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Verdich [7]
3 years ago
7

PLZ ASAP MARK BRAINILEST Josiah conducts an experiment that has 4 possible outcomes. Sally conducts an experiment that has 10 po

ssible outcomes. The students conduct 50 trials each. Which statement best compares the two experiments?
Josiah’s results are more likely to be close to the predicted results because he had a smaller number of possible outcomes.
Sally’s results are more likely to be close to the predicted results because she had a larger number of possible outcomes.
Josiah and Sally have the same likelihood of the experimental results being close to the predicted results because they used the same number of trials.
Josiah and Sally have the same likelihood of the experimental results being close to the predicted results because the outcome of either experiment is unrelated to the outcome of the other experiment.
Mathematics
2 answers:
expeople1 [14]3 years ago
8 0

Answer:

Its A

Step-by-step explanation:

Rina8888 [55]3 years ago
3 0

Answer:Josiah's results are more likely to be close to the predicted results because he had a smaller number of possible outcomes.

Step-by-step explanation:

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Answer:

The correlation coeffcient for this case was provided:

r =0.934

And this coefficient is very near to 1 the maximum possible value, so then we can interpret that the relationship between the entrace exam score and the grade point average are strongly linearly correlated .

We can also find the r^2 who represent the determination coefficient and we got:

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And the interpretation for this is that a linear model explains appproximately 87.2% of the variability between the two variables

Step-by-step explanation:

Previous concepts

The correlation coefficient is a "statistical measure that calculates the strength of the relationship between the relative movements of two variables". It's denoted by r and its always between -1 and 1.

And in order to calculate the correlation coefficient we can use this formula:  

r=\frac{n(\sum xy)-(\sum x)(\sum y)}{\sqrt{[n\sum x^2 -(\sum x)^2][n\sum y^2 -(\sum y)^2]}}  

The correlation coeffcient for this case was provided:

r =0.934

And this coefficient is very near to 1 the maximum possible value, so then we can interpret that the relationship between the entrace exam score and the grade point average are strongly linearly correlated .

We can also find the r^2 who represent the determination coefficient and we got:

r^2 = 0.934^2= 0.872

And the interpretation for this is that a linear model explains appproximately 87.2% of the variability between the two variables

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