• School Mathematics
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• v.16 no.4
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• pp.727-743
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• 2014

The concepts of sample and sampling are central to the statistical thinking and foundations of the statistical literacy, so we need to be emphasized their importance in the statistics education. However, many researches which dealt with samples only analyze textbooks or students' responses. In this study, the concept of sample is addressed by a historical consideration which is one aspect of the didactical analysis. Moreover, developing concept of sample is analyzed from the preceding studies about the statistical literacy, considering the sample representativeness and the sampling variability. The results say that the historical process of developing the concept of sample can be divided into three step: understanding the sample representativeness; appearing the sample variance; recognizing the sampling variability. Above all, it is important to aware and control the sampling variability, but many related researches might not consider sample variability. Therefore, it implies that the awareness and control of sampling variability are needed to reflect to the teaching-learing of sample for developing the students' statistical literacy.

• School Mathematics
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• v.17 no.3
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• pp.515-530
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• 2015

The concepts of sample and sampling are central to make a statistically correct decision, so we need to be emphasized their importance in the statistics education. Nevertheless, there were not enough studies which discuss how to teach the concepts of sample and sampling. In this study, teaching sample and sampling is addressed by foreign curricula and cases of instruction in order to obtain suggestions for teaching sample and sampling. In particular, the curricular of Australia, New Zealand, England and the United States are analyzed, considering the sample representativeness and the sampling variability; the two elements in the concept of sample. Also foreign textbooks and cases of instruction when it comes to teach sample are analyzed. The results say that with respect to teach sample can be divided into four suggestions: first, sample was taught in the process of statistical inquiry such as data collection, analysis, and results. Second, sample was introduced earlier than Korea curriculum. Third, when it comes to teach sample, sample variability, as well as sample representativeness was considered. Fourth, technological tools were used to enhance understanding sample.

• School Mathematics
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• v.19 no.3
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• pp.533-551
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• 2017

The statistical education researchers advise instructors to educate informal statistical inference and they are paying close attention to the progress of the statistical inference in general. This study was conducted by analyzing the levels and the traits of each levels of the informal statistical inference of the middle and high school students for comparing the samples of data and estimating the graph of a population. Research has shown that five levels of the informal statistical inference were identified for comparing the samples of data: responses that are distracted or misled by an irrelevant aspect, responses that focus on frequencies of individual data points and hold a local view of the sample data sets, responses that the student's view of the data is transitioning from local to global, responses that hold a global view but do not clearly integrate multiple aspects of the distribution, and responses that integrate multiple aspects of the distribution. Another five levels of the informal statistical inference were identified for estimating the graph of a population: responses that are distracted or misled by an irrelevant aspect, responses that focus only on representativeness, responses that consider both representativeness and variability and focus on one particular aspect of the distribution, responses that focus on multiple aspects of distribution but do not clearly integrate them, and responses that integrate multiple aspects of the distribution.

• The Mathematical Education
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• v.56 no.1
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• pp.19-39
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• 2017

Taking samples of data and using samples to make inferences about unknown populations are at the core of statistical investigations. So, an understanding of the nature of sample as statistical thinking is involved in the area of statistical literacy, since the process of a statistical investigation can turn out to be totally useless if we don't appreciate the part sampling plays. However, the conception of sampling is a scheme of interrelated ideas entailing many statistical notions such as repeatability, representativeness, randomness, variability, and distribution. This complexity makes many people, teachers as well as students, reason about statistical inference relying on their incorrect intuitions without understanding sample comprehensively. Some research investigated how the concept of a sample is understood by not only students but also teachers or preservice teachers, but we want to identify preservice secondary mathematics teachers' understanding of sample as the statistical literacy by a qualitative analysis. We designed four items which asked preservice teachers to write their understanding for sampling tasks including representativeness and variability. Then, we categorized the similar responses and compared these categories with Watson's statistical literacy hierarchy. As a result, many preservice teachers turned out to be lie in the low level of statistical literacy as they ignore contexts and critical thinking, expecially about sampling variability rather than sample representativeness. Moreover, the experience of taking statistics courses in university did not seem to make a contribution to development of their statistical literacy. These findings should be considered when design preservice teacher education program to promote statistics education.