 = 10 - 1 = 9

Significance level = 5% = 0.05

The hypothesis test uses a one-tailed condition because we're testing only in one direction.

p-value (for t = 2.356, at 0.05 significance level, df = 9, with a one tailed condition) = 0.021441 = 0.0214

4) Alpha = significance level = 5% = 0.05

5) The interpretation of p-values is that

When the (p-value > significance level), we fail to reject the null hypothesis and when the (p-value < significance level), we reject the null hypothesis and accept the alternative hypothesis.

So, for this question, significance level = 0.05

p-value = 0.0214

0.0214 < 0.05

Hence,

p-value < significance level

This means that we reject the null hypothesis, accept the alternative hypothesis & say that there is enough evidence to conclude that the husbands are happier in dual couple marriages.

Hope this Helps!!

5 0
2 years ago
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