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Answer:
There is a 95% chance that values will be within ±2 standard deviations of the mean.
Step-by-step explanation:
Normal Probability Distribution:
Problems of normal distributions can be solved using the z-score formula.
In a set with mean and standard deviation
, the z-score of a measure X is given by:
The Z-score measures how many standard deviations the measure is from the mean. After finding the Z-score, we look at the z-score table and find the p-value associated with this z-score. This p-value is the probability that the value of the measure is smaller than X, that is, the percentile of X. Subtracting 1 by the p-value, we get the probability that the value of the measure is greater than X.
The Empirical Rule states that, for a normally distributed random variable:
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.
In this question:
According to the empirical rule, 95% of the measures are within 2 standard deviations of the mean. So the correct statement is:
There is a 95% chance that values will be within ±2 standard deviations of the mean.
The life expectancies of residents of a country for which the average annual income is $80,000 for the three models are 12309.9352, 172.2436 and 4828.1393
The life expectancies of the models are given as:
--- model 1
--- model 2
--- model 3
Given that the average annual income is $80,000;
We simply substitute 80000 for income in the equations of the three models.
So, we have:
<u>Model 1</u>
<u>Model 2</u>
<u>Model 3</u>
Hence, the life expectancies are 12309.9352, 172.2436 and 4828.1393
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