scholarly journals MAKING COMPARISONS BETWEEN OBSERVED DATA AND EXPECTED OUTCOMES: STUDENTS’ INFORMAL HYPOTHESIS TESTING WITH PROBABILITY SIMULATION TOOLS

2010 ◽  
Vol 9 (1) ◽  
pp. 68-96
Author(s):  
HOLLYLYNNE STOHL LEE ◽  
ROBIN L. ANGOTTI ◽  
JAMES E. TARR
Keyword(s):  
Education Research ◽  
Middle School Students ◽  
Hypothesis Testing ◽  
Social Interactions ◽  
Statistics Education ◽  
School Students ◽  
Simulation Tools ◽  
Research Journal ◽  
Expected Outcomes ◽  
Analyze Data

We examined how middle school students reason about results from a computer-simulated die-tossing experiment, including various representations of data, to support or refute an assumption that the outcomes on a die are equiprobable. We used students’ actions with the software and their social interactions to infer their expectations and whether or not they believed their empirical data could be used to refute an assumption of equiprobable outcomes. Comparisons across students illuminate intricacies in their reasoning as they collect and analyze data from the die tosses. Overall, our research contributes to understanding how students can engage in informal hypothesis testing and use data from simulations to make inferences about a probability distribution. First published May 2010 at Statistics Education Research Journal: Archives

scholarly journals MODELING AS A CORE COMPONENT OF STRUCTURING DATA

2017 ◽  
Vol 16 (2) ◽  
pp. 191-212
Author(s):  
CLIFFORD KONOLD ◽  
WILLIAM FINZER ◽  
KOSOOM KREETONG
Keyword(s):  
Education Research ◽  
Middle School Students ◽  
Real World ◽  
Statistics Education ◽  
Core Component ◽  
School Students ◽  
Statistical Software ◽  
The Road ◽  
Research Journal ◽  
Road Segments

We gave participants diagrams of traffic on two roads with information about eight attributes, including the type of each vehicle, its speed, direction and the width of the road. Their task was to record and organize the data to assist city planners in its analysis. Successfully encoding the information required the creation of a case, a physical record of one repetition of a repeatable observational process. We analyzed data sheets participants created including the methods they used to bind information together into cases. Overall, 79% of their data sheets successfully encoded the data. Even 62% of the middle school students were able to create a bound structure that could hold the critical information from the diagrams. A majority of these structures involved a hierarchy of cases rather than the “flat” case-by-attribute structure that virtually all statistical software require. Our sense is that participants strove to create a structure that modeled the real-world as closely as they could, constructing cases that corresponded to the different sorts of objects they perceived—vehicles with their characteristics nested within road segments with their characteristics. First published November 2017 at Statistics Education Research Journal Archives

scholarly journals STUDENTS’ REASONING ABOUT p-VALUES

2015 ◽  
Vol 14 (2) ◽  
pp. 7-27
Author(s):  
BIRGIT C. AQUILONIUS ◽  
MARY E. BRENNER
Keyword(s):  
College Students ◽  
Community College ◽  
Education Research ◽  
Hypothesis Testing ◽  
Statistics Education ◽  
Research Question ◽  
Statistical Hypothesis ◽  
Statistical Hypothesis Testing ◽  
P Values ◽  
Research Journal

Results from a study of 16 community college students are presented. The research question concerned how students reasoned about p-values. Students' approach to p-values in hypothesis testing was procedural. Students viewed p-values as something that one compares to alpha values in order to arrive at an answer and did not attach much meaning to p-values as an independent concept. Therefore it is not surprising that students often were puzzled over how to translate their statistical answer to an answer of the question asked in the problem. Some reflections on how instruction in statistical hypothesis testing can be improved are given. First published November 2015 at Statistics Education Research Journal Archives

scholarly journals TEACHING PROBABILITY WITH THE SUPPORT OF THE R STATISTICAL SOFTWARE

2014 ◽  
Vol 13 (2) ◽  
pp. 132-147
Author(s):  
ROBSON DOS SANTOS FERREIRA ◽  
VERÔNICA YUMI KATAOKA ◽  
MONICA KARRER
Keyword(s):  
High School ◽  
Education Research ◽  
High School Students ◽  
Statistics Education ◽  
Teaching Experiment ◽  
School Students ◽  
Statistical Software ◽  
Research Journal ◽  
Tree Diagram ◽  
Basic Concepts

The objective of this paper is to discuss aspects of high school students’ learning of probability in a context where they are supported by the statistical software R. We report on the application of a teaching experiment, constructed using the perspective of Gal’s probabilistic literacy and Papert’s constructionism. The results show improvement in students’ learning of basic concepts, such as: random experiment, estimation of probabilities, and calculation of probabilities using a tree diagram. The use of R allowed students to extend their reasoning beyond that developed from paper-and-pencil approaches, since it made it possible for them to work with a larger number of simulations, and go beyond the standard equiprobability assumption in coin tosses. First published November 2014 at Statistics Education Research Journal Archives

scholarly journals DATA LITERACY IS STATISTICAL LITERACY

2017 ◽  
Vol 16 (1) ◽  
pp. 22-25
Author(s):  
ROBERT GOULD
Keyword(s):  
High School ◽  
Education Research ◽  
High School Students ◽  
Data Science ◽  
Science Curriculum ◽  
Statistics Education ◽  
School Students ◽  
Statistical Literacy ◽  
Data Literacy ◽  
Research Journal

Past definitions of statistical literacy should be updated in order to account for the greatly amplified role that data now play in our lives. Experience working with high-school students in an innovative data science curriculum has shown that teaching statistical literacy, augmented by data literacy, can begin early. First published May 2017 at Statistics Education Research Journal Archives

Statistics Education Research Journal

2004 ◽  
Vol 4 (3) ◽  
pp. 58-58
Author(s):  
Flavia Jolliffe ◽  
Iddo Gal
Keyword(s):  
Education Research ◽  
Statistics Education ◽  
Statistics Education Research ◽  
Research Journal

Editorial and Front Matter

2014 ◽  
Vol 13 (1) ◽  
pp. 5-6
Author(s):  
ROBERT DELMAS ◽  
PETER PETOCZ
Keyword(s):  
Education Research ◽  
Statistics Education ◽  
Statistics Education Research ◽  
Research Journal

First published May 2014 at Statistics Education Research Journal Archives

FORTHCOMING IASE CONFERENCES

2013 ◽  
Vol 12 (2) ◽  
pp. 84-87
Author(s):  
ROBERT DELMAS ◽  
PETER PETOCZ
Keyword(s):  
Education Research ◽  
Statistics Education ◽  
Statistics Education Research ◽  
Research Journal

Forthcoming IASE Conferences First published November 2013 at Statistics Education Research Journal Archives

FORTHCOMING IASE CONFERENCES

2014 ◽  
Vol 13 (1) ◽  
pp. 77-79
Author(s):  
ROBERT DELMAS ◽  
PETER PETOCZ
Keyword(s):  
Education Research ◽  
Statistics Education ◽  
Statistics Education Research ◽  
Research Journal

Forthcoming IASE Conferences First published May 2014 at Statistics Education Research Journal Archives

scholarly journals STATISTICAL LITERACY AS THE EARTH MOVES

2017 ◽  
Vol 16 (1) ◽  
pp. 31-37
Author(s):  
CHRIS J. WILD
Keyword(s):  
Education Research ◽  
Statistics Education ◽  
Human Interaction ◽  
Data Display ◽  
Statistical Literacy ◽  
Bob Dylan ◽  
Research Journal ◽  
The Earth ◽  
The Times ◽  
Seismic Forces

“The Times They Are a-Changin’” says the old Bob Dylan song. But it is not just the times that are a-changin’. For statistical literacy, the very earth is moving under our feet (apologies to Carole King). The seismic forces are (i) new forms of communication and discourse and (ii) new forms of data, data display and human interaction with data. These upheavals in the worlds of communication and data are ongoing. If anything, the pace of change is accelerating. And with it, what it means to be statistically literate is also changing. So how can we tell what is important? We will air some enduring themes and guiding principles. First published May 2017 at Statistics Education Research Journal Archives

MORE THAN JUST NUMBERS: CHALLENGES FOR PROFESSIONAL STATISTICIANS

2017 ◽  
Vol 16 (2) ◽  
pp. 362-375
Author(s):  
CLAIRE CAMERON ◽  
ELLA IOSUA ◽  
MATTHEW PARRY ◽  
ROSALINA RICHARDS ◽  
CHRYSTAL JAYE
Keyword(s):  
Education Research ◽  
New Zealand ◽  
Communication Skills ◽  
Statistics Education ◽  
Statistical Literacy ◽  
Workforce Shortage ◽  
Research Journal ◽  
Qualitative Survey ◽  
The People ◽  
The Future

This paper describes a qualitative survey of professional statisticians carried out in New Zealand in 2014. The aim of the study was to find out if the issues this group faced were consistent with those identified in the literature. The issues identified were integrity, legitimacy, isolation, workforce shortage, communication, and marginalisation. They represent points of frustration for statisticians that may impact on the future of the profession as it responds to increasing demands and higher expectations. We found that these issues resonated for many of the statisticians included in our study and we have discussed a number of strategies to address them. They include raising our profile, attracting a broader range of people to the profession, increasing our communication skills, raising the statistical literacy of the people we work with, and a commitment to making it easy to engage with our colleagues. First published November 2017 at Statistics Education Research Journal Archives

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