Interpreting and Solving Problems of Dot Plot & Box Plot

Front

What is a dot plot?

Back

A dot plot is a statistical chart that consists of data points plotted on a simple scale, where each dot represents one data point.

Front

What is a box plot?

Back

A box plot, or whisker plot, is a standardized way of displaying the distribution of data based on a five-number summary: minimum, first quartile (Q1), median, third quartile (Q3), and maximum.

Front

What does the interquartile range (IQR) represent?

Back

The interquartile range (IQR) represents the range of the middle 50% of a data set, calculated as Q3 - Q1.

Front

How do you interpret the median in a box plot?

Back

The median in a box plot is the line inside the box that divides the data into two equal halves, indicating the middle value of the data set.

Front

What does a skewed distribution indicate?

Back

A skewed distribution indicates that the data points are not symmetrically distributed; they lean towards one side, either left (negative skew) or right (positive skew).

Front

What is the purpose of using a box plot?

Back

The purpose of using a box plot is to visually summarize the distribution of a data set, highlighting its central tendency, variability, and potential outliers.

Front

What does it mean if a dot plot shows a symmetrical distribution?

Back

If a dot plot shows a symmetrical distribution, it means that the data points are evenly distributed around the center, with similar frequencies on both sides.

Front

What is the significance of the whiskers in a box plot?

Back

The whiskers in a box plot extend from the quartiles to the minimum and maximum values, showing the range of the data outside the interquartile range.

Front

How can you determine outliers in a box plot?

Back

Outliers in a box plot can be determined by identifying points that fall outside 1.5 times the IQR above Q3 or below Q1.

Front

What does it mean if the IQR is large?

Back

A large IQR indicates a wide spread of the middle 50% of the data, suggesting greater variability in the data set.