Alg 2_Unit 1 Stats_Review

Front

What is standard deviation?

Back

Standard deviation is a measure of the amount of variation or dispersion in a set of values. A low standard deviation indicates that the values tend to be close to the mean, while a high standard deviation indicates that the values are spread out over a wider range.

Front

How do you calculate the standard deviation of a data set?

Back

1. Find the mean of the data set. 2. Subtract the mean from each data point and square the result. 3. Find the average of those squared differences. 4. Take the square root of that average.

Front

What does the symbol 'σ' represent in statistics?

Back

The symbol 'σ' represents the standard deviation of a population.

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What is the empirical rule in statistics?

Back

The empirical rule states that for a normal distribution: approximately 68% of the data falls within one standard deviation of the mean, 95% falls within two standard deviations, and 99.7% falls within three standard deviations.

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What is the range of a data set?

Back

The range is the difference between the highest and lowest values in a data set.

Front

How do you find the range of the following scores: 155, 165, 138, 172, 127, 193, 142?

Back

Range = Highest score - Lowest score = 193 - 127 = 66.

Front

What is variance in statistics?

Back

Variance is the average of the squared differences from the mean. It measures how far a set of numbers are spread out from their average value.

Front

What is the difference between population and sample standard deviation?

Back

Population standard deviation (σ) is calculated using all members of a population, while sample standard deviation (s) is calculated using a subset of the population.

Front

What does a standard deviation of 0 indicate?

Back

A standard deviation of 0 indicates that all values in the data set are identical and there is no variation.

Front

What is a normal distribution?

Back

A normal distribution is a probability distribution that is symmetric about the mean, showing that data near the mean are more frequent in occurrence than data far from the mean.