MGT723 Research Project : Assignment
Added on 2020-05-11
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Running head: RESEARCH PROJECTResearch Project: Hypothesis TestingName of the Student:Name of the University:Author note:
1RESEARCH PROJECTHypothesis testing The purpose of this research paper is to test a hypothesis if it is right or wrong. Ahypothesis represents a particular statement for forecasting. It represents the expectation from astudy. It helps in assessing a situation in the field of research and through data analysis, the resultshould be tested. Depending on the probability value, the hypothesis is ether accepted or rejected(Murphy, Myors and Wolach 2014). The hypothesis is designed through many ways, but it isusually a process of inductive reasoning, where observations results in the formation of a theory.Through many deductive methods, the hypotheses are tested for acceptance or rejection. Thistestifies the result of the research study. Testing of hypothesis always includes one nullhypothesis and an alternative hypothesis. The null hypothesis refers to the situation to be tested.The alternative hypothesis is the opposite result in case the null hypothesis does not hold true(Barr et al. 2013). In this case, the hypothesis to be tested is as follows:H0: there is no significant relationship between an integration of climate change in the businessand voluntary disclosure score on the cdp survey (null hypothesis). H1: there is significant relationship between an integration of climate change in the business andvoluntary disclosure score on the cdp survey. That means H1 is accepted (p value)Here, H0 is the null hypothesis and H1 is the alternative hypothesis. The objective is to find outthe relation between integration of climate change strategy in the business and the voluntarydisclosure score of the businesses on the CDP survey. The survey was conducted to know thestatus of the businesses whether they have integrated any climate change strategy in theirbusinesses and if they are disclosing it.
2RESEARCH PROJECTData analysis Climate change is a big issue in today’s world and it is important to integrate theenvironmental friendly strategy in the businesses for sustainable future. When the businessesvoluntarily disclose about the actions, there is some government incentives. Hence, somebusinesses voluntarily disclose the fact, while some does not to avoid any kind of penalties(Gillson et al. 2013). This research topic is helpful for inferential analysis. The researcher hastaken total of 60 companies for the sampling from a larger population. Among the population,not all companies provided all the data. Hence, last 30 companies with no climate changestrategy in the business and 30 companies with integrated strategies were chosen for the sampleanalysis. The results will be used for inferential data analysis and SPSS will be used for analysis.Inferential data analysis is one type of data analysis process to test a hypothesis and drawa conclusion about the population on the basis of the sample characteristics. The basis of the alltypes of data analysis is collecting the primary and/or secondary data and performing qualitativeor quantitative analysis on that. Inferential data analysis falls under the category of quantitativedata analysis (Eugster, Hothorn and Leisch 2016). It uses various relevant statistical tools toanalyze the data and inference about the larger population. In this research paper, the researcherwill be using the total data of 60 companies and perform quantitative data analysis on that tocome to a conclusion for the 485 companies. One of the first things in inferential data analysis isto find out the distribution of the data. Depending on the distribution of the data, the type of testneeds to be chosen (Best and Kahn 2016). In statistics, distribution of data is of two types;normal and non-normal. Normal distribution takes the shape of Bell curve. It indicates that thedata is clustered around one center value (Kim 2013). Non-normal distributions have skewness.Non-normal distributions happen due to small size of the sample or unusual responses. Skewed
3RESEARCH PROJECTdata is the main reason for non-normal distribution. The data can be positively or negativelyskewed. When the data is skewed towards the right, it is negatively skewed and when it isskewed towards the left, it is positively skewed. Kurtosis is another attribute of non-normaldistribution. It represents the peakness of the data. It says if the data is too peaked or too flat(Vdorhees 2017). Discussion Data was collected on name, account number, country, Ticker symbol, ISIN, GICSsector, 2015 Response status, 2015 disclosure score public, 2015 voluntary disclosure score andif the climate change strategy is integrated in the business. Majority of the data are stringvariables. The relation between disclosure score and integration of the climate change strategyneeds to be tested using scientific tools. Firstly, the researcher has conducted a descriptiveanalysis separately on the datasets of 30 companies for each response. He has taken the last 30companies for both the positive and negative response for the integration of the climate changestrategy. YesMean92.13559322Standard Error1.474200023Median97Mode99Standard Deviation11.32354524Sample Variance128.2226768Kurtosis7.011896627Skewness-2.498590767Range58Minimum42Maximum100Sum5436Count59
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