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Statistics training with Excel. Basic quantitatve analyses of realistic economic data with complete solutions. (Statistik-Praktikum mit Excel. Grundlegende quantitative Analysen realistischer Wirtschaftsdaten mit vollständigen Lösungen.) 2nd revised and extended ed. (German)
Studienbücher Wirtschaftsmathematik. Wiesbaden: Springer Spektrum (ISBN 978-3-658-04186-1/pbk; 978-3-658-04187-8/ebook). xi, 469~p. (2015).
Classification: K40 K70 U70 K80 M40 M30
101
Using the five practices model to promote statistical discourse. (English)
Teach. Stat. 37, No. 1, 13-17 (2015).
Classification: D50 K40 K70 D50
102
Nothing new at the temperatures? Statistical literacy in the age of computer simulations. (Nichts Neues bei den Temperaturen? Statistical Literacy im Zeitalter der Computersimulationen.) (German)
Stoch. Sch. 35, No. 1, 2-6 (2015).
Classification: K90 M50 K40 U70
103
TeMaDi ‒ test for mathematical diagram understanding. Test folder with test manual, 5 test booklets and 3 transparencies. (TeMaDi ‒ Test zum mathematischen Diagrammverständnis. Testmappe mit Testmanual, 5 Testheften und 3 Folien.) (German)
Münster: WTM-Verlag. not consecutively paged. (2015).
Classification: D60 K40
104
Proper and paradigmatic metonymy as a lens for characterizing student conceptions of distributions and sampling. (English)
Educ. Stud. Math. 88, No. 3, 361-383 (2015).
Classification: K70 K40 C30 C50
105
Developing students’ reasoning about samples and sampling variability as a path to expert statistical thinking. (English)
Educ. Stud. Math. 88, No. 3, 327-342 (2015).
Classification: K70 K40
106
Learning to reason from samples: commentary from the perspectives of task design and the emergence of “big data". (English)
Educ. Stud. Math. 88, No. 3, 405-412 (2015).
Classification: K40 K70 K80 E20
107
Data seen through different lenses. (English)
Educ. Stud. Math. 88, No. 3, 305-325 (2015).
Classification: K40 K70
108
Learning to reason from samples. (English)
Educ. Stud. Math. 88, No. 3, 291-303 (2015).
Classification: A60 K40 K70 K80
109
What is “typical” for different kinds of data? Examples from the Melbourne cup. (English)
Aust. Math. Teach. 70, No. 2, 33-40 (2014).
Classification: K40
110
Ethics in statistics. (English)
Aust. Sr. Math. J. 28, No. 1, 38-42 (2014).
Classification: K40 K70 K80 D20 E20
111
Purposeful statistical investigations. (English)
Aust. Prim. Math. Classr. 19, No. 3, 20-26 (2014).
Classification: K40 U70
112
Meaningful statistics in professional practices as a bridge between mathematics and science: an evaluation of a design research project. (English)
Int. J. STEM Educ. 1, No. 1, Paper No. 9, 15 p., electronic only (2014).
Classification: K40 K70 M50 M60
113
Enhancing the teaching and learning of mathematical visual images. (English)
Aust. Math. Teach. 70, No. 1, 18-25 (2014).
Classification: D30 D40 K40
114
Australian curriculum linked lessons: statistics. (English)
Aust. Prim. Math. Classr. 19, No. 4, 20-23 (2014).
Classification: D30 K40
115
Literacy, reasoning and statistical thinking with robots. (Literacia, raciocínio e pensamento estatístico com robots.) (Portuguese. English summary)
Quadrante 23, No. 2, 69-93 (2014).
Classification: K40 K70 M50 U70
116
Teaching and learning of statistical investigations: two case studies of future teachers. (Ensino e aprendizagem dc investigações estatísticas: dois estudos de caso com futuras professoras.) (Portuguese. English summary)
Quadrante 23, No. 2, 47-68 (2014).
Classification: K40
117
Witnesses. Pie charts. (Getuigen. Taartgrafieken.) (Dutch)
Euclides 89, No. 6, 18-19 (2014).
Classification: A30 K40
118
The influence of free agency on NHL player performance. (English)
J. Recreat. Math. 38, No. 2, 113-119 (2014).
Classification: M90 K40 K70
119
Should investors fear friday the 13th? (English)
J. Recreat. Math. 38, No. 2, 106-112 (2014).
Classification: M30 K40 K70
120

Result 101 to 120 of 1087 total

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