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    characteristic one wishes to understand. Because there is seldom enough time or money to gather information from everyone or everything in a population‚ the goal is to find a representative sample (or subset) of that population. For example‚ a researcher might study the success rate of a new ’quit smoking’ program on a sample group of 50 patients‚ in order to predict the effects of the program if it were made available nationwide. Here the superpopulation is "everybody in the country‚ given access to this

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    test machine. b. Tabulate the results. c. Convert all readings to either Rb or Rc values. d. Apply the cylindrical correction factors for cylindrical specimens. 4. Using the hardness conversation chart‚ find the tensile strength of the steel samples. OPERATIONS OF HARDNESS TESTING EQUIPMENT The following operation guide is a general one.Follow it carefully and observe caution and care at every step of the operation.No motion of any controls should be abrupt or using too much force‚ both

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    Worth area had telephones in their offices‚ thereby clearly defining their sampling frame. All samples were selected using the probability sampling method. A primary listing was selected by systematic sampling and sub-sample listing was selected by simple random sampling. The calculation of the sample size resulted in 384 samples. After the adjusted sample size was implanted‚ the new result was 382 samples from a population of 74‚789 that needed to be surveyed. (Exhibit A) The survey‚ however‚ excluded

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    RESEARCH METHODS PAST YEAR QUESTIONS AND ANSWERS Q1.What are the similarities and differences between basic and applied research reports? Solutions : Both basic and applied research are important to the advancement of human knowledge‚ but they work in slightly different ways‚ and they have different end goals in sight. Basic or pure research is conducted solely for the purpose of gathering information and building on existing knowledge‚ as opposed to applied research‚ which is geared towards

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    Purpose of Statistics

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    Everywhere you go‚ everything you see‚ statistics is all around. I for one‚ did not realize how important and relevant statistics was in our everyday lives until taking this course. Everything is run by statistics; the kind of coffee available in Dunkin’ Donuts‚ the flavors of ice cream at Dairy Queen‚ and even the clothes we buy in stores. Statistics evaluates what works in our growing and complex society nowadays. All of these selections would not be available to us without the statistical

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    QTM assignment

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    Quantitative Techniques in Management ASSIGNMENT PROGRAM: MBA 2yrs SEMESTER: IST Subject Name : Permanent Enrollment Number (PEN) : Student Enrollment Number (SEN) : Student Name : INSTRUCTIONS a) Students are required to submit all three assignment sets. ASSIGNMENT Assignment A Assignment B Assignment C b) c) d) e) DETAILS Five Subjective Questions Three Subjective Questions + Case Study 40 Objective Questions MARKS 10 10 10 Total weightage given to these assignments is 30%. OR 30 Marks All

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    on the statistics that were analyzed to determine the outcome of the credit card product based on the organization’s clients and small business-owners. The main concern regarding inferential statistics is finding something about a population from a sample taken

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    is to find an available respondent who is as similar as possible to the selected member of the target sample” (Rivers‚ 2009: 6). Systematic matching sampling is when an individual or a targeted group of people are matched due to similarities they may have. According to Black‚ “Systematic sampling is to be applied only if the given population is logically homogenous‚ because systematic sample units are uniformily distributed over the population” (Black‚ 2004: 7). Black further states that in

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    Sampling Theory

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    do we use a ‘sample’ When do we use a census (population) Sampling errors ◦ Difference between a measure from sample and the measure which can be obtained from the population  Non-sampling errors ◦ Selection Error ◦ Population specification Error  A bias/error which creeps in when sample obtained through nonprobabilistic techniques does not represent the population  When an inappropriate population is chosen from which a sample is selected  E.g. could be choosing a sample of cat owners

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    Impact Value

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    chamber at thelower edge is capable of sliding freely between vertical guides‚ and fall concentric over the cup. There is anarrangement for raising the hammer and allowing it to fall freely between vertical guides from a height of 38cm on the test sample in the cup‚

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