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The article's main goal was to increase the responsiveness, suppleness, and compliance of enterprises in the ceramics industry. One response variable and five predictor variables were used in the multiple regression methods (Turóczy Zsuzsanna 509). The size of the profit was the study's response variable, and the investment per employee, self-financing ability, cost of labor per employee, yield on equity, and size of the practical endowment were the predictor variables. The units of analysis for the variables were RON apart from return on equity which was measured in percentage (Turóczy Zsuzsanna 509). The data used was secondary that is the response and predictors observations from 2002 to 2011. The data used was sampled from the ceramic sector arriving in only ten observations for every variable. Sampling was done via simple random sampling techniques.
Since the industry has been in existence for an extended period, there was the need to find a sample to make inference on the whole sector. Thus, the author used inferential statistics. Further, there are many variables that affect the profits earned by employees in the ceramic industry, but only five independents variables were used to make inference on the profitability of the personnel in this sector(Turóczy Zsuzsanna 511). Having analyzed the association amid the response factor and the five predictor variables, the outcome indicated that only three elements are significant predictors of the size of profits. There was a crucial association between the response variable and the predictors. According to the findings, the significant predictors of the proportion of earnings in the ceramic industry are self-financing capacity, return on equity and investment per person employed (Turóczy Zsuzsanna 511). It then implies that an increase of the three significant predictors leads to a continuous rise of the size of profits. The use of statistics helps the author in conveying the message since the relationship between the size of profit and the five predictors can only be determined in a regression model.
Turóczy Zsuzsanna, Liviu Mariana. "Multiple regression analysis of performance indicators in the." Emerging Markets Queries in Finance and Business (2012):, Elsevier Ltd, 509 - 514.
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