Data Analysis And Inferential Statistics For Carbon Emissions Dataset

Research Problem

Data was obtained from a database that contain all the carbon emissions data for all the countries around the globe. The dataset are categorized for the different industries in different countries working on different sectors of economy. We considered the 2012 data set for three countries; Australia, Belgium and Brazil. There were a total of 218 observations (industries) considered for this study with 80 companies from Australia, 11 companies from Belgium and 127 companies from Brazil. A separate excel file is submitted together with this report.  

The table below presents the descriptive statistics for the numerical data that was collected. The two variables are the carbon intensity and percentage change in carbon emissions in 2012. Results shows that the average carbon emissions for 2012 for the selected companies was 321.51 with the highest recorded emission amount for that year being 13093.78. The lowest emission amount recorded was 0.00 with the standard deviation being 1755.65. In regard to the percentage change the average percentage change was found to be -2.16% with the highest change recorded being 305.33% and the lowest change recorded being -78%. The standard deviation for the percentage change was 29.34.

The results for the skewness and kurtosis for both the intensity and percentage change indicated that the variables are heavily skewed. The fact that the skewness values are greater than positive 3 implies that the variables (intensity and percentage change in intensity) are positively skewed and that they seem to have a number of outliers.

Table 1: Descriptive statistics

	Intensity Save Time On Research and Writing Hire a Pro to Write You a 100% Plagiarism-Free Paper. Get My Paper	% change
N	142.00	222.00
Range	13093.78	383.33
Minimum	0.00	-78.00
Maximum	13093.78	305.33
Mean	321.51	-2.16
Std. Deviation	1755.65	29.34
Variance	3082289.75	860.88
Skewness	6.37	6.21
0.20	0.16
Kurtosis	40.62	60.49
0.40	0.33

As can be seen, most the companies included in the study were from Brazil (58.3%, n = 127) followed by companies from Australia (36.7%n = 80) and the least were from Belgium (5.0%, n = 11).

Table 2: Distribution of companies based on countries

	Frequency	Percent	Valid Percent	Cumulative Percent
Valid	Australia	80	36.7	36.7	36.7
Belgium	11	5.0	5.0	41.7
Brazil	127	58.3	58.3	100.0
Total	218	100.0	100.0

Respondents were asked to where the responsibility regarding the climate change decision inside their organization lies. Results showed that the responsibility regarding the climate change decision inside their organization lies on the board for most of the companies (72%, n = 157) followed by the senior manage (24.3%, n = 53) and lastly form other manager (3.7%, n = 8).

Table 3: Highest responsibility level

	Frequency	Percent	Valid Percent	Cumulative Percent
Valid	Other manager	8	3.7	3.7	3.7
Senior manager	53	24.3	24.3	28.0
Board	157	72.0	72.0	100.0
Total	218	100.0	100.0

In regard to whether the Company offers some kind of motivation in relation to issues surrounding climate change management, which are not limited to targets attainment. Slightly more than half of the companies (50.9%, n = 111) said to offer incentives while 49.1% (n = 107) did not offer some kind of motivation in relation to issues surrounding climate change management. 

Provision of incentives
	Frequency	Percent	Valid Percent	Cumulative Percent
Valid	Yes	111	50.9	50.9	50.9
No	107	49.1	49.1	100.0
Total	218	100.0	100.0

Theoretical Argument and Conceptual Model

Lastly, the survey sought to understand whether the companies have integrated climate change policies in their day-to-day business strategy. 70.4% (n = 152) had integrated climate change policies in their day-to-day business strategy while the rest 29.6% (n = 64) did not have.

Is climate change integrated into your business strategy?
	Frequency	Percent	Valid Percent	Cumulative Percent
Valid	Yes	152	69.7	70.4	70.4
No	64	29.4	29.6	100.0
Total	216	99.1	100.0
Missing	999	2	.9
Total	218	100.0

Inferential statistics was used to test the hypothesis.

The first hypothesis we sought to test is;

H₀: There is no significant difference in the amount of carbon intensity for the companies in the three countries.

H_A: There is significant difference in the amount of carbon intensity for the companies in the three countries.

To test this, a one-way ANOVA was used and tested at 5% level of significance. Results are given below;

ANOVA
Intensity
	Sum of Squares	df	Mean Square	F	Sig.
Between Groups	2458070.402	2	1229035.201	.376	.687
Within Groups	431383697.384	132	3268058.314
Total	433841767.785	134

The p-value is given as 0.687 (a value greater than α = 0.05), this means that the null hypothesis is not rejected. By failing to reject the null hypothesis we conclude that there is no significant difference in the amount of carbon intensity for the companies in the three countries. That is, none of the three countries can be thought to produce more carbon emissions than the other in 2012.

The second hypothesis we sought to test is;

H₀: There is no significant difference in the percentage change in carbon emissions for the companies in the three countries.

H_A: There is significant difference in the percentage change in carbon emissions for the companies in the three countries.

To test this, a one-way ANOVA was used and tested at 5% level of significance. Results are given below;

ANOVA
% change
	Sum of Squares	df	Mean Square	F	Sig.
Between Groups	538.960	2	269.480	.302	.740
Within Groups	185687.185	208	892.727
Total	186226.145	210

Again, the p-value is given as 0.740 (a value greater than α = 0.05), this means that the null hypothesis is not rejected. By failing to reject the null hypothesis we conclude that there is no significant difference in the percentage change in carbon emissions for the companies in the three countries. That is, none of the three countries can be thought to have had a significant change in carbon emissions than the other in 2012.

The third hypothesis we sought to test is;

H₀: There is no significant difference in the amount of carbon intensity for the companies based on the supreme responsibility regarding the climate change decision inside their organization.

H_A: There is significant difference in the amount of carbon intensity for the companies based on the supreme responsibility regarding the climate change decision inside their organization.

To test this, a one-way ANOVA was used and tested at 5% level of significance. Results are given below;

ANOVA
Intensity
	Sum of Squares	df	Mean Square	F	Sig.
Between Groups	3512416.492	2	1756208.246	.539	.585
Within Groups	430329351.293	132	3260070.843
Total	433841767.785	134

Relationships between theoretical constructs

The p-value is given as 0.585 (a value greater than α = 0.05), this means that the null hypothesis is not rejected. By failing to reject the null hypothesis we conclude that there is no significant difference in the amount of carbon intensity for the companies based on the supreme responsibility regarding the climate change decision inside their organization. That is, the individual responsibility level does not affect the company’s carbon emission intensity.

We also sought to test how the supreme responsibility regarding the climate change decision inside their organization affects the percentage change in the carbon emissions for the companies in 2012. The following hypothesis was tested;

H₀: There is no significant difference in the percentage change of the carbon emissions for the companies based on the supreme responsibility regarding the climate change decision inside their organization.

H_A: There is significant difference in the percentage change of the carbon emissions for the companies based on the supreme responsibility regarding the climate change decision inside their organization.

To test this, a one-way ANOVA was used and tested at 5% level of significance. Results are given below;

ANOVA
% change
	Sum of Squares	df	Mean Square	F	Sig.
Between Groups	221.881	2	110.940	.124	.883
Within Groups	186004.264	208	894.251
Total	186226.145	210

The p-value is given as 0.883 (a value greater than α = 0.05), this means that the null hypothesis is not rejected. By failing to reject the null hypothesis we conclude that there is no significant difference in the percentage change of the carbon emissions for the companies based on the supreme responsibility regarding the climate change decision inside their organization. That is, the individual responsibility level does not affect the company’s percentage change in carbon emissions.

Another hypothesis tested was whether there is significant difference in the carbon emission intensity between the companies that offer some kind of motivation in relation to issues surrounding climate change management and those that do not provide. The following hypothesis was tested at 5% level significance using an independent samples t-test.

H₀: There is no significant difference in the carbon intensity emissions for the companies that offer some kind of motivation in relation to issues surrounding climate change management and those that do not provide.

H_A: There is significant difference in the carbon intensity emissions for the companies that offer some kind of motivation in relation to issues surrounding climate change management and those that do not provide. The results are presented in the table below; 

Group Statistics
	Provision of incentives	N	Mean	Std. Deviation	Std. Error Mean
Intensity	Yes	81	323.4760	1749.18341	194.35371
No	54	360.2330	1888.52836	256.99616

Independent Samples Test
	Levene’s Test for Equality of Variances	t-test for Equality of Means
F	Sig.	t	df	Sig. (2-tailed)	Mean Difference	Std. Error Difference	95% Confidence Interval of the Difference
Lower	Upper
Intensity	Equal variances assumed	.084	.772	-.116	133	.908	-36.76	317	-664	591
Equal variances not assumed			-.114	107.635	.909	-36.76	322	-675	602

We performed an independent t-test was in order to compare the average carbon intensity emissions for the companies that offer some kind of motivation in relation to issues surrounding climate change management and those that do not provide. Results showed that the average carbon intensity emissions for the companies that offer some kind of motivation in relation to issues surrounding climate change management and those that do not provide (M = 323.48, SD = 1749.18, N = 81) did not significantly different with the average carbon intensity emissions for the companies that did not offer some kind of motivation in relation to issues surrounding climate change management (M = 360.23, SD = 1888.53, N = 54), t (133) = -0.116, p > .05, two-tailed.

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