Cantitate/Preț
Produs

Understanding Significance Testing: Quantitative Applications in the Social Sciences, cartea 73

Autor Lawrence B. Mohr
en Limba Engleză Paperback – 9 apr 1990
Significance testing - a core technique in statistics for hypothesis testing - is introduced in this volume. Mohr first reviews what is meant by sampling and probability distributions and then examines in-depth normal and t-tests of significance. The uses and misuses of significance testing are also explored.
Citește tot Restrânge

Toate formatele și edițiile

Toate formatele și edițiile Preț Express
Paperback (1) 33576 lei  6-8 săpt.
  SAGE Publications – 9 apr 1990 33576 lei  6-8 săpt.
Electronic book text (1) 11433 lei  Precomandă
  SAGE Publications – 29 apr 1990 11433 lei  Precomandă

Din seria Quantitative Applications in the Social Sciences

Preț: 33576 lei

Nou

Puncte Express: 504

Preț estimativ în valută:
5942 6969$ 5210£

Carte tipărită la comandă

Livrare economică 24 ianuarie-07 februarie 26

Preluare comenzi: 021 569.72.76

Specificații

ISBN-13: 9780803935686
ISBN-10: 0803935684
Pagini: 80
Ilustrații: 1, black & white illustrations
Dimensiuni: 140 x 216 x 6 mm
Greutate: 0.12 kg
Ediția:Will Be Reissue.
Editura: SAGE Publications
Colecția Sage Publications, Inc
Seria Quantitative Applications in the Social Sciences

Locul publicării:Thousand Oaks, United States

Cuprins

Introduction
Some Definitions
The Sampling Distribution
Interval Estimation
Significance Testing
The Functions of the Test

Notă biografică

Professor Mohr is currently working on a theoretical paper in program evaluation called An Exploration in the Theory of Valuing and a research monograph called The Impacts of Sponsored Research Dollars on Academic Institutions. The next project will be an edited volume with critique called The Case Study As a Research Design in Social Science.

Descriere

Significance testing - a core technique in statistics for hypothesis testing - is introduced in this volume. Mohr first reviews what is meant by sampling and probability distributions and then examines in-depth normal and t-tests of significance. The uses and misuses of significance testing are also explored.