Analysis Techniques and Statistical Tools Sample Clauses

Analysis Techniques and Statistical Tools. In order to present a picture about the general and physical profiles of the 43 firms interviewed, the quantitative data gathered from the first part of the interviews, is analyzed graphically with the Microsoft Office-Excel 2013 program. These graphs show the general distribution of the interviewed firms of the 4 sector clusters that I defined before, for the following: ⮚ Scale (SME vs. large) ⮚ Annual income ⮚ Number of patents/utility models ⮚ Number of trademarks ⮚ Number of total finished project/product numbers In order to analyze the qualitative data provided by the firms (firm opinions), “NVivo 10 Qualitative Analysis Program” is used. In order to analyze the qualitative data provided by the firms (firm opinions), “NVivo 10 Qualitative Analysis Program” is used. All of the semi-structured interviews conducted with 43 firms, is coded one by one in the Nvivo 10 Analysis Program as a “source” with regard to their sector clusters. With the help of the program, the qualitative data (firm opinions) in each and every source is related to the nodes that I defined as “references”, i.e. as positive or negative opinions. With these relations I can reach to the information that which firm makes positive or negative references to the nodes in its interview (one or more than one reference). After that for each node, the total number of the firms making positive or negative references (source) is collected under “node family couples” including the “cooperation”. All of these node family couples and their analysis will be explained in detail in Chapter 4 (Analysis and Results). As a result of the calculations/analysis mentioned above, a report is prepared by the NVivo 10 program. These node family couples (positive/negative) for each sector cluster are analyzed in terms of degree of association with each other in “SPSS 20 Statistical Analysis Program”. In the program, the relations between the nodes couples are analyzed as the results of “contingency tables” created after “chi-square tests”. The values I got from these tables are used in making the node family couples more meaningful. In other words, whether the degree of association between the node family couples are “meaningful (H-alternative)” or “not meaningful (H-zero)” is figured out. Related to this, for each sector cluster, from the firms’ general perspective and perception, each of the four constituents of the METUTECH (R&D and Innovation, Support, Sectoral Diversification, Support), are studied to figur...
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