...WEEK 4 STATISTICAL ANALYSES To purchase this visit here: http://mindsblow.us/question_des/BSHS435WEEK4STATISTICALANALYSES/2786 Contact us at: help@mindblows.us BSHS 435 WEEK 4 STATISTICAL ANALYSES • Student selected a peer reviewed article from the library related to human services and statistical analysis. • Student discussed statistical analyses, including the following information: • Summarize in 100 to 150 words what the research study discussed in the article is about. (Provide a complete citation for the article using proper APA format.) • Discuss in 250 to 400 words the statistical analyses within the article. o Does the article incorporate graphs or tables that facilitate understanding of the data? o Are the descriptive statistical analyses appropriate for the subject? What descriptive statistics were used in the study? o Identify the inferential statistics used and comment if the analyses supported the research problem/hypothesis. (For example, do they support the conclusions reached by the author or authors? Are the statistics misleading or biased?). • The paper is 700 to 1,050 words in length. BSHS 435 WEEK 4 STATISTICAL ANALYSES To purchase this visit here: http://mindsblow.us/question_des/BSHS435WEEK4STATISTICALANALYSES/2786 Contact us at: help@mindblows.us BSHS 435 WEEK 4 STATISTICAL ANALYSES • Student selected a peer reviewed article from the library related to human services and statistical analysis. • Student discussed statistical analyses...
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...Withers November 23, 2015 Statistics Introduction Data analysis is done to convert the raw data into meaningful information. Statistics is all about this data analysis. Before actually working on data analysis in real world, it is important that the basic knowledge is possessed by everybody involved in this process. The following paper seeks to provide basic knowledge in some specific areas of statistical data analysis. Descriptive statistics As the name suggests, descriptive statistics means analysis of data to describe or summarize data in a meaningful manner. The analysis helps in determination of patterns that exist in the data. Descriptive statistics simply describes the data but not present an analysis beyond the data. One cannot make any conclusions about any hypothesis using this. The data, when presented to users, is difficult to comprehend in its raw form. Sometimes the sheer size and volume of data may render it impossible to understand what it represents. Descriptive statistics helps in proper presentation of data such that it can be understood and analyzed by the user. For example, if we had the data about the returns from stocks of 100 companies, then that data would make no sense as it would be difficult to comprehend. But if that data is arranges, classified industry-wise, an average is calculated for each industry and for all the stocks, and then the interpretation would be simpler. Here, descriptive statistics comes as a savior. Following are two most common...
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...differences between descriptive statistics and Inferential statistics and the reasons why we use them. I will also discuss hypothesis development and testing, when to select the appropriate statistical test, and how to evaluating statistical results. In this class I learned the difference between descriptive statistics and inferential statistics. We use descriptive statistics to measure and analysis data. There are a number of reasons why we use Descriptive statistics. We use it, because Descriptive statistics numerical summaries measure the central tendency of a data set, it can include graphical summaries that show the spread of the data, and they provide simple summaries about the sample that help interpret and analyze data. First, there are a number of reasons why we use descriptive statistics we use it because descriptive statistics numerical summaries that either measure the central tendency of a data set. In business therefore descriptive statistics helps in making conclusions about various issues and therefore helps in making decision. Description statistics is the first step in analyzing data before making inferences of data, therefore it is important in analyzing any data collected that will help in describing the characteristics of data collected. There are three measurements that we tend to use. One measurement is the mean. The mean is often referred to as the average. The average is found by adding all the data and then multiplying by the total number of data value. We...
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...BSHS 435 WEEK 4 STATISTICAL ANALYSES TO purchase this tutorial visit following link: http://wiseamerican.us/product/bshs-435-week-4-statistical-analyses/ Contact us at: SUPPORT@WISEAMERICAN.US BSHS 435 WEEK 4 STATISTICAL ANALYSES • Student selected a peer reviewed article from the library related to human services and statistical analysis. • Student discussed statistical analyses, including the following information: • Summarize in 100 to 150 words what the research study discussed in the article is about. (Provide a complete citation for the article using proper APA format.) • Discuss in 250 to 400 words the statistical analyses within the article. o Does the article incorporate graphs or tables that facilitate understanding of the data? o Are the descriptive statistical analyses appropriate for the subject? What descriptive statistics were used in the study? o Identify the inferential statistics used and comment if the analyses supported the research problem/hypothesis. (For example, do they support the conclusions reached by the author or authors? Are the statistics misleading or biased?). • The paper is 700 to 1,050 words in length. BSHS 435 WEEK 4 STATISTICAL ANALYSES • Student selected a peer reviewed article from the library related to human services and statistical analysis. • Student discussed statistical analyses, including the following information: • Summarize in 100 to 150 words what the research study discussed in the article is about. (Provide a...
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...of Statistics Georgia Student Survey, as described on pp. 22, 23, and 151 of Statistics Olympic High Jump, as described on pp. 124, 125, and 128 of Statistics Introduction o Introduce the Learning Team members and the data set. o Briefly explain how the data was gathered and identify the study population. Descriptive Statistics o Define descriptive statistics and list the various descriptive measures. o Explain how descriptive statistical analysis increases understanding of the data. o Include an original graph created with StatCrunch that uses at least one descriptive statistical measure to illustrate the data set. Inferential Statistics o Define statistical inference and include and explain at least one original inferential statistical calculation. o Use StatCrunch to check the calculation and show the steps in your presentation. o Explain how inferential statistical analysis increases understanding of the data. Null Hypothesis Testing o Explain the purpose of null hypothesis testing and provide examples of null hypotheses that may be tested with the data set. o Explain the logic of hypothesis testing and the role of the null hypothesis. Implications for Future Research o Differentiate between descriptive and inferential statistics and how they support...
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...Descriptive and Inferential Statistical Method RES/351 Researchers have many tools available to them in order test and analyze a specific hypothesis. Some of these tools help gather data, while others help ensure accurate and relevant analysis. Data collection can take the form of quantitative and qualitative methods. In a qualitative method, your data is more interpretive. This data is used when trying to discover more of a meaning of specific question rather than the frequency (Cooper, Schindler 2014). This data is generally obtained through interviews, participant observation, or focus groups. On the other hand quantitative data is the precise measurement of a specific behavior or phenomena (Cooper, Schindler 2014). Quantitative data is generally gathered by experiments, standardized testing, surveys, or non-participant observation (Cooper, Schindler 2014). While gathering both types of data, it is important to focus on the type of sampling method you utilize. For example, simple random sampling, or probability sampling, can be used to test a targeted representation of a test population (Cooper, Schindler 2014). There are other sampling methods as well. Stratified random sampling, for instance, is probability sampling that draws from each strata of population. One study I found to demonstrate descriptive statistics used stratified random statistics. In this study, they used stratified random sampling to test accuracy in medical billing (Buddahulsomsiri...
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...with it. To minimize and control these unpleasant occurrences there is police. Police has mandate to ensure a safe life for citizens by controlling and minimizing occurrence of criminal activities, which is evident from reduced criminal cases year after year. The data on criminal cases are logged and a suitable statistical analysis can be made to see if really there is any significant drop in criminal cases in subsequent years. Statistics is the branch of knowledge in which data pertaining to different variables are either collected or generated by suitable experimental design. However, the data is generally very huge in volume and the useful information and underlying trends are hidden in the noise. Therefore, data needs to be processed to extract suitable information and underlying trends. There are many statistical procedures, which helps in extracting suitable information and underlying trends from a large pool of data. One such procedure is “Descriptive Statistics”, which provides useful statistics pertaining to a variable like mean, median, mode, standard deviation, kurtosis, skewness etc. These statistics provide information about central tendency, dispersion and skewness of the data and are very useful information about the variable under consideration. This test speaks about a single variable. Many times we need to know more about a pair of sample and also about the interrelationship between the two variables in the pair. It may be required...
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...research Studies include Questionnaire, Tests, and Surveys. Validity is the degree to which an instrument measure what it is purports to measure. Imprecise information collection can influence the outcome of a study and eventually lead to unacceptable results. Reliability is the internal consistency or stability of the measuring device over time (Gay, 1996). The collection data of Quantitative methods depend on random sampling and organized data collection instruments that fit different involvement into fixed response groups (www.mbaisherebyravali.com). An important aspect of the quantitative research design is the non-probability method. Through the non-probability method, there are many sampling designs such as convenience sampling, purposive sampling and model instance sampling (www.wilderdom.com). Listed below are two Quantitative strength approaches. The first quantitative strength approach is offering vivid data; for example, permitting us to take pictures of an employer population (www.library.pinpoint.com). Another strength is quantitative research have the ability to translate numbers and data in quantifying graphs and charts. (www.library.pinpoint.com) The first weakness of the quantitative approach is large samples are needed thus causing the study to be more expensive, time- consuming and make it susceptible to error. The second quantitative approach is the misuse of sampling and weighing can undiscovered the accuracy ultimately, the validity and strategy of...
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...of an organization’s data with emphasis on statistical analysis. It describes the skills, technologies, practices for continuous iterative exploration and investigation of past business performance to gain insight and drive business planning. Business analytics is used by companies committed to data-driven decision making. It focuses on developing new insights and understanding of business performance based on data and statistical methods. BA is used to gain insights that inform business decisions and can be used to automate and optimize business processes. Business analytics makes extensive use of statistical analysis, including explanatory and predictive modeling, and fact-based management to drive decision making. It is therefore closely related to management science. Analytics may be used as input for human decisions or may drive fully automated decisions. Data-driven companies treat their data as a corporate asset and leverage it for competitive advantage. Successful business analytics depends on data quality, skilled analysts who understand the technologies and the business and an organizational commitment to data-driven decision making. Once the business goal of the analysis is determined, an analysis methodology is selected and data is acquired to support the analysis. Data acquisition often involves extraction from one or more business systems, cleansing, and integration into a single repository such as a data warehouse or data mart. The analysis is typically performed...
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...When faced with an analysis of a situation which deals with a population, an analyzer will incorporate both descriptive and inferential statistics to evaluate his or her results and create a credible conclusion. Descriptive statistics provides information focused on an immediate group of data. After defining what needs to be analyzed, the descriptive statistics will help the analyzer abridge the data to a more meaningful and comprehendible form, which will then provide patterns in his or her research that, will provide a foundation to his or her thesis. For example, a person could use descriptive statistics to evaluate the answers on an exam taken by 400 American students, and use descriptive statistics to determine the overall performance of the 400 students at that school. By using descriptive statistics, the analyzer can use his or her findings, to provide useful information regarding which subjects students need to improve most in, and which minority group or grade level are grasping the educational tools provided at the school more effectively, then those not grasping the provided educational tools and still need more room for improvement. While descriptive statistics helps an analyzer assess an immediate group of data from a single population, inferential statistics allow an analyzer to collect data using bits and pieces of samples which are portions of a collection of data focusing on the group or population of interest in which the analyzer research is concentrated on...
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...Descriptive and Inferential Statistics ________________________________________ Statistics can be broken into two basic types. The first is known as descriptive statistics. This is a set of methods to describe data that we have collected. Ex. Of 350 randomly selected people in the town of Luserna, Italy, 280 people had the last name Nicolussi. An example of descriptive statistics is the following statement : "80% of these people have the last name Nicolussi." Ex. On the last 3 Sundays, Henry D. Carsalesman sold 2, 1, and 0 new cars respectively. An example of descriptive statistics is the following statement : "Henry averaged 1 new car sold for the last 3 Sundays." These are both descriptive statements because they can actually be verified from the information provided. The second type of statistics in inferential statistics. This is a set of methods used to make a generalization, estimate, prediction or decision. Ex. Of 350 randomly selected people in the town of Luserna, Italy, 280 people had the last name Nicolussi. An example of inferential statistics is the following statement : "80% of all people living in Italy have the last name Nicolussi." We have no information about all people living in Italy, just about the 350 living in Luserna. We have taken that information and generalized it to talk about all people living in Italy. The easiest way to tell that this statement is not descriptive is by trying to verify it based upon the information provided. Ex....
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...Descriptive and Inferential Statistics Statistics are all-around and used in everyday life. Statistics are used to describe how effective a medication is for a certain disorder to what the most popular color is in the United States. According to Aron, Aron, and Coups, 2009, “statistics is a method of pursuing truth. As a minimum, statistics can tell you the likelihood that your hunch is true in this time and place and with these sorts of people” (p. 2). Psychologist use two branches of statistics to summarize his or her results and those are descriptive and inferential statistics. This paper will discuss the function of statistics, what descriptive and inferential statistics are, and the relationship between descriptive and inferential statistics. Statistics are used in almost every branch of study and is found behind the scenes in many of our normal daily activities. From economic to scientific studies, statistics are utilized in one way or another. Statistics are an essential part of understanding information and expanding knowledge base and is encompasses almost all aspects of enquiry ("7 Most Essential Functions Of Statistics", 2012). Statistics have many functions that we utilize;statisticsprovides for a better understanding of phenomenon of nature and helps in proper and statistical planning in all forms of study. Using statistics helps in collecting useful quantitative data and also aids in presenting difficult or confusing data in an understandable way. Statistics facilitate...
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...Introduction Predictive analytics is an advanced analytics technique. Predective analytics uses both new and historical data to foresee the result, activity, behavior and trends. Statistics is branch of mathematics, mainly concerns about collection, analysis, interpretation and presentation of tons of numerical facts. Statistics is used in almost every field of research. Head to Head Comparisons Predictive Analytics Statistics Definition Predictive analytics is branch of the data analytics to predict the future events. Statistics in simpler terms is collection of numerical facts. It is the science of collecting, classifying and representing the numerical data. Why it matters? Predictive analytics can identify the risks and opportunities...
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...STAT582 HW7 Review of Two Statistical Software Packages – Minitab and SPSS Yan Sun As a statistician, have you ever got stuck in front of your computer, trying to figure out the correct syntax of a command to type into the little programming window, and just could not get it right? At that moment, I am sure you would wish there was some magic easy button that you could just click and then things would work the way they should. Well, magic does not happen everyday. However, some better choices can make life easier. Instead of using programmed command lines, some statistical software make their usage much easier by using a menu-driven interface. This kind of software are like well-organized control panels. Each of the things you need to do is controlled by a button somewhere on the panel. Once you get familiar with the layout of the panel, the actual work should be quite an enjoyable process. Several good menu-interface statistical software are available. Among them, Minitab and SPSS are the most widely used ones. This report serves as an introduction to these two software packages. For each of them, the software’s specialties, advantages, and suitability will be discussed. Some important functionalities, their implementations, and programming in the two software will be introduced. This report also includes ‘helpful resources’, which I personally found very helpful in learning and using the two software. 1. Minitab History Minitab was...
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...Unit 1 - Fundamentals of Statistics Jeanna Starr American InterContinental University Abstract A data analysis was done on job satisfaction for the company AIU categorized by age, gender, tenure, position, and department. Overall job satisfaction as well as intrinsic (satisfaction with the actual performance of the job) and extrinsic (office location or work colleagues) job satisfaction were considered in this survey. Introduction AIU assembled a team of researchers to study job satisfaction. I was selected as part of a group to participate in a massive global undertaking. The study required me to examine data and analyze the results. The study consists of job satisfaction, which is extremely important to an organization’s overall success. This particular study will allow managers to gain understanding and knowledge about what type of human behaviors can be used to strengthen an organization’s performance. Chosen Variables I have chosen gender for my qualitative data and intrinsic for my quantitative data. The reason that I have chosen these two variables is because I thought it would be interesting to analyze if males or females were more satisfied with their job, and how the actual job performance reflected their job satisfaction rating. Difference in variable types Qualitative variables include subjects that are non-numerical, such as gender. Quantitative variables include subjects that are numerical and give us a clear visual as to what...
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