Introduction

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==== Zieffler, Garfield, delMas, and Reading (2008) present a comprehensive and thorough working definition of informal inferential reasoning as “the way in which students use their informal statistical knowledge to make arguments to support inferences about unknown populations based on observed samples” (p. 44). They add that such reasoning is performed through a “process” in which students consider attributes of graphical displays of data (e.g. distribution, measures of center), interpret those attributes in context, compare populations based on representative samples, and test the reasonableness of the outcomes of those data (Zieffler et al., 2008). ====

Burrill (2006) writes that in these contemporary times,
> ==== Individual citizens are empowered perhaps more than ever…to make countless decisions affecting education, health, money, careers, even the way they govern…Citizens also have more access to data…Faced with such freedoms, a barrage of information, and inevitably the uncertain consequences of their choices, an understanding of statistics and probability is increasingly important for every citizen. (p. ix) ====

==== This indicates the importance of offering a rich and comprehensive statistics education experience for students. Educational researchers contend that statistical inference is among the “conceptual foundations” for statistics education (Garfield and Ben-Zvi, 2007, p. 389). This view is well-reflected in the NCTM //Principles and Standards for School Mathematics// (2000), as they include “Instructional programs from prekindergarten through grade 12 should enable all students to…develop and evaluate inferences and predictions that are based on data” among their Math Standards and Expectations for Data Analysis and Probability (p. 50). The //GAISE Report// (2005) includes inference as being among the skills students have at the highest level of development in statistical thinking as they “look beyond the data in some contexts” (p. 15). Even further, the //Common Core Standards for School Mathematics// (2010b) include inference as one of the key topics in statistics education that should be covered in the middle and high school grades (Standards 7.SP and S-IC). Each of these makes specific note that development of statistical knowledge and reasoning skills requires the inclusion of inference in a statistics curriculum. ====

==== In our discussion here, we synthesize research conducted on students’ conceptual development and understanding of informal statistical inference based on Zieffler et al.’s definition and the implications this research has on teaching informal inference in the middle school grades. ====

**References**
==== Burrill, G. F. & Elliott, P. C. (2006). Preface. In G. F. Burrill & P. C. Elliott (Eds.), //Thinking and reasoning with data and chance: Sixty-eighth yearbook// (pp. ix-xii). Reston: VA: National Council of Teachers of Mathematics. ====

Common Core State Standards Initiative. (2010b). //Common Core State Standards for mathematics// . Retrieved from http://www.corestandards.org/assets/CCSSI_Math%20Standards.pdf
==== Franklin, C., Kader, G., Mewborn, D., Moreno, J., Peck, R., Perry, M., & Scheaffer, R. (2007). //Guidelines for assessment and instruction in statistics education (GAISE) report: A preK-12 curriculum framework//. Alexandria, VA: American Statistical Association. ====