Given the linear correlation coefficient r and the sample size n, determine the critical values of r and use your finding to state whether or not the given r represents a significant linear correlation. Use a significance level of 0.05. r = 0.543, n = 25

Using the principle of hypothesis testing, the correlation Coefficient is greater than the critical value. Hence, the linear correlation Coefficient value is significant.

Given the Parameters :

Recall :

Decision Region :

Critical value at T0.05, 23 = ±0.396

Comparing the critical value and correlation Coefficient :

Hence, the correlation Coefficient is significant.

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 r represents a significant linear correlation.

Step-by-step explanation:

GIven : Linear correlation coefficient: r = 0.543

Sample size: n= 25

Significance levle:

Degree of freedom : n-2 = 25-2=23

Now, we check r critical value table for value with df = 23 and .

Critical value = ±0.396  [From r critical value table]

Since r = 0.543 > 0.396, that means there is significant linear correlation.

Hence,  r represents a significant linear correlation.

d) by the cross product property, ab^2 = bc multiplied by ad

step-by-step explanation:

we are given

in the given triangle abc

angle a is 90° and segment ad is perpendicular to segment bc

we can see that

triangle(abc) and triangle(abd) are similar because they have common side and same angle (90 degree)

so, triangles(abc) and abd are similar

since, they are similar

so, the ratio of their sides must be equal

we get

now, we can cross multiply

and we get

so, this could be step to prove it