Hrm 531 Week 4 Paper

These values also prove to be statistically significant, based on the p-values that accompany them.

Statistical procedures can be divided into two major categories: descriptive statistics and inferential statistics. Typically, in most research conducted on groups of people, you will use both descriptive and inferential statistics to analyse your results and draw conclusions. So what are descriptive and inferential statistics? And what are their differences?We have seen that descriptive statistics provide information about our immediate group of data. For example, we could calculate the mean and standard deviation of the exam marks for the 100 students and this could provide valuable information about this group of 100 students. Any

When you hire a professional cleaning company, especially Alta Clean, to maintain your floors and carpeting, you can be sure that they will keep both looking good every day and for as long as possible. Professionals not only know how to clean your carpeting gently to keep carpet fibers intact and to guard against discoloration, they also know how to keep your floors polished and gleaming. A professionally-cleaned floor or carpet will improve your employee morale and show your clients that you care about them and your business.

Waits and Sons is a landscaping business operating as a family business since 2007 (Waits, 2012). Matt Waits has been the contracted landscaper for the residence at 411 N Wayman Street for the past three years. In a recent interview, Waits answered the following questions:

The specific groups that will be impacted by this change will be the Stock Team associates who will have to convert to days. They will be the ones who will have to adjust to a new work schedule, new job roles and new job environment. They are the driving force who will make this change work or not.

Statistics refers to the use of numerical information in everyday life to calculate facts and figures in limitless circumstances. In addition, statistics refers to the scientific collecting, classifying, summarizing, organizing, analyzing, and interpreting numerical data. This week the class’s objectives were to apply the steps in testing a research hypothesis, to compare the means of two or more groups, and to calculate the correlation between two variables. Learning Team D’s members have reflected on each of these issues and share their insights on these objectives.

Dream Home Construction HRIS needs are for the following, staffing strategy, total rewards strategy, training/learning strategy and performance management strategy. In continuing to provide high quality construction for dream homes in the Atlanta area, the company will need to implement an HRIS vendor or software package to assist with supporting the staffing, total rewards, training/learning, and performance management strategies. These functions will serve as a supportive background for the company by providing everything from skilled and talented labor to management training services, employee enrichment opportunities and more. In order for Dream Home Construction to function optimally and improve productivity the company must have the right tools and resources in place. I’m proposing one of the vendors listed below to support Dream Home Construction’s HRIS needs.

The main purpose of the most researchers in conducting a research study is to achieve a statistically significant result. When we say statistically significant, it means that the result in a research study was not attributed to chance. In addition, it also means

You asked the following questions: “We are working on a project in an existing warehouse that stores and distributes auto parts protected by an existing ESFR system. The owner(s) would like to add a 10 ft high mezzanine with a solid deck about 32,000 sq. ft. in area and store below it. The framing for this mezzanine will be open web bar joist approximately 18 in. deep. The top of the shelving will be 8 ft in. with no storage on the top shelf. The owner is anticipating that about 50% of the products will be Group A Plastics and could be placed anywhere below the mezzanine. The proposed shelving is to be solid shelves by placing two 18 in. deep shelving back-to-back with no longitudinal or transverse flue spaces with a 36 in. aisle. There are five things we are looking to verify: 1) If we are interpreting NFPA 13 (2007 edition) Chapter 17 correctly, if the

Couldn’t NextCapital create a QA test script that we could run? Do we have a policy regarding this?

Walmart currently employees more that 2 million people worldwide in their more than 10,000 retail stores, strategically located in 27 different countries worldwide (Walmart Inc., 2013). In 2012 the company reported earning well over 400 billion dollars (Walmart Inc., 2013; "Walmart- Refocus," 2006). Here in the third week of the needs assessment being conducted on behalf of our client Sams’s Club a division of Walmart Inc., the focus surrounds the collection and its analysis. Following the collection of data and a meeting was held with Sam’s Club management and a recommendation was made based on this analysis.

Stang, Poole and Kuss explain, in SST, P-value is an important part to decide the null hypothesis. The SST itself, they explain is analytical approach that developed based on two prominent statisticians, Fisher and the Neyman-Pearson. However, in present practical, SST is incompatible amalgamation of those two theories. In Fisher theory, P value represents the strength of evidence against the null hypothesis: the lower the P-value, the stronger the evidence. In this theory, they criticize lake of alternative hypothesis and concept of statistical power. In contrast Neyman and Person theory included the alternative for the null hypothesis, type I and II error and theoretical of effect size. This hybrid method leads to

In the mid 90’s, the Board of Scientific Affairs (BSA) of the American Psychological Association (APA) convened a Task Force on Statistical Affairs whose goal was to “elucidate some of the controversial issues surrounding applications of statistics including significance testing and its alternatives; alternative underlying models and data transformation; and newer methods made possible by powerful computers” (BSA, personal communication with the author, February 28, 1996). This task force consisted of statisticians, teachers of statistics, authors of statistics, journal

Many interesting points are presented in this book with an assortment of interesting ways the book introduces serious issues surrounding statistics as it relates to influencing outcomes that are of very high importance in people’s lives. One example is the idea of manupilation of health statistics that are made to present trends in cancer that was the focus of one of the statistical analysis reports that followed patients over a period of time but failed to give a description of how the statistic model was carried out. The insusing outcome was never explained to be based on random sampling information that was collected over a period of time that did not cover the time period of a given time that would be deliver of good statistical results. The book boost on pretence. It could be interpretered as being a primer in ways to use statistics to deceive an audience by those individuals who might be of the persuasion to take the information and run with the examples to sell points and ideas that otherwise might not fly in our everyday world. It is in away a simple and effective statistical device to impress readers about how much people can be duped by the statistics in many ways by the use of “word average”- mean, median, or a mode model as a vehicle for the collection of data. This book is definitely concise while being practical in its development and presentation. It is also witty and unique in that it introduces concepts in ways that are sellable to the

When using inferential statistics depends on the sampling technique used as well as the characteristics of the population data. This dependency does assume that the sample and population meet certain criteria. The criteria is called statistical assumptions, and if there are violations of these statistical assumptions that are not addressed, than the data may not be interpreted correctly. In particular, Type I or Type II errors may be increased or decreased incorrectly. Nimon’s (2012) article focused on assumptions associated with substantive statistical analyses across the