Leveled Texts for Mathematics: Data Analysis and Probability PDF Download

Author: Stephanie Paris
Publisher: Teacher Created Materials
ISBN: 9781425807559
Category : Education
Languages : en
Pages : 150

View

Book Description
With a focus on data analysis and probability, a guide to using leveled texts to differentiate instruction in mathematics offers fifteen different topics with high-interest text written at four different reading levels, accompanied by matching visuals and practice problems.

Author: Lori Barker
Publisher: Teacher Created Materials
ISBN: 9781425807153
Category : Education
Languages : en
Pages : 150

View

Book Description
With a focus on number and operations, a guide to using leveled texts to differentiate instruction in mathematics offers fifteen different topics with high-interest text written at four different reading levels, accompanied by matching visuals and practice problems.

Author: Lori Barker
Publisher: Teacher Created Materials
ISBN: 9781425807856
Category : Education
Languages : en
Pages : 150

View

Book Description
With a focus on fractions, decimals, and percents, a guide to using leveled texts to differentiate instruction in mathematics offers fifteen different topics with high-interest text written at four different reading levels, accompanied by matching visuals and practice problems.

Author: Stephanie Paris
Publisher: Teacher Created Materials
ISBN: 1425877427
Category : Mathematics
Languages : en
Pages : 9

View

Book Description
All students can learn about analyzing line graphs through text written at four different reading levels. Symbols on the pages represent reading-level ranges to help differentiate instruction. Provided comprehension questions complement the text.

Author: Stephanie Paris
Publisher: Teacher Created Materials
ISBN: 1425877400
Category : Mathematics
Languages : en
Pages : 9

View

Book Description
All students can learn about analyzing bar graphs through text written at four different reading levels. Symbols on the pages represent reading-level ranges to help differentiate instruction. Provided comprehension questions complement the text.

Author: Stephanie Paris
Publisher: Teacher Created Materials
ISBN: 1425877389
Category : Mathematics
Languages : en
Pages : 9

View

Book Description
All students can learn about analyzing pictographs through text written at four different reading levels. Symbols on the pages represent reading-level ranges to help differentiate instruction. Provided comprehension questions complement the text.

Author: Douglas Wolfe
Publisher: Springer Nature
ISBN: 3030474798
Category : Mathematics
Languages : en
Pages : 233

View

Book Description
This book is specially designed to refresh and elevate the level of understanding of the foundational background in probability and distributional theory required to be successful in a graduate-level statistics program. Advanced undergraduate students and introductory graduate students from a variety of quantitative backgrounds will benefit from the transitional bridge that this volume offers, from a more generalized study of undergraduate mathematics and statistics to the career-focused, applied education at the graduate level. In particular, it focuses on growing fields that will be of potential interest to future M.S. and Ph.D. students, as well as advanced undergraduates heading directly into the workplace: data analytics, statistics and biostatistics, and related areas.

Author: Norman Matloff
Publisher: CRC Press
ISBN: 0429687117
Category : Business & Economics
Languages : en
Pages : 295

View

Book Description
Probability and Statistics for Data Science: Math + R + Data covers "math stat"—distributions, expected value, estimation etc.—but takes the phrase "Data Science" in the title quite seriously: * Real datasets are used extensively. * All data analysis is supported by R coding. * Includes many Data Science applications, such as PCA, mixture distributions, random graph models, Hidden Markov models, linear and logistic regression, and neural networks. * Leads the student to think critically about the "how" and "why" of statistics, and to "see the big picture." * Not "theorem/proof"-oriented, but concepts and models are stated in a mathematically precise manner. Prerequisites are calculus, some matrix algebra, and some experience in programming. Norman Matloff is a professor of computer science at the University of California, Davis, and was formerly a statistics professor there. He is on the editorial boards of the Journal of Statistical Software and The R Journal. His book Statistical Regression and Classification: From Linear Models to Machine Learning was the recipient of the Ziegel Award for the best book reviewed in Technometrics in 2017. He is a recipient of his university's Distinguished Teaching Award.

Author: Stephanie Paris
Publisher: Teacher Created Materials
ISBN: 1425877443
Category : Mathematics
Languages : en
Pages : 9

View

Book Description
All students can learn about analyzing circle graphs through text written at four different reading levels. Symbols on the pages represent reading-level ranges to help differentiate instruction. Provided comprehension questions complement the text.

Author: John Tabak
Publisher: Infobase Publishing
ISBN: 0816068739
Category : Electronic books
Languages : en
Pages : 241

View

Book Description
Presents a survey of the history and evolution of the branch of mathematics that focuses on probability and statistics, including useful applications and notable mathematicians in this area.