Get Comparing Data Displayed In Box Plots Lesson 11 2 Answer Key

Boxplots can tell you about your outliers and what their values are. They can also tell you if your data is symmetrical, how tightly your data is grouped and if and how your data is skewed.

Boxplots can tell you about your outliers and what their values are. They can also tell you if your data is symmetrical, how tightly your data is grouped and if and how your data is skewed.

When you should use a box plot. Box plots are used to show distributions of numeric data values, especially when you want to compare them between multiple groups. They are built to provide high-level information at a glance, offering general information about a group of data's symmetry, skew, variance, and outliers.

When you should use a box plot. Box plots are used to show distributions of numeric data values, especially when you want to compare them between multiple groups. They are built to provide high-level information at a glance, offering general information about a group of data's symmetry, skew, variance, and outliers.

To compare box side by side box plots: Compare the location of the median to compare the averages of the data. Compare the lengths from whisker to whisker (the range), which is the spread of the data. Compare the lengths of the boxes (the interquartile range), which is the spread of the middle 50% of data.

To compare box side by side box plots: Compare the location of the median to compare the averages of the data. Compare the lengths from whisker to whisker (the range), which is the spread of the data. Compare the lengths of the boxes (the interquartile range), which is the spread of the middle 50% of data.

Guidelines for comparing boxplots Compare the respective medians, to compare location. Compare the interquartile ranges (that is, the box lengths), to compare dispersion. Look at the overall spread as shown by the adjacent values. ... Look for signs of skewness. ... Look for potential outliers.

Guidelines for comparing boxplots Compare the respective medians, to compare location. Compare the interquartile ranges (that is, the box lengths), to compare dispersion. Look at the overall spread as shown by the adjacent values. ... Look for signs of skewness. ... Look for potential outliers.

It is used to compare multiple sets of data describing the same, single variable. It uses separate box plots for each data set. It allows comparisons of the median (center), upper and lower extremes, quartiles, interquartile range (IQR), and range between and among multiple data sets.

It is used to compare multiple sets of data describing the same, single variable. It uses separate box plots for each data set. It allows comparisons of the median (center), upper and lower extremes, quartiles, interquartile range (IQR), and range between and among multiple data sets.

A box and whisker plot—also called a box plot—displays the five-number summary of a set of data. The five-number summary is the minimum, first quartile, median, third quartile, and maximum. In a box plot, we draw a box from the first quartile to the third quartile. A vertical line goes through the box at the median.

A box and whisker plot—also called a box plot—displays the five-number summary of a set of data. The five-number summary is the minimum, first quartile, median, third quartile, and maximum. In a box plot, we draw a box from the first quartile to the third quartile. A vertical line goes through the box at the median.

In its simplest form, the boxplot presents five sample statistics - the minimum, the lower quartile, the median, the upper quartile and the maximum - in a visual display.

In its simplest form, the boxplot presents five sample statistics - the minimum, the lower quartile, the median, the upper quartile and the maximum - in a visual display.

When comparing two box plots, you should make a comment about: The average (the median) – i.e. which is higher/larger on average; The spread or consistency (the interquartile range or IQR) – a greater IQR means that data points are more spread out, and therefore less consistent.

When comparing two box plots, you should make a comment about: The average (the median) – i.e. which is higher/larger on average; The spread or consistency (the interquartile range or IQR) – a greater IQR means that data points are more spread out, and therefore less consistent.

Step 1: Assess the key characteristics. Examine the center and spread of the distribution. ... Step 2: Look for indicators of nonnormal or unusual data. Skewed data indicate that data may be nonnormal. ... Step 3: Assess and compare groups. If your boxplot has groups, assess and compare the center and spread of groups.

Just like histograms, box plots should only be used with continuous or discrete variables. Box plots are similar to histograms in that they both display the distribution of a variable, but box plots make it to more straightforward to identify the actual value of the minimum, Q1, median (Q2), Q3, and maximum.

Step 1: Assess the key characteristics. Examine the center and spread of the distribution. ... Step 2: Look for indicators of nonnormal or unusual data. Skewed data indicate that data may be nonnormal. ... Step 3: Assess and compare groups. If your boxplot has groups, assess and compare the center and spread of groups.

Just like histograms, box plots should only be used with continuous or discrete variables. Box plots are similar to histograms in that they both display the distribution of a variable, but box plots make it to more straightforward to identify the actual value of the minimum, Q1, median (Q2), Q3, and maximum.

Average: In a box plot, the measure of average used is the median. This is represented by the vertical line inside the box. Comparing the medians of two data sets, we can determine in which data set the values are “on average” higher or lower than in the other, or if there is no difference on average.

Average: In a box plot, the measure of average used is the median. This is represented by the vertical line inside the box. Comparing the medians of two data sets, we can determine in which data set the values are “on average” higher or lower than in the other, or if there is no difference on average.