Bsbwor504 Problem 3

 3. Promoting transfer readiness and postsecondary enrollment along with further transitory pathways toward relevant employment, apprenticeships or job training.

Write a summary review of Appendix A, B, C, and D from Intelligence Led Policing "The New Architecture" from Week 5.

I have examined task, tools and technology, knowledge, skills, ability, work activities and work context, interested code, work style and work values for job : 35-2014.00 –Cook and Restaurant, 21-1012.00 –Educational Guidance, School and Vocational Counselors; 27-2022.00-Coaches and Scouts. After reviewing the O.Net results, I will report my talents and lack of desire to do those occupations now, and aspiration to accomplish these positions.

I have learned many very important skills from BPBE 272 that I value in my educational career as well as in my future endeavours. Yes, I learned all of the key elements of economics that makes it so important in the world today, but most importantly I learned how to apply all of the economic skills BPBE 272 gave me. This class gifted me with the ability to evaluate the world around me and within my career in an economic mind set. This class really enforced a life long understanding of agricultural economics through the use of teaching styles that require us not to memorize, but to actually learn and hold the information. Throughout, I will explain:

The last few weeks we covered descriptive statistic: the central tendency, variability, correlation and Z-score. Today’s session is a little bit different, we will be talking about statistical significance. Statistical significance is the level of risk one is willing to take to reject or accept a null hypothesis while it is true and it separate random error from systematic error. When doing a study or research, the statistical significance shows that the difference obtained were not caused by chance. Inferential statistics, the T-test, partition noise from bias by studying a random sample than the population in which we are interested and from the results we infer. The advantage of using sample than a population, it is convenient, saves time, energy and money because n is smaller than population and above all it helps to control systematic and random errors. When we are making a conclusion, we should have a certain confidence or probability of being right and that is called the alpha level; which the risk you are willing to

A population is the entire group to be studied and a sample is a portion of the population.

I choose to use my older sister,Chioma, for this assignment because I felt like she was the perfect candidate to explain what she does. I decided to call my sister and ask if she was available to help on November 1,2017. I said my name and explained why I thought she my best resource.She came up with an idea that we could actually meet up at a private place so that I can be interviewed. We scheduled to meet up on a Sunday because it was basically the only day we were both free. She choose one of the officesses that she worked at earlier in the year; and thought that 2:00 pm was a reasonable time.That following Sunday we meet up and was dressed in formal attire. I wore a tan button down with a blue tie, and accompanied with black slacks. My

The median home sales price was between $348,000 and $1,100,000. These numbers include distressed and non-distressed properties. Additionally, 1607 homes were at some stage in the foreclosure process. Current home values are as follows: 503 homes were valued between $50,000 and $200,000; 873 between $200,000 and $300,000; 6,954, $300,000 and $500,000 and 2,418, over $500,000. Median housing price is reported at $425,600 (U.S.Census, 2010).

· monitor the relative growth rate of each sample by measuring the size of each frond compared to the beginning size. Measure once every two days.

a) Based on a randomly selected group of 500 patients with high cholesterol, it was found that 67% have heart disease. Is this a population or a sample; explain your answer. Raw data is collected from a subset of patient with high cholesterol to determine numbers describing characteristics of the subset (Bennett, Briggis, & Triola, 2009). The raw data collected from the 500 patients is consolidated and summarized to form sample statistics. The raw data and sample statistics are indications that this is a sample (Bennett, Briggis, & Triola, 2009).

Statistics is a mathematical science pertaining to the collection, analysis, interpretation or explanation, and presentation of data. It is applicable to a wide variety of academic disciplines, from the physical and social sciences to the humanities. Statistics are also used for making informed decisions – and misused for other reasons – in all areas of business and government. Statistical methods can be used to summarize or describe a collection of data; this is called descriptive statistics. In addition, patterns in the data may be modeled in a way that accounts for randomness and uncertainty in the observations, and then used to draw inferences about the process or population being studied; this is called inferential statistics. Both

maximus and S. surattensis at varying elevations. Percent cover is often used to determine the coverage of a particular species; in this case it is used to determine the cover of Guinea grass and Kolomano on the different plots. Based on observations from several ridge hikes, a hypothesis had been drawn up, and stated that: As elevation increases, so does percent cover of M. maximus and S. surrattensis. M. maximus is a good species to test because of it’s high abundance, particularly on the ridge. Kolomano is also a readily available on the ridge and is easily visible due to its flowers. By collecting measurements of percent cover at each of the 11 plots, the hypothesis could be supported or refuted.

a. Conclusion drawn must be based on a sample that represent the entire group .

One could describe descriptive statistics as collecting, organizing, summarizing and then presenting data. Inferential statistics may be explained as making predictions, making inferences, determining relationships, and hypothesis testing. To express the fundamental characteristics of the facts in a certain examination one would use descriptive statistics. This type of statistics presents straightforward outlines about the example and the quantity. Thus with detailed illustrative examinations, they shape the base of nearly all quantitative analysis of data. To summarize a collection of data in a clear and understandable way is the most essential use of descriptive statistics (RVLS, 2009). Numerical and graphical are the two crucial methods in descriptive statistics. If one is using the numerical style one may calculate statistics by using mean and average differences. Descriptive statistics are usually recognized from inferential statistics. With descriptive statistics it is simply describing what is or what the data shows (Social Research Methods, 2006). With inferential statistics, it is trying to reach

Presented below is the model assessment graph that represents the misclassification rates at each number of leaves.