| Information based decision making | Unit 5002V1 | | | 4/1/2015 |
Task 1 (600-700 words):
A.C.1.1 – Examine the nature of data and information
Data comprises of factual information. Data are the facts from which information is derived. Data is not necessarily informative on its own but needs to be structured, interpreted, analysed and contextualised. Once data undergoes this process, it transforms in to information. Information should be accessible and understood by the reader without needing to be interpreted or manipulated in any way.
Knowledge is the framework for understanding information and using it to inform judgements, opinions, predictions and decisions – a pyramidal relationship (See diagram 1)
Diagram
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Therefore, I prefer circular model (Diagram 2) of the relationship as knowledge can influence what data is collected thus generating information to enhance knowledge that in turn can generate more data.
There are different types of data and information. These are examined in Table 1:
Type of data | Definition | Pros | Cons | Qualitative data/ information | A rich and detailed method to capture how and why people behave in certain ways and the impact of these processes on behaviour. | Captures participant’s lived experiences.Allows a deeper understanding of a topic.Smaller sample sizes so less expensive to do.Takes researcher bias in to account – an ethical strengthCan help to provide new ideas to shape a service for people. | Smaller sample sizes, so less generalizable to larger populations.Not possible to create statistics – which can help to shape and plan service effectiveness and deliveryTime consumingDifficult to make comparisons within the sample.Poor re-test reliabilityResults vulnerable to researcher bias and experience. | Quantitative data/ information | Analysis of numerical data to explain outcome, prevalence, frequency, time, cost. | Based on explicit knowledge and this can be easy and fast to capture and analyse.Results can be generalised to larger populationsCan be repeated – therefore good test re-test reliability and validityStatistical analyses and interpretation are
This is important because if the standardisation sample and Ruby’s demographic did not match, there could be chance of test bias (Sim and Wright, 2000). The reliability and validity measures obtained for the standardization sample do not indicate adequate reliability and validity for the target population (Papathanasiou, Coppens and Potagas, 2013)
Simple and frank as it could sound, the main features of the upcoming of data knowledge have a
The aim of this report is to look at information based decision making to help identify and select sources of information, analyse and present information to support decision making and communicate the results of information analysis and decisions. I will look at the key models and
Quantitative data was represented as mean, standard deviation, median and range. Data was analyzed using student t-test to compare means of two groups and paired t-test compared pre and post results. Qualitative data was presented as number and percentage and compared using either Chi square test or fisher exact test. Graphs were produced by using Excel or STATA program. P value was considered significant if it was less than 0.05.
Knowledge is a characteristic of a person that influences the person’s behavioral potential. Since knowledge, itself, cannot be directly observed, it must be inferred from observing performance on a test, e.g. questions designed to determine the beliefs of a person about, say, adding two-digit numbers. Knowledge has been conventionally defined as beliefs that are true and are justified. It is reasonable to think of a ((true)) belief as one that is in accord with the way in which objects, people, processes and events exist and behave in the real world. Also, it is the information of understanding and skills that are gained through education or experience (Oxford Learners Dictionary, 2001).
First, before we talking about the question, there should be a definition about data. Everyone's understanding of the data is not always the same. From a broad perspective, all the behavior of the system
As a researcher, picking the correct statistical method is an important step of an evidence-based research that enhances the study and ensures validity. There are two major types of statistical methods; descriptive statistics and inferential statistics. Descriptive statistics gives a basic description of a data set, and an inferential statistics enables the researcher to make inferences between the independent variable and the dependent variable. Initially, a descriptive statistic was used to analyze the data. The analysis of a descriptive statistics entails using the calculations of the mean, standard deviation, and medium. However, Messina et al. (2009) has a small sample size in the research study and the descriptive statistics produced
Assignment Requirements 5002.....................................................................................4 Learning Outcome 1: Be able to identify and select sources of data and information ....................................................................................................................................4 1.1 Discuss the nature of data and information......................................................4 1.2 Evaluate relevant sources of data and
The results from this study only reflect a very small number of the population, so it is difficult for this experiment to show any significant results. It would have reflected better on the results if the sample size had been meet, however it was not possible due to lack of time and number of eligible volunteers.
Data is a collection of facts that can be measured or translated. Data may consist of words, numbers, observations, descriptions of things, and measurements. Data may be qualitative or quantitative. “Qualitative data is descriptive information that describes something. Quantitative data is continuous measurements of numerical information” (Lind, Marchal, & Wathen, 2011, p. 9). Data can be collected in many ways but the simplest way is direct observation. Understanding data analysis helps people to make an informed decision.
1. What are data, information and knowledge? Provide an example of transformation of data to knowledge using as an example the Accounts Receivable (AC) in the accounting department or personnel data in the HR department.
In order to understand the various data that is collected it must be organized. The goal in doing this is to provide information. Data refers to the units of observation while information is data that has been organized, making it useful (Davis & Lacour, 2014, p. 34).
Throughout this paper, the values of the Six Thinking Hats will be discussed and the meanings behind the Six Hats. Six Thinking Hats’ is “used to look at decisions from a number of important perspectives. This forces you to move outside your habitual thinking style, and helps you to get a more rounded view of a situation (de Bono, 1985)”. There are five values behind the Six Thinking Hats. They are role-playing, attention direction, convenience, possible basis in brain chemistry, and rules of the game. Decision-making can be difficult, but these are decisions that are made after all the information has been provided beforehand.
Information is very important when used in organisations. Organisations need to have accurate and quality information so the information is reliable. There is Date and Information, Data is raw facts or figures that have not yet been processed, data is things such as times, weights, measurements and scales. Information is data that is useable, such as TV listings, bus timetables. Etc. there are two types of data, Qualitative date and Quantitative data.
According to (Chimedza, Muchengetwa & Chinyemba 2010) data is a collection of numbers or observations of things that are happening brought together for reference or analysis for example hourly movement of a cyclone.(Tucker 1988)