SR Unit 2 Final Review

Front

What is a z-score?

Back

A z-score indicates how many standard deviations an element is from the mean. It is calculated as (X - μ) / σ, where X is the value, μ is the mean, and σ is the standard deviation.

Front

How do you interpret percentiles in a data set?

Back

A percentile indicates the relative standing of a value in a data set. For example, being in the 85th percentile means that the value is higher than 85% of the data points.

Front

What is the mean in a normal distribution?

Back

The mean is the average of all data points in a distribution and is the center point of a normal distribution curve.

Front

What does standard deviation measure?

Back

Standard deviation measures the amount of variation or dispersion in a set of values. A low standard deviation means that the values tend to be close to the mean.

Front

What is the total area under a normal distribution curve?

Back

The total area under a normal distribution curve is equal to 1, representing the total probability of all outcomes.

Front

How do you find the 10th percentile in a normal distribution?

Back

To find the 10th percentile, you can use the z-score corresponding to 0.10 in the standard normal distribution and apply the formula: X = μ + (z * σ).

Front

What is the formula for calculating a z-score?

Back

The formula for calculating a z-score is z = (X - μ) / σ, where X is the value, μ is the mean, and σ is the standard deviation.

Front

What does it mean if a value is in the top 22% of a distribution?

Back

If a value is in the top 22%, it means that it is higher than 78% of the values in the distribution.

Front

What is the significance of the mean and standard deviation in a normal distribution?

Back

The mean determines the center of the distribution, while the standard deviation determines the spread or width of the distribution.

Front

How do you calculate the minimum height in a certain percentile?

Back

To calculate the minimum height in a certain percentile, find the corresponding z-score, then use the formula: X = μ + (z * σ).