The purpose of this study is to examine 8 th grade students' skills of connecting mathematics to real life. This study uses survey design since it aims to determine existing situations regarding to students' skills of connecting mathematics to real life. The study sample consists of 176 students in total, who are studying at a state school in the Etimesgut district of Ankara in the second semester of 2016-2017 academic year. "Connecting mathematics to real life scale" which is developed by the researchers, used as the data collection tool of this study. In this scale, students are provided with real life situations and then asked to connect these situations with mathematical concepts. During the data analysis, the responses of students examined in detail and subsequently general categories (levels) which identify students' mathematical connection skill, were created and consequently four levels of connecting (Level 1, 2, 3 and 4) were defined. Study findings are showed that, participating 8 th grade students' skill of connecting mathematics to real life is not in sufficient level. It is observed that, most of the students can only connect mathematics in real life with numbers and shapes.

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The purpose of this study is to analyze the statistical reasoning levels of preservice elementary school teachers. With this purpose, pre-service teachers consisting of 29 groups worked on a model eliciting activity (MEA) in scope of an elective course they were taking. At the end of the class, they were asked to present their solutions while working on the MEA in form of a detailed report. The data of the study consisted of these reports and solution sheets. Content analysis method was used in the analysis of the data. As a result, it was found that when the participants were asked to interpret a data set in a table, they could not establish a relationship between measurements of central tendency and variation, and their reasoning was limited or mistaken. The general tendency when pre-service teachers encounter a data set is that they think the only value representing the data set is the arithmetic mean. Additionally, it was found that, although the pre-service teachers were able to correctly compute the measures of variation such as standard deviation and interquartile range, they did not have sufficient knowledge about what these measures tell us about the variation of the data set. Accepted: 27 October 2016 Keywords Statistical reasoning Model eliciting activity Pre-service teachers Central tendency Variation IntroductionEven if we are not a statistics expert, while we are examining data in our hands, some points might get our attention and inspire curiosity in us. Do the data consist of values close to each other, or are there outliers? If we wanted to represent this value with only one number, what would it be? How do we proceed to reach this value that will represent the data set and maybe lead us to reach the correct result? Such questions may run through our heads. As a matter of facts, all of us encounter large amount of data in our daily lives without knowing about it, and use statistics to make a correct decision regarding these data. In the decisions we make, while some of us use statistically correct reasoning, some of us may tend toward wrong decisions and be mistaken because of the limitations in our knowledge or experience. The importance of statistical reasoning, which is significantly effective in the decisions we make, is undeniable. So, how can we define statistical reasoning? Chervany, Collier, Fienberg, Johnson and Neter (1977), who were some of the people who defined statistical reasoning first, defined it as: a) what a student is able to do with statistical content (for instance, recalling, recognizing, distinguishing statistical concepts), and b) the skill shown by students in using statistical concepts in specific problem solving steps. On their definition, the researchers also added the property of statistical reasoning that it is not a directly observable process. The researchers, starting with this property of statistical reasoning, indicated that this skill may only be observed while working on a specific task. Statistical reasoning includes making sense of statistical information ...