Diagnostic Statistics and Predictive Statistics as a Re-Definition to Inferential Statistics

2021 ◽  
pp. 157-164
Author(s):  
Ezz H. Abdelfattah
2020 ◽  
Vol 9 (4) ◽  
pp. 146-150

Statisticians use to classify Statistics into two main parts, namely Descriptive and Inferential Statistics. Here, we suggest reclassifying Inferential Statistics into two parts, namely Diagnostic Statistics and Predictive Statistics. Based on that we will have four levels to analyze data (Descriptive, Diagnostic, Predictive and Perspective Statistics). Descriptive statistics mainly related to Graphs, Frequency tables, Measures of Central Tendency, Measures of Variation and Measures of Shape. Diagnostic statistics mainly related to the effects of the Independent variables (inputs) on the Dependent (Target) variable based on the Tests of Correlation or Association, Tests for Means differences and Tests for Classification. Predictive statistics mainly related to Estimation, Regression techniques and Time series Analysis for the Dependent (Target) variable. Perspective statistics mainly related to the previous three levels and acts as a prescription to how to solve or prevent the problem. In this paper, we will clarify the statistical tests used in each level of statistical analysis and will give an example on a real data related to Gynecologic Cancer


2010 ◽  
Author(s):  
Laurence D. Smith ◽  
Lisa A. Best ◽  
Alan Stubbs

Author(s):  
Hamida Mwilu ◽  
Reuben Njuguna

The dynamic nature of business operating environment has called on business leaders to be strategic in their leadership roles if they are to sustain their competitiveness into the unforeseen future. Growth is important in Sacco’s because it is future oriented establishing ways in which the organizational operations can be aligned to future changes in the business environment to ensure that competitiveness is sustained. The SACCOs in Kenya have experienced problems in the past; some even shutting down therefore there is need for customer growth to be enhanced so as to increase their incomes so as to sustain the business. These SACCOs have to look for leaders and managers who can develop future targets, direct and lead other staffs towards meeting the firm’s objective and gaining a competitive edge. The aim of this study was an assessment of corporate growth strategies and performance in savings and cooperative societies in Kenya, Nairobi County. The study sought to determine the influence of market expansion, diversification strategies and acquisition strategies. The study target population was 41 licensed SACCOs in Nairobi County. The study used primary data to collect information, and the data collection instrument was a questionnaire which was given to the 41 operations managers in the 41 selected SACCOs. The data collection procedure was done by the researcher and drop-and-pick strategy will be applied. The data was coded and keyed in Statistical Package for Social Science (SPSS Version 23.0), and was analyzed using both descriptive and inferential statistics. For descriptive statistics was through mean scores, standard deviations, frequencies and percentages, while the inferential statistics was through regression analysis to establish the relationship between strategic leadership and customer growth. The findings were presented in tables and charts for easy understanding, interpreting, and describing the data. The study established that market expansion, diversification strategies and acquisition strategies as corporate growth strategies had a positive and significant effect on the performance of SACCOs in Nairobi City County. The study concluded that the SACCOs significantly employed market expansion strategies through improved branch network, customer base enhancement, new distribution channels and technological innovation. The study concluded that the SACCOs embraced a hybrid of the main diversification strategies, diverse products and services significantly. It was concluded that to a little extent the selected SACCOs in Nairobi City County have employed acquisition as a corporate growth strategy. The study recommends that the SACCOs should embrace integrate technology in the implementation of corporate growth strategies to enhance efficiency and effectiveness.  Further studies should be undertaken to establish the effect of corporate growth strategies on the performance of other SACCOs in other regions to establish the disparities or similarities among the financial sector players. 


Author(s):  
David Blanco-Herrero ◽  
Jorge Gallardo-Camacho ◽  
Carlos Arcila-Calderón

During the lockdown declared in Spain to fight the spread of COVID-19 from 14 March to 3 May 2020, a context in which health information has gained relevance, the agenda-setting theory was used to study the proportion of health advertisements broadcasted during this period on Spanish television. Previous and posterior phases were compared, and the period was compared with the same period in 2019. A total of 191,738 advertisements were downloaded using the Instar Analytics application and analyzed using inferential statistics to observe the presence of health advertisements during the four study periods. It was observed that during the lockdown, there were more health advertisements than after, as well as during the same period in 2019, although health advertisements had the strongest presence during the pre-lockdown phase. The presence of most types of health advertisements also changed during the four phases of the study. We conclude that, although many differences can be explained by the time of the year—due to the presence of allergies or colds, for instance—the lockdown and the pandemic affected health advertising. However, the effects were mostly visible after the lockdown, when advertisers and broadcasters had had time to adapt to the unexpected circumstances.


2020 ◽  
Vol 16 (3) ◽  
pp. 238-247
Author(s):  
Mbithi Mutua

This article attempts to find out if there is breadth in application of quantitative techniques in published literature within the field of human resource management (HRM). In addition, it investigates the holistic use of specific categories of statistics, and if there are categories that are neglected. The study utilises a combination of research questions and hypotheses. The broad categories of statistics that this study focussed on include descriptive, data science statistics, exploratory graphical, advanced statistics such as structural equation modelling, Bayesian statistics and inferential statistics. It goes further to study application of machine learning statistics in HRM research. Using archival methodology, the article utilises a sample of 120 journal papers to answer formulated research questions and hypotheses. Descriptive statistics, exploratory graphical analysis and inferential statistics are used in the analysis. The findings indicate that there are neglected statistics in HRM research. Overall, most statistical categories are underutilised. HRM journal editors, researchers and practitioners must stock HRM methodological toolbox.


SAGE Open ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 215824402110041
Author(s):  
Mohammad Salehi ◽  
Samaneh Gholampour

Cheating is an academically dishonest behavior about which there has been a thrust of research. However, it has not been extensively researched in an Iranian context. Therefore, the current study was conducted with 310 Iranian students. A cheating questionnaire was devised and administered to the participants. Certain demographic variables were investigated. Both descriptive and inferential statistics were employed to analyze the obtained data. The results of the descriptive statistics revealed that cheating was common among participants, and most students did not harbor any negative attitude toward cheating or at least were neutral about it. The most common method of cheating was “letting others look at their papers while taking exams.” The most common reason for cheating was “not being ready for the exam.” As for inferential statistics, one-way analysis of variance, an independent t-test, and correlational analyses were used to test the effect and relationship of demographic variables on and between the cheating behaviors of the participants. It was found that none of the two demographic variables of gender and year level had any effect on students’ cheating behaviors. Furthermore, achievement scores and age were not significantly correlated with cheating behavior scores.


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