Data Collection Methods. Introduction Data collection is the process of gathering and measuring information on variables of interest‚ in an established systematic fashion that enables one to answer stated research questions‚ test hypotheses‚ and evaluate outcomes. Data Collection Techniques include the following: Personal Interviews Conducting personal interviews is probably the best method of data collection to gain first hand information. It is however‚ unsuitable in cases where there are
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Sample Assessment Materials Edexcel GCSE in Statistics (2ST01) Inside this Sample Assessment Materials pack you’ll find: • Accessible papers to help you and your students prepare for the assessment • Clear and concise mark schemes to • Supported controlled assessment let you know what the examiners are looking for information including sample tasks and assessment criteria to share with students. Issue 3 February 2010 Welcome to the GCSE 2009 Statistics Sample Assessment Materials
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of 12 students‚ we want to select a random sample of 4 students to serve on a university committee. How many different random samples of 4 students can be selected? a.|48| b.|20‚736| c.|16| d.|495| ANS: D 2. Parameters are a.|numerical characteristics of a sample| b.|numerical characteristics of a population| c.|the averages taken from a sample| d.|numerical characteristics of either a sample or a population| ANS: B 3. How many simple random samples of size 3 can be selected from a population
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they are going to us a sample to draw an inference about a population‚ it means that rather than survey the entire population‚ they’ll survey a smaller group and apply the results to a larger group. For example‚ if you take a neighborhood in a town with 100 homes and survey approximately 80% of the households and 76% of those families own multiple televisions you may infer that the majority of the 100 home neighborhood also own multiple televisions. A simple random sample is important for this
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we can’t count on a non-probability sampling scheme to produce representative samples. In mathematical statistics books (for courses that assume you have already taken a probability course): * Described as assumptions about random variables * Sampling with replacement versus sampling without replacement What are the main types of sampling and how is each done? Simple Random Sampling: A simple random sample (SRS) of size n is produced by a scheme which ensures that each subgroup of the
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STUDY ON “A STUDY ON THE CONSUMER PERCEPTION REGARDING THE SUCCESS OF BIG BAZAAR” [pic] ACKNOWLEDGEMENT One of the most pleasant parts of preparing the project is the opportunity to thank those who have contributed to its preparation. The list of expression of thanks – no matter how extensive is always incomplete and inadequate. These acknowledgements are no exception. First of all we would like to thank our mentor Miss Deepti For her unflagging patience‚ and knowledge which has proved
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Why we need to do M&E Feedback mechanism (what works and what does not) Informing stakeholders Project Cycle Assessment and planning- implementation and monitoring- evaluation- adaption Outcome Monitoring (Impact Evaluation) vs. Process Monitoring (Implementation Evaluation) Monitoring Strategy Comparisons- comparing results of our project to some benchmarks: Comparing a group impacted by our project to itself (over time) Comparing a group impacted by our project to a group not impacted
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Procedures There are many sampling procedures that have been developed to make sure that a sample really represents the target population. Simple Random Sampling In simple random sampling‚ every individual in the target population has an equal chance of being part of the sample. This requires two steps: 1. Obtain a complete list of the population. 2. Randomly select individuals from that list for the sample. In a study where the unit of analysis is the student‚ the researcher must obtain a
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hypothesis test for each sample at the .01 level of significance and determine what action‚ if any‚ should be taken. Provide the test statistic and the p-value for each test. At 0.01 level of significance │Zᾳ/2 │ = 2.58 Reject Ho when │Z│> │Zᾳ/2 │ Sample 1 Sample 2 Sample 3 Sample 4 SAMPLE MEAN 11.958 12.028 11.889 12.081 POPULATION MEAN 12 12 12 12 SAMPLE STANDARD DEVIATION 0.22 0.22 0.20 0.20 SAMPLE SIZE 30 30 30 30 Z -1.028 0.712 -2.935 2.161 RESULT ACCEPT ACCEPT REJECT ACCEPT Sample 3 is the only one
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author is that a presented interval brackets the true value in the population. With everyone measured‚ the true value would be known‚ unless of course there were measurement or calculation errors. When the true value in a population is estimated with a sample of persons‚ things get more complicated. Rather then just the mean or proportion‚ we need to derive the standard error for the variable of interest‚ used to construct a confidence interval. This chapter will focus on simple random sampling or persons
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