Data Analysis

Data Analysis

Introduction

The purpose of this paper is to analyze the results given in the table below through statistical techniques, from the point of view of human resource management, health and safety of employees is one of the main bases for the preservation of the force working properly. We will try to collect the necessary measures, ranked by the scope thereof, for which the employer can guarantee job security in their activity. At work, it can affect health in many ways and all are important. It can cause damage as a result of the workload, whether physical or mental, and in general, psychosocial and organizational factors can generate fatigue, stress, job dissatisfaction, and so on. We act on them as tools and Psychosociology Ergonomics applied to prevention of occupational hazards. Disease contracted as a result of the work and not covered in this table will be considered, for legal purposes, such as accidents. From the technical point of view prevention, we talk about work-related illnesses, no occupational disease, meaning, that slow and gradual deterioration of the health of workers, produced by chronic exposure to adverse situations, whether produced by the environment it develops the work or the way it is organized.

Discussion

Descriptive statistics are commonly encountered, relatively simple, and for the most part easily understood. Most of the statistics encountered in daily life, in newspapers and magazines, in television, radio, and Internet news reports, and so forth, are descriptive in nature rather than inferential. Compared with the logic of inferential statistics, most descriptive statistics are somewhat intuitive. Typically the first five or six chapters of an introductory statistics text consist of descriptive statistics (means, medians, variances, standard deviations, correlation coefficients, etc.), followed in the later chapters by the more complex rationale and methods for statistical inference (probability theory, sampling theory, t and z tests, analysis of variance, etc.)

Descriptive statistical methods are also foundational in the sense that inferential methods are conceptually dependent on them and use them as their building blocks. One must, for example, understand the concept of variance before learning how analysis of variance or t tests are used for statistical inference (Smith and Roberson, 2002). One must understand the descriptive correlation coefficient before learning how to use regression or multiple regressions inferentially. Descriptive statistics are also complementary to inferential ones in analytical practice. Even when the analysis draws its main conclusions from an inferential analysis, descriptive statistics are usually presented as supporting information to give the reader an overall sense of the direction and meaning of significant results.

The results in the table below shows the descriptive statistics for the study conducted, it can be observed that on average all employees have worked for 46106.67 hours for the 12 months period ending in 2009, however, the standard deviation is much greater due to the larger range. The data set also shows that on average the injury rate is 14.83 over the period of 12 months per 100 employees which is quite high, the range of this injury rate shows ...