dc.contributor.author | Heiberger, Richard M. | |
dc.contributor.author | Holland, Burt | |
dc.date.accessioned | 2020-04-29T09:54:51Z | |
dc.date.available | 2020-04-29T09:54:51Z | |
dc.date.issued | 2015 | |
dc.identifier.isbn | 978-1-4939-2122-5 | |
dc.identifier.uri | http://ir.mksu.ac.ke/handle/123456780/6032 | |
dc.description.abstract | Students seeking master’s degrees in applied statistics in the late 1960s and 1970s
typically took a year-long sequence in statistical methods. Popular choices of the
course textbook in that period prior to the availability of high-speed computing and
graphics capability were those authored by Snedecor and Cochran (1980) and Steel
and Torrie (1960).
By 1980, the topical coverage in these classics failed to include a great many
new and important elementary techniques in the data analyst’s toolkit. In order to
teach the statistical methods sequence with adequate coverage of topics, it became
necessary to draw material from each of four or five text sources. Obviously, such a
situation makes life difficult for both students and instructors. In addition, statistics
students need to become proficient with at least one high-quality statistical software
package.
This book Statistical Analysis and Data Display can serve as a standalone text
for a contemporary year-long course in statistical methods at a level appropriate for
statistics majors at the master’s level and for other quantitatively oriented disciplines
at the doctoral level. The topics include concepts and techniques developed many
years ago and also a variety of newer tools.
This text requires some previous studies of mathematics and statistics. We suggest
some basic understanding of calculus including maximization or minimization
of functions of one or two variables, and the ability to undertake definite integrations
of elementary functions. We recommend acquired knowledge from an earlier
statistics course, including a basic understanding of statistical measures, probability
distributions, interval estimation, hypothesis testing, and simple linear regression. | en_US |
dc.language.iso | en_US | en_US |
dc.publisher | Springer | en_US |
dc.relation.ispartofseries | Springer Texts in Statistics; | |
dc.subject | Mathematical statistics--Data processing | en_US |
dc.subject | R (Computer program language) | en_US |
dc.subject | Statistics--Data processing | en_US |
dc.title | Statistical Analysis and Data Display | en_US |
dc.title.alternative | An Intermediate Course with Examples in R | en_US |
dc.type | Book | en_US |