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Carbon Pollution Reduction Scheme

The Carbon Pollution Reduction Scheme (or CPRS) was a cap-and-trade emissions trading scheme for anthropogenic greenhouse gases proposed by the Rudd government, as part of its climate change policy,[1] which had been due to commence in Australia in 2010. It marked a major change in the energy policy of Australia. The policy began to be formulated in April 2007, when the federal Labor Party was in Opposition and the six Labor-controlled states commissioned an independent review on energy policy, the Garnaut Climate Change Review, which published a number of reports. After Labor won the 2007 federal election and formed government, it published a Green Paper on climate change for discussion and comment
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Greenhouse Gas

A greenhouse gas (sometimes abbreviated GHG) is a gas that absorbs and emits radiant energy within the thermal infrared range. Greenhouse gases cause the greenhouse effect[1] on planets. The primary greenhouse gases in Earth's atmosphere are water vapor (H
2
O
), carbon dioxide (CO
2
), methane (CH
4
), nitrous oxide (N
2
O
), and ozone (O3)
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Greenhouse Gas Emission

A greenhouse gas (sometimes abbreviated GHG) is a gas that absorbs and emits radiant energy within the thermal infrared range. Greenhouse gases cause the greenhouse effect[1] on planets. The primary greenhouse gases in Earth's atmosphere are water vapor (H
2
O
), carbon dioxide (CO
2
), methane (CH
4
), nitrous oxide (N
2
O
), and ozone (O3)
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Correlation Coefficient
A correlation coefficient is a numerical measure of some type of correlation, meaning a statistical relationship between two variables.[a] The variables may be two columns of a given data set of observations, often called a sample, or two components of a multivariate random variable with a known distribution.[citation needed] Several types of correlation coefficient exist, each with their own definition and own range of usability and characteristics
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Correlation And Dependence
In statistics, correlation or dependence is any statistical relationship, whether causal or not, between two random variables or bivariate data. In the broadest sense correlation is any statistical association, though it commonly refers to the degree to which a pair of variables are linearly related. Familiar examples of dependent phenomena include the correlation between the height of parents and their offspring, and the correlation between the price of a good and the quantity the consumers are willing to purchase, as it is depicted in the so-called demand curve. Correlations are useful because they can indicate a predictive relationship that can be exploited in practice. For example, an electrical utility may produce less power on a mild day based on the correlation between electricity demand and weather. In this example, there is a causal relationship, because extreme weather causes people to use more electricity for heating or cooling
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