"Why is it important to distinguish between data and the interpretation of the data" Essays and Research Papers

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    Distinguish between primary data and secondary data? Primary data is the data that is collected first hand from the original source for the purpose of making statistical inference while secondary data is the data that is collected by the method of abstraction and is used to make statistical inference by using primary data already collected by an investigator. Primary data is collected by  Identifying population of interest  choosing sample  analyse sample information  draw inference from

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    Data Interpretation

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    Interpreting your data is a process that involves answering a series of questions about the research. We suggest the following steps: 1) Review and interpret the data "in-house" to develop preliminary findings‚ conclusions‚ and recommendations. 2) Review the data and your interpretation of it with an advisory group or technical committee. This group should involve local‚ regional‚ and state resource people who are familiar with monitoring and with your product. They can verify‚ add to‚ or

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    DATA ANALYSIS AND INTERPRETATION No of responance 80 TOOLS OF THE ANALYSIS Simple percentage calculation‚ multiple correlation and weighted average method are the statistical tools used for the analysis. What is the level of contribution do you think you contributed towards the success of the company and your team. Level of contribution No of responance percentage I think my contribution was huge 40 50% I think I might have contributed to an extent 38

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    Data Interpretation and Short Essays B.1. Using the results from A.1‚ describe and comment on the differences in the mortality parameters (CDR and I-SDR) and patterns of the Black and White American female population. Please justify what are the possible reasons of its differences. Using the results from A1‚ we can see that there is the Black American Female Population has a lower CDR and a higher ISDR than the White American Female Population. As we know CDR does not refer to sub-groups that

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    Interpretation and Analysis of Data In Trinidad chocolate is a very popular snack. Charles chocolate is Trinidad and Tobago’s local chocolate brand and it falls under the chocolate industry. At ASJA Girl’s College San Fernando a survey was conducted to analyze the factors that affect the demand for Charles chocolate. In the survey conducted 20 questionnaires were given out to students; five questionnaires were given to random students within the various age groups 11 to 13 years‚ 14 to 15 years

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    AND DATA INTERPRETATION MASTER TABLE FOR WORKING CAPITAL: Particulars 2008-09 2009-10 2010-11 2011-12 Cash 26641162 55642473 138100028 161490169 Raw-Materials 518716903 2590738053 2733309086 3670256062 Work-in-progress 14357756 212436011 593120762 6448792 Finished-Goods 387209501 765102729 1581471825 1093748619 Debtors 43076543 13796139 89900304 83813855 TOTAL 990001865 3637715405 5135902005 5015757497 Statement showing working capital on 2009 INTERPRETATION

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    From this it can be said that most of the respondents chosen by using the random sampling method where youths with the age group of eighteen through twenty years of age. The first on the questionnaire asked the respondents what level of education they have obtained. A vast number of the participants attained a secondary education forty five percent‚ following by a primary education thirty five percent and the minority attaining a tertiary education twenty percent. From the information mentioned above

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    Data Analysis‚ Presentation & Interpretation Prof. Dr. Md. Nazrul Islam Ph.D 1 Data Analysis Plan The appropriate methods of data analysis are determined by your data types and variables of interest‚ the actual distribution of the variables‚ and the number of cases. 2 Data Management 3 Why prepare a plan for processing and analysis of data? All information has been collected in a standardized way Not collected unnecessary data which will never be analyzed A statistical analysis plan should

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    RUNNING HEADER: Data Interpretation Practicum Data Interpretation Practicum 1 RUNNING HEADER: Data Interpretation Practicum Abstract The constant changes in government agencies create stressors among the different age groups. The ILS consists of two scores‚ interpersonal life stress‚ and occupational life stress. The SPSS data file contains 45 cases‚ one for each woman‚ and four variables‚ their interpersonal and occupational life stress at age 40 and their interpersonal and occupational life

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    range and scope of data being collected today. We are barraged with statistics on sports results‚ economic indicators and politics: people are becoming familiar with scoring averages‚ inflation rates and voter satisfaction surveys. The advent of low-cost personal computers combined with the widespread availability of powerful computing software‚ such as Excel‚ means that many people have both large data sets and powerful tools with which to analyse them. In this report‚ a data set collected by the

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