Applied statistics for public policy /
by Macfie, Brian P; Nufrio, Philip M.
Material type:
BookPublisher: Armonk, N.Y. : M.E. Sharpe, c2006; New Delhi : Printice-Hall, 2006Description: xv, 536 p. : ill. ; 26 cm.ISBN: 0765612399 (cloth : alk. paper); 812032904X.Subject(s): Social sciences -- Statistical methods | Political statisticsOnline resources: Table of contents | Item type | Current location | Collection | Call number | Copy number | Status | Date due | Barcode |
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Dhaka University Science Library General Stacks | Non Fiction | 519.5 MAA (Browse shelf) | 1 | Available | 424165 |
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| 519.5 M133g Generalized linear models / | 519.5 M465b Basic statistics in behavioural research / | 519.5 MAA Applied statistics : | 519.5 MAA Applied statistics for public policy / | 519.5 MAD Distribution-free statistical methods / | 519.5 MAD Distribution-free statistical methods / | 519.5 MAF Families of bivariate distributions / |
Includes bibliographical references and index.
Unit I. Descriptive statistics -- Introduction : what is statistics all about? -- Using polystat to do statistical analysis -- Presentation of data -- Summarizing data and using descriptive statistics -- Unit II. Basic probability and probability distributions -- Basic probability : theory and applications -- Sampling and the normal distribution -- The central limit theorem -- Unit III. Hypothesis testing -- Introduction to inferential statistics -- Estimating means, proportions, and sample size with confidence -- Validating a hypothesis about a single population mean using a sample -- Validating hypotheses between two population means -- Validating hypotheses about a single population proportion -- Validating hypotheses about two population proportions -- Unit IV. Measures of association -- Comparing more than two population means with anova -- Comparing more than two population proportions using the chi-square test -- Determining relationships for two variables using correlation -- Measuring relationships with simple regression analysis -- Measuring multivariate relationships with regression analysis -- Planning statistical research.
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