To solve this problem, we can use the empirical rule, also known as the 68-95-99.7 rule, which states that for a bell-shaped distribution:
- Approximately 68% of the observations fall within one standard deviation of the mean
- Approximately 95% of the observations fall within two standard deviations of the mean
- Approximately 99.7% of the observations fall within three standard deviations of the mean
Since the mean is 30 and the standard deviation is 7, we can calculate the number of observations that fall within the range of 44 or higher by calculating the z-score and using the empirical rule.
First, we calculate the z-score for 44:
z = (x - μ) / σ
z = (44 - 30) / 7
z = 2
According to the empirical rule, approximately 95% of the observations fall within two standard deviations of the mean. This means that approximately 5% of the observations fall beyond two standard deviations from the mean.
To calculate the number of observations that are more than 44, we need to calculate the remaining 5% of the observations. We can calculate this using the area under the standard normal curve, which is available in the standard normal distribution table.
Using the standard normal distribution table, we find that the area to the left of z = 2 is approximately 0.9772. This means that the remaining 1 - 0.9772 = 0.0228, or approximately 2.28%, of the observations fall beyond z = 2.
To find the number of observations that corresponds to this percentage, we multiply the number of observations (150) by the percentage (0.0228):
Number of observations = 150 * 0.0228 = 3.42
Rounding to the nearest whole number, we find that approximately 3 observations are more than 44.
Data with 150 observations are drawn from a bell-shaped distribution with a mean of 30 and a standard deviation of 7. Approximately how many observations are more than 44? (Round your answer to the nearest whole number.)
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