Reading Graphs

Front

What does it mean if data is skewed right?

Back

If data is skewed right, it means that the tail on the right side of the distribution is longer or fatter than the left side. This indicates that there are a few high values that are pulling the mean to the right.

Front

What does it mean if data is skewed left?

Back

If data is skewed left, it means that the tail on the left side of the distribution is longer or fatter than the right side. This indicates that there are a few low values that are pulling the mean to the left.

Front

What does it mean if data is not skewed?

Back

If data is not skewed, it means that the distribution is symmetrical, and the mean, median, and mode are all approximately equal.

Front

What is a histogram?

Back

A histogram is a type of bar graph that represents the frequency distribution of numerical data. It shows how many data points fall within certain ranges (bins).

Front

What is a line graph?

Back

A line graph is a type of chart that displays information as a series of data points called 'markers' connected by straight line segments. It is often used to show trends over time.

Front

What is the purpose of a pie chart?

Back

A pie chart is used to represent data in a circular graph, where each slice represents a proportion of the whole. It is useful for showing relative sizes of parts to a whole.

Front

What is the mean of a data set?

Back

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

Front

What is the median of a data set?

Back

The median is the middle value of a data set when the numbers are arranged in order. If there is an even number of values, the median is the average of the two middle numbers.

Front

What is the mode of a data set?

Back

The mode is the value that appears most frequently in a data set. A data set may have one mode, more than one mode, or no mode at all.

Front

How do you identify outliers in a data set?

Back

Outliers are values that are significantly higher or lower than the majority of the data. They can be identified using statistical methods, such as the interquartile range (IQR) or z-scores.