The measure of an angle is 4 degrees less than the measure of its complementary angle.What is the measure of each angle?
2 answers:
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Answer:
b. the results are unlikely to have occurred by chance.
Correct when we say significant means that the difference between the hypothetical correlation coefficient of 0 and the real correlation coefficient are large enough to conclude the significant result and not just by chance.
Step-by-step explanation:
When we want to analyze of two variables present significant correlation usually we use the following system of hypothesis:
Null hypothesis:
Alternative Hypothesis:
And when we conduct the test if we conclude that we have a significant relationship that means, we have enough evidence to conclude that the correlation coefficient is different from 0 at some significance level . Let's analyze one by one the possible options:
a. the finding has no mathematical validity.
False, we are conducting an hypothesis test, that procedure present validity always.
b. the results are unlikely to have occurred by chance.
Correct when we say significant means that the difference between the hypothetical correlation coefficient of 0 and the real correlation coefficient is large enough to conclude the significant result and is not just by chance.
c. there is a cause-and-effect relationship between the two variables.
False, we can't analyze causal relationships with the correlation coefficient.
d. the finding can be used to generate new theories.
That's False we can't create new theories with this result, we just can conclude that the correlation coeffcient for the population is different from 0, but nothing else.
Using Visual inspection, the model which fits the data in the distribution better is the power function.
The power and linear functions can of the data can both be modeled using technology,
<u>Using Technology</u> :
The power function in the form which models the data is
The linear function in the form which models the data is
- Where A = intercept and B = slope
- From the model, correlation coefficient given by the power and linear models are 0.999 and 0.986 respectively.
- Hence, the power model is a better fit for the data than the linear model.
Therefore, Inspecting the models visually, the power function fits the data better as the points on the curve are closer to the regression line than on the linear model.
Learn more :brainly.com/question/18405415
