Standard Deviation Flashcard

Front

What is the mean?

Back

The mean is the average of a set of numbers, calculated by adding all the numbers together and dividing by the count of numbers.

Front

How do you calculate the median?

Back

To find the median, arrange the numbers in ascending order and identify the middle number. If there is an even number of observations, the median is the average of the two middle numbers.

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 for a sample?

Back

1. Find the mean of the data set. 2. Subtract the mean from each data point and square the result. 3. Sum all squared results. 4. Divide by the number of data points minus one (n-1). 5. Take the square root of the result.

Front

What is the formula for population standard deviation?

Back

The formula for population standard deviation is: σ = √(Σ(xi - μ)² / N), where μ is the population mean, N is the number of data points, and xi represents each data point.

Front

What is mode in statistics?

Back

The mode is the value that appears most frequently in a data set.

Front

How do you find the mode of a data set?

Back

To find the mode, count how many times each number appears in the data set. The number that appears the most is the mode.

Front

What is the difference between population and sample in statistics?

Back

A population includes all members of a specified group, while a sample is a subset of the population used to represent the group.

Front

What is variance?

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

How do you calculate variance for a sample?

Back

1. Find the mean of the sample. 2. Subtract the mean from each data point and square the result. 3. Sum all squared results. 4. Divide by the number of data points minus one (n-1).