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Data collection Assignment PDF

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Added on  2021-06-14

Data collection Assignment PDF

   Added on 2021-06-14

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Data collection The current research is aimed to examine the relationship between the climate change and theorganizational structure which are related to the climate change. For the analysis purpose thedata from the 60 firms has been collected. The random sampling method or the non-probabilitymethod of sample selection has been used to extract the sample from the population data set. Thedata was created in the new excel sheet (which is provided separately) and the data cleaningprocess was also completed in excel. The missing values were coded as 999 so that it can beeasily identified. Also the variable which were not relevant to the current study were removedfrom the final data set. After the data cleaning process, the data was imported to SPSS and thedescriptive and inferential analysis was conducted. Data analysis (descriptive) The descriptive statistics of the variable are discussed in this section. For the continuous variablevarious measured of the central tendencies has been included along with other measures such asthe kurtosis and skewness. Among the variables included in this research only the dependentvariable is continuous so the results for the same has been shown in the table below. All othervariables are categorical variables, and the graphical representation of the categorical variableare discussed in the next section.StatisticsEmission (metric ton) NValid34Missing26Mean2853.9791Median.0030Mode.00Std. Deviation16521.51606Variance272960493.002Skewness5.831Std. Error of Skewness.403Kurtosis33.999Std. Error of Kurtosis.788Minimum.00Maximum96356.00Percentiles25.000050.0030754.8425Table 1 Results from the descriptive statistics As shown in the table above the mean value for the dependent variable (emission of carbon) is2853.97 and the standard deviation for the same is 16521. This shows that the data points are far
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from the mean value and there is high variation in the data set. The high variation is may bebecause the firms from different sectors are included in the data set. The firms in themanufacturing are expected to have more carbon emission as compared to the firms in theservice sector. The minimum and the maximum value also indicates that the carbon emission isvery different among the firms. Skewness The results from the skewnes shows that variable is less skewed or the emission of carbon is lessfor most of the firms. If the data was normally distributed more data points lies near the meanvalue. The skweness value of 5.81 also suggest the same.The descriptive results for the categorical variable has been shown in terms of the pie chart as thenumerical presentation are not very appropriate for the categorical variables.
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5%7%7%7%10%13%25%27%CountryArgentinaBermudaColombiaIsraelMexicoNew ZealandSwitzerlandotherFigure 1 Results from the descriptive statistics based on countriesThe results from the country show that most of the firms are either developed or developingcountries. The highest proportion of countries are from Switzerland followed by the firms inNew Zealand. 5%28%55%12%Highest responsibility other managerSenior managerBoardothersFigure 2 Results from the descriptive statistics for highest responsibility Another important variable included in the data set is to examine who have the highestresponsibility of decision making on climate change in the selected firms. Results shows that formost of the firm the board is responsible for all the decisions related to climate change in thefirm.
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