Transcript March 6, 2012 1) Summarizing Measurement Data 2) Analyzing Two Quantitative Variables.

March 6, 2012
1) Summarizing Measurement Data
2) Analyzing Two Quantitative Variables
Title your poster (say what you measured)
Create a line plot that displays your data
Complete the left-side column on the
“Summarizing the Survey” sheet from last
class
Join with another group
Take turns sharing posters.
As your partner group shares their poster,
complete the right side column of the
“Summarizing the Survey” sheet
After both groups have shared, discuss your
observations from the recording sheet
Generate measurement
data by measuring lengths
using rulers marked with
halves and fourths of an
inch. Show the data by
marking a line plot, where
the horizontal scale is
marked off in appropriate
units-whole numbers,
halves, or quarters.

MATH
◦ What prior knowledge and understandings do the
students need for this lesson?

LANGUAGE:
◦ What were the demands on the receptive language
of the students?
◦ How were they required to express their knowledge
and understanding?

SOCIAL SKILLS
◦ What did the students have to do to successfully
participate?
◦ What were the expectations for movement and
interactions?

ORGANIZATION
◦ What did students have to manage?

Read the description of your student and
identify:
Challenges
s/he may
have with the
lesson
demands
Aspects of
this lesson
that may
actually
support the
student,
given his/her
challenges
What else
you may
need to do to
provide the
support
needed by
this student
Kevin
Have him paraphrase the directions
Provide a peer buddy
Work with him to create a readable
checklist of what to do.
Isabelle
Be selective about her group
members
Have her paraphrase/repeat the
directions
Consider a check-off sheet with
“quality indicators” for tasks
completed
Use a self-monitoring check-off
sheet for listening to peers
Danny
Provide a social skills checklist for him to
use to self-monitor
Rehearse how to ask questions when
conducting survey
Rehearse how to participate in groups
Assign a partner
Provide templates to organize the data as
he collects it
Have him verbalize each step
Use graph paper if data is categorical
Melissa
Address vocabulary
Consider terms to pre-teach
Be mindful of using terms consistently
Provide a chart with examples
Ask her to paraphrase directions
Consider rehearsal using sentence starters
That is a good idea because…..
That might not work because….
If we ask that question, people’s
answers might be…
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Would they profit from the teacher
modeling his/her thinking and planning in
each part of the process?
Is there a way to break the task(s) down
further?
Could a peer help?
Would they profit from checklists?
Would they profit from strategy posters?
Distinguish between 2 variables: quantitative
and categorical data
Identify the independent and dependent
variables
Construct a scatterplot
Identify positive, negative, or no association in
a scatterplot.
Investigate patterns of association in bivariate
data.
1. Construct and interpret scatter plots for
bivariate measurement data to investigate
patterns of association between two
quantities. Describe patterns such as
clustering, outliers, positive or negative
association, linear association, and nonlinear
association.
At your table make a list of the different types
of data we have analyzed and what were
some of the primary tools we used to analyze
the data types.
Be as specific as you can.

Categorical
One variable
Bar or Circle Graph
Two Variables
Two way table
Segmented bar Graph
Association
Examples:
One Variable: favorite pizza topping or favorite candidate
for governor
Two variables: size of dog and pass obedience class or
gender and roll tongue
Quantitative
One variable
dot plot, box plot, stem and leaf plot,
histogram
Two variable
Scatterplot
Examples:
One variable: height, IQ, $ in bank
Two variable: Height and weight, arm span and
height
Statistical Questions:
Is there a relationship between where a student
sits in a classroom and how attentive the
student is?
Is there a relationship between the weight of a
car and the number of miles per gallon the
car gets?
Is there a relationship between the population
of a state and the number of area codes?
Is there a relationship between taking an
aspirin and chances of a heart attack?
Is there a relationship between number of TV
sets per capita and life expectancy?
Is there a relationship between taking vitamin
C and getting a cold?
Overarching question:
How can I determine if there is a relationship
between 2 quantitative variables?
Example:
Is there a relationship between height and
wingspan?
What are the 2 variables?
Independent Variable (Explanatory Variable)
The independent variable is typically the
variable representing the value being
manipulated or changed.
Dependent Variable (Response Variable)
The dependent variable is the observed result
of the independent variable being
manipulated.
Identify the independent and dependent
variable in each pair:
1. Miles
per gallon and weight of car
2. Age and height of a person
3. Minutes studied and test score
4. Years of schooling and lifetime earnings
5. Grams of fat and calories in fast food
As the population increases the number of state representatives
increases
As the temp outside increases the age when a baby crawls decreases
As the running time of a movie increases the gross income is hard to predict. (scattered)

For each of the following make a sketch of a
scatterplot and describe the association
1. Miles
per gallon and weight of car
2. Age and height of a person
3. Minutes studied and test score
4. Years of schooling and lifetime earnings
5. Grams of fat and calories in fast food
6. Marriage rate and divorce rate
7. Amount of sun and amount of rain/snow
8. Number of TV sets and life expectancy
Where were you (the more senior of our group)
when the space shuttle challenger exploded
on 1/28/86?
The 25th flight of the National Aeronautics and
Space Administration (NASA) space shuttle
program took off on January 20, 1986. Just
after liftoff a puff of gray smoke could be
seen coming from the right solid rocket
booster. Seventy-three seconds into the
flight, the space shuttle Challenger had
climbed 10 miles into the air and then
exploded into a fireball. All seven astronauts
died.
The cause of the explosion was determined to
be an O-ring failure in the right solid rocket
booster. Cold weather was a contributing
factor.
The Shuttle solid rocket booster is assembled
in three sections. Each joint between sections
has a pair of rubber O-rings (a primary Oring and a secondary O-ring) that are
designed to seal the joint and prevent the
escape of hot gasses.
The following table gives the temperature and
the number of O-ring failures for each of the
previous 24 shuttle flights. The term failure is
used here in a very broad sense, and occurs
whenever there is significant erosion of the
O-rings at a joint or blow-by of the hot
gasses at the joint. Since there are two
rockets, each with three joints, the number of
O-ring failures for a launch is between 0 and
6. Flight number 4 has a missing data point
because the rockets were lost at sea.
1.
1.
Sketch a dot plot for the number of O-ring
failures. What does this plot tell you about
a possible relationship between temperature
and O-ring failure?
Sketch a bar graph that shows the number
of O-ring failures as a function of flight
number. Does this graph given any useful
information on the possible relationship
between temperature and O-ring failure?
1.
Construct a scatterplot for the two variables temperature
and O-ring failures. Does this graph suggest a possible
link between temperature and O-ring failures?
Note: Independent is x and dependent is y
Note: Kids have a difficult time with the scale for the x and y
axis
2. Do you think that the relationship suggested in the
scatterplot can be extrapolated (going beyond the data)
to a temperature of 31º (the approximate temperature
on the day that Challenger was launched)? Discuss the
potential problems with such extrapolation.
Using the data number of TV sets and life
expectancy:
1. Construct
a scatterplot with TV sets as the
independent variable.
2. Describe the association.
3. In your own words what is the relationship
between TV sets and life expectancy.
4. Can we say more TV Sets increases life
expectancy?
Describe a real life situation that would involve
a positive association.
2. Describe a real life situation that would involve
a negative association.
3. Describe a real life situation that would involve
no association.
For each clearly identify the independent and
dependent variables and make a sketch of a
possible scatterplot. Make sure both axis are
labeled.
4. Complete the Area code worksheet.
5. Calories and Life expectancy worksheet.
1.