make a line plot for each set of data. Identify any clusters, gaps and outliers.
daily low temperatures
26F, 25F, 24F, 29F, 28F, 21F, 10F
number of stories in town buildings
3, 3, 1, 1, 8, 6, 6, 4, 3, 23, 7, 9
To make a line plot for each set of data and identify any clusters, gaps, and outliers, follow these steps:
1. Daily Low Temperatures:
- Start by setting up a line plot with the vertical axis representing the temperature values and the horizontal axis representing the days.
- Plot each temperature value on the line plot according to its corresponding day.
- Identify any clusters (groupings of temperature values that are close together), gaps (missing temperature values between two consecutive days), and outliers (temperature values that are significantly different from the rest).
2. Number of Stories in Town Buildings:
- Set up a new line plot with the vertical axis representing the number of stories and the horizontal axis representing the buildings.
- Plot the number of stories for each building according to its corresponding position on the horizontal axis.
- Look for any clusters (groupings of buildings with a similar number of stories), gaps (missing buildings between two consecutive positions), and outliers (buildings with an unusually high or low number of stories).
Note: Since there are no specific positions mentioned for the town buildings, the line plot for the number of stories may not provide as much meaningful information as the one for daily low temperatures.
To create a line plot for each set of data, you can follow these steps:
1. Gather the data: For the daily low temperatures, the data points are 26F, 25F, 24F, 29F, 28F, 21F, and 10F. For the number of stories in town buildings, the data points are 3, 3, 1, 1, 8, 6, 6, 4, 3, 23, 7, and 9.
2. Prepare a number line: Draw a horizontal number line that includes all the values in the given data set. For the daily low temperatures, the number line will range from 10F to 29F. For the number of stories, the number line will extend from 1 to 23.
3. Plot the data points: For each data point, mark a dot above the corresponding value on the number line. Repeat this step for all the data points in the given set.
4. Connect the dots: Draw a line connecting all the dots from left to right for each set of data. This will create a line plot that represents the data.
Additionally, while analyzing the line plots, you can identify clusters, gaps, and outliers:
- Clusters: Observe if there are any groups or clusters of data points that are close to each other on the line plot. These clusters indicate that the values within them are similar or have a similar range.
- Gaps: Look for areas on the line plot where there is a significant space or distance between data points. These gaps suggest that there is no data or few data points within that range.
- Outliers: Identify any data points that appear to be significantly different from the other data. These outliers represent values that are either much higher or much lower compared to the rest of the data set.
By examining the line plots, you can easily spot clusters, gaps, and outliers, aiding in the understanding and interpretation of the data.