1. Unit 6 Day 2 Vocabulary and Graphs Review
Standards
MCC9-12.S.1D.2 and MCC9-12.S.ID.3

2. Vocabulary
Quantitative Data – Data that can be measured and is reported in a numerical form.
Categorical/Qualitative Data – Data that can be observed but not measured and is sorted by categories.

3. Vocabulary
Center – the middle of your set of data; represented by mean, median, and/or mode.
Spread – the variability of your set of data; represented by range, IQR, MAD, and standard deviation.
Outlier – a piece of data that does not fit with the rest of the data. It is more than 1.5IQRs from the lower or upper quartile, or it is more than 3 standard deviations from the mean.

4. Learning Questions What am I learning today?
How to display data in different types of statistical graphs
How will I show that I learned it?
Show data in different graphical representations and decide which is the best form

5. 5-Number Summary (Review)
A 5-Number Summary is composed of the minimum, the lower quartile (Q1), the median (Q2), the upper quartile (Q3), and the maximum.
These numbers discuss the spread of the data and divide the data into 4 equal parts.

6. Box Plot (Review)
From a five-number summary, I can create a box plot on a graph with a scale.
Minimum – left whisker Lower Quartile – left side of box Median – middle of box Upper Quartile – right of box Maximum – right whisker
Each portion of the box plot represents 25% of the data.

7. Box Plot - Example
2, 4, 4, 5, 6, 8, 8, 8, 9, 10, 11, 11, 12, 15, 17 Min: Q1: Med: Q3: Max: Range: IQR:
– 2 = – 5 = 6

8. Interquartile Range: 20 – 6 = 14
Box and Whisker Plot
The numbers below represent the number of homeruns hit by players of the Wheeler baseball team.
2, 3, 5, 7, 8, 10, 14, 18, 19, 21, 25, 28
Q1 = 6
Q3 = 20
Interquartile Range: 20 – 6 = 14 6 12 20

9. Types of Graphs
Depending on the type of data, some graphs are better to display the information than others.

10. Box Plot
A plot for quantitative data showing the minimum, maximum, first quartile, median, and third quartile of a data set; the middle 50% of the data is indicated by a box. Example:

11. Box Plot: Pros and Cons Advantages: Shows 5-point summary and outliers
Easily compares two or more data sets
Handles extremely large data sets easily
Disadvantages:
Not as visually appealing as other graphs
Exact values not retained

12. Dot Plot
A frequency plot for quantitative data that shows the number of times a response occurred in a data set, where each data value is represented by a dot.
Example:

13. Dot Plot: Pros and Cons Advantages: Simple to make
Shows each individual data point
Disadvantages:
Can be time consuming with lots of data points to make
Have to count to get exact total. Fractions of units are hard to display.

14. Histogram
A frequency plot for quantitative data that shows the number of times a response or range of responses occurred in a data set. Ranges should not have overlapping values.
Example:

15. Histogram: Pros and Cons
Advantages:
Visually strong
Good for determining the shape of the data
Disadvantages:
Cannot read exact values because data is grouped into categories
More difficult to compare two data sets

16. Pie Chart
A chart for categorical data that shows the percentage of responses that fell into each category as a fraction of a pie.
Example:

17. Pie Chart: Pros and Cons
Advantages:
Visually strong
Good for comparing the popularity of each category
Disadvantages:
Cannot read exact values because data is represented as proportion instead of number of responses.
Could be skewed comparison if charts have substantially different numbers of responses.

18. Bar Graph
A graph that represents categorical data by the number of responses received in each category. Example:

19. Bar Graph: Pros and Cons
Advantages:
Shows number of each answer
Good for comparing the popularity of each category
Disadvantages:
Graph categories can be reorganized to emphasize certain effects since it resembles a histogram.