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3 years ago

If two variables were completely correlated, their correlation coefficient would be:

1 answer:

meriva3 years ago

7 0

<span>Pearson's correlation coefficient 'r' measures the degree to which two variables are correlated. The value is between -1 and 1. Negative values correspond to negative correlation (as one variable increases, the other variable decreases) whereas positive values correspond to positive correlation. The larger the absolute value of r, the closer a correlation graph resembles a set of points on the same line. Therefore, if two variables are completely correlated, the correlation value is 1 or -1, depending on whether the correlation is positive or negative.</span>

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Which of the following expressions is INCORRECT given the value for the variable n? Group of answer choices 50 - n = 40, n = 10

Vlad1618 [11]

Answer:

it is 6 + n = 10, n = 1

Step-by-step explanation:

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3 years ago

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Plz I just wanna if my answers are true

Zigmanuir [339]

Answer:

3^2

3^4

3^6

Step-by-step explanation:

9 is actually 3^2, so you have the first one wrong.

The second one is correct, but the third one is not

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3 years ago

The vertex of this parabola is at (2,-4). When the y-value is -3 and the x-value is -3. What is the coefficient of the squared e

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4 years ago

A sample of 900900 computer chips revealed that 76v% of the chips do not fail in the first 10001000 hours of their use. The comp

Sergio039 [100]

Answer:

Null hypothesis: $p=0.78$

Alternative hypothesis: $p \neq 0.78$

$z=\frac{0.76 -0.78}{\sqrt{\frac{0.78(1-0.78)}{900}}}=-1.448$

$p_v =2*P(Z$

So the p value obtained was a very high value and using the significance level given $\alpha=0.05$ we see that $p_v>\alpha$ so we can conclude that we have enough evidence to FAIL to reject the null hypothesis, and we can said that at 5% of significance the proportion of chip that do not fail in the first 1000 hours is not significantly different from 0.78 or 78%.

Step-by-step explanation:

1) Data given and notation

n=900 represent the random sample taken

$\hat p=0.76$ estimated proportion of chips do not fail in the first 1000 hours

$p_o=0.78$ is the value that we want to test

$\alpha$ represent the significance level

z would represent the statistic (variable of interest)

$p_v$ represent the p value (variable of interest)

2) Concepts and formulas to use

We need to conduct a hypothesis in order to test the claim that the true proportion is 0.78:

Null hypothesis: $p=0.78$

Alternative hypothesis: $p \neq 0.78$

When we conduct a proportion test we need to use the z statistic, and the is given by:

$z=\frac{\hat p -p_o}{\sqrt{\frac{p_o (1-p_o)}{n}}}$ (1)

The One-Sample Proportion Test is used to assess whether a population proportion $\hat p$ is significantly different from a hypothesized value $p_o$ .

3) Calculate the statistic

Since we have all the info requires we can replace in formula (1) like this:

$z=\frac{0.76 -0.78}{\sqrt{\frac{0.78(1-0.78)}{900}}}=-1.448$

4) Statistical decision

It's important to refresh the p value method or p value approach . "This method is about determining "likely" or "unlikely" by determining the probability assuming the null hypothesis were true of observing a more extreme test statistic in the direction of the alternative hypothesis than the one observed". Or in other words is just a method to have an statistical decision to fail to reject or reject the null hypothesis.

The significance level assumed for this case is $\alpha=0.05$ . The next step would be calculate the p value for this test.

Since is a bilateral test the p value would be:

$p_v =2*P(Z$

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3 years ago

For which conditions is p ∨ q false?

Gelneren [198K]

Answer:

D)p is false and q is false.

Step-by-step explanation:

This is the case of the disjunction operator. This operator creates a compound statement that:

1. It's true if either simple statement is true

2. It's false if both simple statements are false.

So p and q are statements and the only way the compound statement is false is when both simple statements are false. For instance:

For:

p: "Peter is home"

q: "Charles is home"

The disjunction would look like these two forms:

p v q

Other form to write this is as follows:

Peter is home OR Charles is home.

So the compound statement is false if both Peter and Charles aren't home.

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4 years ago

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