Applied statistics I : basic bivariate techniques /
Warner, Rebecca M.,
Applied statistics I : basic bivariate techniques / Rebecca M. Warner, Professor Emerita, University of New Hampshire. - Third Edition. - California : SAGE Publications, Inc , @ 2021 - xxiv, 623 pages : illustrations ; 25 cm
Revised edition of the author's Applied statistics, c2013.
Includes bibliographical references.
Chapter 1: Evaluating Numerical Information.-- Chapter 2: Basic Research Concepts.-- Chapter 3: Frequency Distribution Tables.-- Chapter 4: Descriptive Statistics.-- Chapter 5: Graphs: Bar Charts, Histograms and Boxplots.-- Chapter 6: The Normal Distribution and zScores.-- Chapter 7: Sampling Error and Confidence Intervals.-- Chapter 8: The One-Sample tTest: Introduction.-- Chapter 9: Issues in Significance Test: Effects Size, Statistical Significance Test.-- Chapter 9: Issues significance Tests: Effect Size: Statistical; Power, and Decision Errors.-- Chapter 10: Bivariate Pearson Correlation.-- Chapter 11: Bivariate Regression.-- Chapter 12: The Independent-Samples tTest.-- Chapter 13: One-Way Between-Subjects Analysis of Variance.-- Chapter 14: Paired-Samples tTest.-- Chapter 15: One-Way Repeated-Measures Analysis of Variance.-- Chapter 16: Factorial Analysis of Variance.-- Chapter 17: Chi-Square Analysis of Contingency Tables
"Applied Statistics I: Basic Bivariate Techniques has been created from the first half of Rebecca M. Warner's popular Applied Statistics: From Bivariate Through Multivariate Techniques. The author's contemporary approach differs from some of the well-worn texts in the market, and reflects current thinking in the field. It spends less time on statistical significance testing, and moves in the direction of the "new statistics" by focusing more on confidence intervals and effect size. Instructors of upper undergraduate or beginning graduate level courses will find that the greater focus on basic concepts such as partition of variance and effect size is more useful to students, particularly as preparation for more advanced courses. Spending less time on statistical significance testing allows for more time to be devoted to more interesting and useful statistics that students will see in journal articles (such as correlation and regression). This introductory statistics text includes examples in SPSS, together with datasets on an accompanying website. A companion study guide reproducing the exercises and examples in R will also be available"--
9781506352800
2019046882
Social sciences--Statistical methods.
Psychology--Statistical methods.
Multivariate analysis.
STA340
HA31.35 / .W37 2021
519.5/35
Applied statistics I : basic bivariate techniques / Rebecca M. Warner, Professor Emerita, University of New Hampshire. - Third Edition. - California : SAGE Publications, Inc , @ 2021 - xxiv, 623 pages : illustrations ; 25 cm
Revised edition of the author's Applied statistics, c2013.
Includes bibliographical references.
Chapter 1: Evaluating Numerical Information.-- Chapter 2: Basic Research Concepts.-- Chapter 3: Frequency Distribution Tables.-- Chapter 4: Descriptive Statistics.-- Chapter 5: Graphs: Bar Charts, Histograms and Boxplots.-- Chapter 6: The Normal Distribution and zScores.-- Chapter 7: Sampling Error and Confidence Intervals.-- Chapter 8: The One-Sample tTest: Introduction.-- Chapter 9: Issues in Significance Test: Effects Size, Statistical Significance Test.-- Chapter 9: Issues significance Tests: Effect Size: Statistical; Power, and Decision Errors.-- Chapter 10: Bivariate Pearson Correlation.-- Chapter 11: Bivariate Regression.-- Chapter 12: The Independent-Samples tTest.-- Chapter 13: One-Way Between-Subjects Analysis of Variance.-- Chapter 14: Paired-Samples tTest.-- Chapter 15: One-Way Repeated-Measures Analysis of Variance.-- Chapter 16: Factorial Analysis of Variance.-- Chapter 17: Chi-Square Analysis of Contingency Tables
"Applied Statistics I: Basic Bivariate Techniques has been created from the first half of Rebecca M. Warner's popular Applied Statistics: From Bivariate Through Multivariate Techniques. The author's contemporary approach differs from some of the well-worn texts in the market, and reflects current thinking in the field. It spends less time on statistical significance testing, and moves in the direction of the "new statistics" by focusing more on confidence intervals and effect size. Instructors of upper undergraduate or beginning graduate level courses will find that the greater focus on basic concepts such as partition of variance and effect size is more useful to students, particularly as preparation for more advanced courses. Spending less time on statistical significance testing allows for more time to be devoted to more interesting and useful statistics that students will see in journal articles (such as correlation and regression). This introductory statistics text includes examples in SPSS, together with datasets on an accompanying website. A companion study guide reproducing the exercises and examples in R will also be available"--
9781506352800
2019046882
Social sciences--Statistical methods.
Psychology--Statistical methods.
Multivariate analysis.
STA340
HA31.35 / .W37 2021
519.5/35