Christians view mankind as a union that narrowly connects scientific materials. However, from the Christians' historical context, (Hill, 1981) Bayes' theorem explains the statistical analysis through a method of induction, which shows how, given the results from an experiment; statisticians may obtain the probability of a hypothesis
This growth has subsequently advanced into broad dimensions of data handling and analysis, resulting into a fully-fledged scientific discipline. Statistics is a science that serves within the framework of construction, and theoretical mathematical applications in order to analyze a set of numerical data hence obtaining credible knowledge (Kemptborne, 1979)
Canonical correlation analysis is used to measure the strength of the association between the independent and independent sets of variables. This type of analysis is most helpful in validation of test results, wherein the researcher would determine which variables are significantly related, and upon determining this, run further canonical analysis with the identified significant variables (Hair, 1995:187)
Multiple regression, when applied to specific situations, could best answer problems wherein it must be determined which among the many extant factors are possibly contributing to a set of outcomes (dependent variables). For example, is variation in sales driven by prices, distribution, or advertising? Is individual perception about a political personality determined by psychographic or demographic profile? And which among the variables in each factor contribute strongly to the formation of this perception? Discriminant analysis is most useful in profiling specific groups of people or individuals based on specific characteristics, which may be demographic, psychographic, lifestyle, and specific categories defined by the researcher to be characteristic of the dependent variable (Malhotra, 1996:617)
Factor analysis helps the researcher determine and explain the relationships, specifically correlations, extant among the variables tested. Application of this type of analysis is most useful in market research, wherein psychographic factors and attitude statements are often treated as one set of variables, factor analyzed to generate a smaller set of variables that would somehow reflect, highlight, or explain differences among the variables and across respondent groups or profiles (Weiers, 1984:473)
Although the research investigators chose to use the entire population as their sample this procedure can be described as a probability sampling as the sample is excessive (1548 participants). If the researchers had opted to take a random sample from the 1548 participants the procedure would likely have had delivered the same results -- provided the sample drawn from the overall population was large enough (Ferguson, 1966)
Following a well-defined research question the research investigators' task is to follow-up with a statement of a testable null hypothesis or hypotheses. The null form of the hypothesis is required in order for the proper application of a statistical data analysis tool to be implemented (Ohlson, 1998)
The null form of the hypothesis is required in order for the proper application of a statistical data analysis tool to be implemented (Ohlson, 1998). Simply stating that an attempt to "confer" that an insulin deficiency might or might not affirm a "predisposition to complications" is not adhering to proper scientific research protocol with respect to a needed testable null hypothesis (Van Dalen, 1964)
Police do need to screen calls for service and analyze whether or not they are discovery crimes or involvement crimes, as well as many other particulars. This is where the importance of police phone operators comes into play and is elaborated upon in the article, Calling the Cops Police Telephone Operators and Citizen Calls for Service (Atunes & Scott 1981)
Statistical research therefore arms managers with valuable information when it comes to making of informed decisions for business sucess. Therefore to form a basis of good decision making business people should be able to understand how statistics can be applied in the description of markets, advertising development, price setting and how they can best respond to the consumer demands that are often changing (Petryni, 2010)
It is the science of collecting, summarizing, analyzing data in numerical form. It entails planning on data collection in terms of design of surveys and experiments to be used (Calkins, 2005)
Nurse practitioners in Oncology can benefit from this study because the carefully collected, examined and interpreted data will give them greater understanding and deal with their breast cancer patients' distress issues and effects. Module 8: One Clinical Use of Research Results in Advanced Nursing Roles of Practitioner, Educator, or Administrator Are older patients comfortable discussing sexual health with nurses? (Farrell & Belza, Jan-Feb 2012) provides research results that can be used by a nurse practitioner, educator and administrator
Nursing Research How Data Collection Influences Statistics Data collection influences statistics in several ways. First, data is collected according to a "category scheme," which is the establishment of meaningful categories in which the data is collected and analyzed (Polit & Beck, 2008, p
" A null hypothesis usually asserts a lack of effect or a lack of difference and is used by a researcher to test a hypothesis and possibly prove it to be false. A null hypothesis can never be proven false itself; it can only be used as a tool to prove or disprove a hypothesis by data examination (Purssell & While, Nov 2011, p
In specific, the researchers' primary interest was, "to assess the optimal BMI range and to provide stable estimates of the risks associated with being overweight, obese, and morbidly obese (BMI ?40.0), with minimal confounding due to smoking or prevalent disease" (de Gonzalez, A
In general, prospective studies are those designed to observe a predefined population over time. In a prospective analysis, a particular outcome of interest, say death or the development of disease, is documented, and exposure or non-exposure to certain risk factors are ascertained as they occur during the course of a study (Gordis, L
The most basic level of analysis using statistics is in the development of descriptive statistics, which provide information about a particular data set but do not allow for conclusions to be drawn about elements outside of this particular set of observed data (Lund, 2010; Hill, 2012). Elements such as the average real cost of a procedure, the variation and/or range of responses to a specific treatment plan for a specific illness, and the standard deviation of the number of nurse-hours lost due to illness are all considered by various personnel within the healthcare organization, and are all examples of descriptive statistics (Hill, 2012)
In this way, though the organization would be working on less certain information and a projected range of expectations rather than concrete and certain measurements, preparedness can still be increased (Hill, 2012). The four levels of measurement typically identified in any data collection setting are nominal (in which the data attributes can be classified or named, but not readily manipulated), ordinal (in which the data attributes can be ordered), interval (in which the relative distance between data points/attribute observations becomes measurable/meaningful), and ratio (in which there is an absolute or constant measurement, typically a zero, that is meaningful to the data set as a whole) (Trochim, 2006)
Participants were required to sign a human subjects' consent form before participating in the study. The experimental design met the requirements for a low-risk study as determined by the British Psychological Society and the University of Sussex (Field, 2012)
The subjects were then asked to write down all the words they could remember during the two-minute recall period. Statistical Analysis -- Since the data was ratio scale, segregated by gender, and divided into three independent groups (Hoskins, n