Concentration of cOz in the Atmosphere Levels of carbon dioxide (CO2) in the atm

Question

Concentration of cOz in the Atmosphere Levels of carbon dioxide (CO2) in the atmosphere are rising rapidly, far above any levels ever before recorded. Levels were around 278 parts per million in 1800, before the Industrial Age, and had never, in the hundreds of thousands of years before that, gone above 300 ppm. Levels are now nearing 400 ppm. Table 1 shows the rapid rise of CO2 concentrations over the last 50 years, also available in CarbonDioxide. We can use this information to predict CO2 levels in different years. Year 1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 CO2 316.91 320.04 325.68 331.08 338.68 345.87 354.16 360.62 369.40 379.76 389.78 Table 1 Concentration of carbon dioxide in the atmosphere Click her for the dataset associated with this question. Dr Pieter Tans, NOAA/ESRL, www.esrl.noaa.gov/gmd/ccgg/trends/, Values recorded at the Mauna Loa observatory in Hawaii. (a) What is the explanatory variable? Year O COz level (b) Use technology to find the correlation between year and CO2 levels. Round yaur answer to three decimal places. the absolute tolerance is +/-0.001 (c) Use technology to calculate the regression line to predict Coz from year Round your answer for the intercept to the nearest integer and your answer for the slope to two decimal places CO2 = Year) (d) Interpret the slope of the regression line, in terms of carbon dioxide concentrations. O The slope tels the predicted Co2 level one year later. O The slope tells the predicted number of yeers for the cO2 level to go up by one. O The slope tells the predicted number of years for the Co2 level to go up by that amount. O The slope tells the predicted change in CO2 level one yeer later.

Explanation / Answer

a) explanatory variable -

In statistics, linear regression is a linear approach for modeling the relationship between a scalar dependentvariable y and one or more explanatory variables(or independent variables) denoted X.

So here year is independent variable. So year is explanatory variable.

b) find correlation between yera and co2 level.

First enter year values in excel coulmn A and co2 level values in B column.Then use excel command to find correlation value.

=CORREL(A1:A11,B1:B11) this will give r = 0.993086

c) Regression equation.

Here we will obtain regression equation by using Excel.Here we have given data for Age and selling price. So first we will determine variables. year = x = independent variable. co2 level = Y = Dependent variable.

1)On the Data tab, in the Analysis group, click Data Analysis.

2). Select Regression and click OK.

3. Select the Y Range (A1:A11). This is the predictor variable (also called dependent variable).

4. Select the X Range(B1:B11). These are the explanatory variables (also called independent variables). These columns must be adjacent to each other.

5. Check Labels.

6. Click in the Output Range box and select cell J11.

7. Check Residuals.

8. Click OK.

we will get output from cell J11 on same page.

we get intercept = -2571.2122 , x variable = 1.47081

so regression equation is co2 level = -2571.2122 + 1.47081 year

d) Interpretation of slope in terms of co2 level

If, for example, the slope is 2, you can write this as 2/1 and say that as you move along the line, as the value of the X variable increases by 1, the value of the Y variable increases by 2

in same way the slope tells the predicated change in co2 level one year later

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