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Marketing refers to the strategies a company undertakes to promote its brands to its potential audience. Advertising provides useful venues for marketing to promote a company's survives/goods to the audience. It has a positive impact on the sale of services or products. In this study, we consider a well-known online medium called Twitter (the fourth most popular social media platform used by marketers) to check its impact on sales. For this purpose, the simple linear regression modeling approach is implemented to test the significance and usefulness of Twitter advertising on sale. Statistical tests such as t-test and correlation test are adopted to test the hypothesis of the "impact of Twitter advertising on sales." Based on the findings of this study, it is observed that Twitter advertising has a positive impact on sales. Furthermore, a new statistical model called the exponential T-X exponentiated exponential is introduced. The proposed model is very interesting and possesses heavy-tailed characteristics which are useful in finance and other related sectors. Finally, the applicability of the new model is illustrated by considering the sales data. [ABSTRACT FROM AUTHOR]

Background. Increasing divorce rates is a major problem in Saudi society. Divorce has become the primary solution for many couples who are experiencing problems in their relationships, and the language of divorce has become prevalent in both the daily register of Saudi courts on a daily basis and in fictional works. This trend has become a threat to marital life and is particularly damaging for children and young people. There has been previous research on the increase in divorce rates; however, no one addresses this important issue statistically. The specific research question is what are the actual reasons for the increase in divorce rates mentioned in previous studies? Objective. This study contains a statistical analysis of the underlying reasons for rising divorce rates in Saudi society. Methods. An online survey was conducted that gathered quantitative data from 800 participants. The responses of factual relevance were examined via edge plan analysis, regression analysis, and analyses with SPSS software to determine the causes for the rise in divorces in Saudi society. A predesign of edge consisting of six factors and twelve trials is selected. The design is examined in all the data for each row of it and according to the factor or reason chosen, provided that all design items are fulfilled; after that, it is analyzed in two ways. Results. Some examples are presented, so the findings indicated that differences on the couple's characters and the length of time the wife spent doing housework and amount of attention to the husband are factors that contributed to divorce. Conclusion. The Saudi Arabian government needs to develop an operational plan to study these causes of divorce and take action. Future studies could analyze the data using supersaturated prototypes, where a large number of variables are studied in just a few simulation trials. [ABSTRACT FROM AUTHOR]

Consistent estimation techniques need to be implemented to obtain robust empirical outcomes which help policymakers formulating public policies. Therefore, we implement the least squares (LS) and the high breakdown robust least trimmed squares (LTS) regression techniques, while using econometric regression model based on a growth equation for the two countries, namely, India and Pakistan. We used secondary annual time series data which covers a long period of 41 years. The adequacy of the time series econometric model was checked through cointegration analysis and found that there is no spurious regression. Classical and robust procedures were employed for the estimation of the parameters. The empirical results reveal that the overall fit of the model improves in case of LTS technique, while the significance of the predictors changes significantly in cases of both countries due to the removal of outliers from the data. Thus, empirical findings exhibit that the results, obtained through LTS, are better than LS techniques. [ABSTRACT FROM AUTHOR]