A collection of paired data consists of the number of years that students have studied Spanish and their scores on a Spanish lan
guage proficiency test. A computer program was used to obtain the least squares linear regression line and the computer output is shown below. Along with the paired sample data, the program was also given an x value of 2 (years of study) to be used for predicting test score. What percentage of the total variation in test scores can be explained by the linear relationship between years of study and test scorch? Are both of coefficients of regression statistically significant?
1 answer:
Complete Question
The complete question is shown on the first uploaded image
Answer:
The percentage is 83%
Step-by-step explanation:
Generally R-Sq is known as the coefficient of determination and from the question the value is 83% and this R-Sq defines the total variation in test scores can be explained by the linear relationship between years of study and test scores
So 83 % of the total variation in test scores is unexplained by the linear relationship between years of study and test scores
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Answer:
E. 0.11
Step-by-step explanation:
We have these following probabilities:
A 10% probability that a person has the flu.
A 90% probability that a person does not have the flu, just a cold.
If a person has the flu, a 99% probability of having a runny nose.
If a person just has a cold, a 90% probability of having a runny nose.
This can be formulated as the following problem:
What is the probability of B happening, knowing that A has happened.
It can be calculated by the following formula
Where P(B) is the probability of B happening, P(A/B) is the probability of A happening knowing that B happened and P(A) is the probability of A happening.
In this problem, we have that:
What is the probability that a person has the flu, given that she has a runny nose?
P(B) is the probability that a person has the flu. So P(B) = 0.1.
P(A/B) is the probability that a person has a runny nose, given that she has the flu. So P(A/B) = 0.99.
P(A) is the probability that a person has a runny nose. It is 0.99 of 0.1 and 0.90 of 0.90. So
What is the probability that this person has the flu?
The correct answer is:
E. 0.11
Using the Empirical Rule, it is found that:
- a) Approximately 99.7% of the amounts are between $35.26 and $51.88.
- b) Approximately 95% of the amounts are between $38.03 and $49.11.
- c) Approximately 68% of the amounts fall between $40.73 and $46.27.
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The Empirical Rule states that, in a <em>bell-shaped </em>distribution:
- Approximately 68% of the measures are within 1 standard deviation of the mean.
- Approximately 95% of the measures are within 2 standard deviations of the mean.
- Approximately 99.7% of the measures are within 3 standard deviations of the mean.
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Item a:
Within <em>3 standard deviations of the mean</em>, thus, approximately 99.7%.
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Item b:
Within 2<em> standard deviations of the mean</em>, thus, approximately 95%.
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Item c:
- 68% is within 1 standard deviation of the mean, so:
Approximately 68% of the amounts fall between $40.73 and $46.27.
A similar problem is given at brainly.com/question/15967965