Transcript Using Gapminder to explore Bivariate data web

Using Gapminder to
explore Bivariate data
Ricky Pedersen
De La Salle College
About me…
• HoF Mathematics De La Salle College
• 10 Years – still a baby!
• Love my calculus
About De La Salle College…
• Catholic Boys School
• Year 7 to 13
• Pasifika and ESOL
Problems
Low levels of literacy
Difficulty connecting with contexts
Making connections and research
Interactive Task
Talk to the person next to you and find out:
• One thing they hope to gain
• What they do in their school for Bivariate data
What do I hope to achieve by presenting?
Student Work Example 1
Student Work Example 2
Using Gap Minder and other resources…
• http://www.gapminder.org
• http://www.jake4maths.com/
• https://www.stat.auckland.ac.nz/~wild/iNZight/index.php
So how do we assess?
• Assessing as an assignment
• 2 – 3 Lessons of exploring the use of the software
• 4 – 5 Lessons of in class assessment time
• Video assessment?
Interactive Task - Authenticity
Discuss with the person next to you how you
manage authenticity
Student work
I discovered that there was a definite relationship between the children per woman and the life
expectancy of a country. However, upon evaluation, I found that the relationship between
children per woman and life expectancy can be explained by GDP/Income per Person. I identified
that those countries who averaged higher incomes tended to have less children and in turn lived
longer lives. Whether or not this is a coincidence, this could be apparent because GDP is
effecting:
Education: many of the countries who are having more children (perhaps those in third world
countries) are falling victim to a lack of education in appropriate sexual intercourse. For instance,
they may not be educated in using contraception, preventing pregnancy.
Access to health care: if the average income of the country is low, this affects the access to simple
health care services such as being able to see a General Practitioner (Family Doctors) to be
treated for minor illness that may, if given the chance to develop, become seriously harmful to
one’s health (eg death)
Effects the economy: the stock market of a country is also affected by GDP/average income. Bad
economy, lower incomes, less public services available.
Student work
After looking into both the data set for the year 2002, I was able to understand that it is fairly visible that the number
of child per woman (total fertility) can be used in calculating the life expectancy of a country as it shows children with
more siblings tend to have a shorter life spam compared to children with less or no siblings who tend to live longer.
This could be coincidental and to further verify this, I decided to look and see if another variable would explain this
data. Thus I used GDP to further analyse my data in order to find a better relation to my findings. GDP projects in
countries ,children with more siblings are mostly the less economically developed countries which contribute to the
mortality rate statistics as of a shorter life spam compared with countries with higher GDP which are mostly the high
economically developed countries where child mortality rate is low. To support this finding GapMinder world and
Inzight were helpful supporting tools. Even though the data displays relationship between child per woman (total
fertility) and life expectancy as the child per woman (total fertility) increases life expectancy drops. This could be
coincidental therefore I have further explored another variable in order to find a better reason for this relation, thus I
used GDP. By investigating GDP I was able to get a better understanding towards the reason why countries with more
children per woman tend to have a lower life expectancy, this is due to the income of the country rather than on the
basis of child per woman (total fertility) of a country. I conducted a further investigation which revealed countries
with a low life expectancy are the developing countries who have a low economic stability which explains why the
population has a low life expectancy as their social system and health care systems are not as developed as the high
economically developed counties who’s economy is stable with an improved health care and social system allowing
the population to have a longer life expectancy. To conclude, there is a relationship between life expectancy and child
per woman (total fertility), as child per woman increases life expectancy decreases this is more to do with the income
of the country which determines the life expectancy of the country.
Summary
• Easier for students to make connections with
meaningful data
• Think about your own schools context
Task - reflection
What is one thing that you are going to go away
and try?
Final Questions?