1. Math Alliance Project 4th Stat Session
Analyzing Quantitative Data

2. Review GAISE Statistical problem solving steps:
1. formulate a statistical question
2. design and implement a plan to collect data
analyze the data
interpret the results in the context of the original question

3. Types of Data
Categorical Graphs Bar Graphs Pie Chart

4. Types of Data
Quantitative Graphs Dot plot Stemplot Histogram Boxplot

5. Essential Understanding
Big Idea 1: The common thread in the statistical problem solving process is the focus on recognizing, summarizing and understanding variability in data. The distribution describes the variability in data.
There are various ways to represent and summarize a distribution. These include tables, graphs, and numerical summaries.
Representations for the distribution of data on a single categorical variable include:
Frequency / relative frequency table
Frequency / relative frequency bar graph
Pie chart (circle graph)

6. Essential Understanding
Representations for the distribution of data on a single numerical variable include:
Dot plot
Frequency / relative frequency table
Cumulative Frequency / relative frequency table
Stem and leaf plot
Histogram
Box plot
With numerical data, identify patterns in the variability and describe important features of the distribution including:
Shape of the distribution
Mound, symmetric, skewed, bi-modal
Center of the distribution
Mean, Median, mode
Spread of the distribution
Range, interquartile range, mean absolute deviation, standard deviation

7. Grade 6 Statistics & Probability
Develop understanding of statistical variability.
1. Recognize a statistical question as one that anticipates variability in the data related to the question and accounts for it in the answers. For example, “How old am I?” is not a statistical question, but “How old are the students in my school?” is a statistical question because one anticipates variability in students’ ages.
2. Understand that a set of data collected to answer a statistical question has a distribution which can be described by its center, spread, and overall shape.
3. Recognize that a measure of center for a numerical data set summarizes all of its values with a single number, while a measure of variation describes how its values vary with a single number.

8. Grade 6 Statistics & Probability
Summarize and describe distributions.
4. Display numerical data in plots on a number line, including dot plots, histograms, and box plots.
5. Summarize numerical data sets in relation to their context, such as by:
Reporting the number of observations.
Describing the nature of the attribute under investigation, including how it was measured and its units of measurement.
Giving quantitative measures of center (median and/or mean) and variability (interquartile range and/or mean absolute deviation), as well as describing any overall pattern and any striking deviations from the overall pattern with reference to the context in which the data were gathered.
Relating the choice of measures of center and variability to the shape of the data distribution and the context in which the data were gathered.

9. Essential Understanding
Representations for the distribution of data on a single numerical variable include:
Dot plot
Frequency / relative frequency table
Cumulative Frequency / relative frequency table

10. Activity
Statistical Question: How long are the names of students in our class? Criteria: Population Measurement Variability

11. GAISE Step 2: collect the data
Complete table
Last Name
Length
First Name
Combined length
Hopfensperger 13
Patrick 7 20
Winn 4
Judy 8

12. Gaise Step 3: Analyze the Data
Dotplot (also called a lineplot) Steps to construct a dotplot: Horizontal axis scaled to cover the range of the different name – lengths Read down list and place a (•) or (x) for each length above the appropriate mark

13. Frequency Table Combined Name – Length Frequency 7 3 8 1 9 10 6 11 1210 6 11 12 13 14

14. Reflection
What are the advantages and disadvantages of each type of display? (Dotplot vs. Frequency table) Does one have to be constructed first in order to construct the other?

15. Gaise Step 4: Interpret the results
Original question: How long are the names of students in our class? Write an answer to this question using the dotplot and frequency table to support your findings.

16. Extension
Have you ever completed a form that does not have enough blanks for your entire name? Suppose a form has only 15 blanks for the combined name (first, space, last). How many people in class would be able to enter their entire name?

17. Cumulative Frequency table
Length
Frequency
Cumulative Frequency 7 3 8 1 4 9 10 6

18. Relative Cumulative Frequency table
Length
Frequency
Cumulative Frequency
Relative Cumulative Frequency 7 3 .3 8 1 4 .4 9 10 6
1.00
Total

19. Interpret the results
If we wanted to design a form so that “most” of the students in class would have enough room to write their full name, how long should the form be?

20. Essential Understanding
With numerical data, identify patterns in the variability and describe important features of the distribution including:
Shape of the distribution
Mound, symmetric, skewed, bi-modal

21. Mound, normal, bell-shaped

22. Symmetric, Uniform

23. Skewed

24. Bi-Modal

25. Stemplot
Example of a stem plot Travel Times How many minutes did it take you to get to Gaeslen from your school? Statistical Question? Burger King Data

26. Other examples of stemplots
Students and Basketball players Heights (Navigating book p. 88) Skateboard prices (p. 23 Data Distributions)

27. Activity: How long is a minute?
How good are you at estimating how long a minute is? Partner one: Head down and hand up Leave hand up until you think one minute has passed Partner two: Carefully time and recorded how long your partner kept their hand up

28. Minute Activity
Switch roles Partner two – while timing talk to your partner about school, sports, news, your family Remember to carefully time and record how long your partner has their hand up

29. Back-to- Back Stemplot
Compare estimating one minute between the groups What is the statistical question we are attempting to answer? Construct a back-to-back stemplot to help answer our question.

30. Histograms
A histogram is a graphical display of a frequency distribution of quantitative data using bars of the same width (class interval) and heights dependent on the frequencies.

31. How is a Histogram Made?
Consider the set of values: 3, 11, 12, 19, 22, 23, 24, 25, 27, 29, 35, 36, 37, 45, 49 Construct a frequency table – decide class width
Class Width
Tally
Frequency
0-10 | 1
10-20
| | | 3
20-30
| | | | | | 6
30-40
| | | | 4
40-50
| | 2

32. Reflection Why are there no gaps between the bars in a histogram?

33. Histogram Examples
Burger King Data Migraines Data p. 94 NCTM Navigating through Data Analysis in Grades 6-8

34. Summary
When would each of these be most useful? What are the advantages and disadvantages of each type of display? Dotplot Stemplot Histogram

35. Summary
Purpose is to get a visual display of your data and begin to draw some conclusions about the statistical question. Describe the shape Estimate center and spread