34, 36, 43, 46, 47, 48, 48, 52, 53, 54
Box And whisker Plot
I Don't Understand these at all can someone Explain without totally giving me the answer?
http://ellerbruch.nmu.edu/cs255/jnord/boxplot.html
Ty! :)
Certainly! A box and whisker plot is a visual representation of a set of data that helps us understand the distribution and key characteristics of the data. To create a box and whisker plot, you need to follow these steps:
1. Arrange the data in ascending order: In your case, the data is already given in ascending order: 34, 36, 43, 46, 47, 48, 48, 52, 53, 54.
2. Determine the median: Find the middle value of the dataset. If the number of data points is odd, the median is the value exactly in the middle. If the number of data points is even, the median is the average of the two middle values.
3. Find the first quartile: The first quartile (Q1) represents the median of the lower half of the data. To find Q1, divide the data into two halves, and find the median of the lower half.
4. Find the third quartile: The third quartile (Q3) represents the median of the upper half of the data. To find Q3, divide the data into two halves, and find the median of the upper half.
5. Calculate the interquartile range (IQR): The IQR is the difference between Q3 and Q1. It measures the spread of the middle 50% of the data.
6. Identify any outliers: Outliers are data points that are significantly different from the rest of the data. They can be identified using a specific formula, which compares the values to the IQR.
7. Create the plot: On a number line, draw a horizontal axis and mark the lowest and highest data values. Draw a box from Q1 to Q3, with a horizontal line inside representing the median. Add "whiskers" (vertical lines) extending from Q1 and Q3 to the minimum and maximum values that are not outliers. Finally, mark any potential outliers using dots or asterisks.
By following these steps, you should be able to create a box and whisker plot for the given data set. Remember that the plot provides a visual summary of the data, including measures of central tendency (median) and dispersion (IQR), while also allowing you to identify potential outliers.