For this class exercise, we are looking into how we can use simple graphs and charts to represent data and understand relationships between different data better.
We usually use a simple co-relation efficient to talk about relationship between data.
It is a simple qualitative approach that gives people an idea of the strength of the relationship between 2 different sets of data.
The degree of the relationship (positive or negative) can be quantified by calculating the R ( correlation coefficient).
Excel provides a very quick way of calculating the "line of best fit" to allow us to see the R value very fast.
A "R value" that is close to 1 means there is a strong positive relationship between the sets of data. As X increase, Y also increase.
A "R value" that is close to -1 means there is a strong negative relationship between the sets of data. As X increase, Y decreases.
Pay attention in class as Mrs Lim demonstrates the use of excel for item 1 and 3 in TASK B.
TASK A: THINK TIME:
What happens when you get a value that is close to 0? Discuss!
TASK B: EXCEL TIME (Work in pairs or trios, according to sharing of computers in class)
Download the data file from Espace IH2013 module workbin.
Open the file in Excel.
As a class, we will discuss the best way to represent data to aid the following investigations:
- Co-relation of population size and energy consumption per capita
- Co-relation of GDP per capita and energy consumption per capita
- Comparison of types of countries and their energy consumption per capita
- Comparsion of GDP per capita and energy consumption per capita according to types of countries
Preparation for first lesson in Week 8:
- Discuss the data representations and the implications of what you observe.
- What do the analyse suggest about the distribution of resources?
- How do the implications affect the way these countries tackle global issues on the environment?
Gdrive link: https://docs.google.com/file/d/0B0NH1U79c6yJSDZaNU5kWUNRelE/edit?usp=sharing
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