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Significance Testing (Statistical Associates Blue Book Series 18) (English Edition) [Formato Kindle]

G. David Garson

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Significance Testing: Parametric and Nonparametric

A statistical significance coefficient is the chance that a relationship as strong or stronger than the one observed was due to the chance of random sampling. Thus if a correlation coefficient is significant at exactly the .05 level, this means there is 5% chance that a correlation as strong or stronger than the observed one would result from an unusual random sampling of data when in fact the correlation was zero. There are many, many specific significance tests. Common tests are listed below, but in addition each statistical procedure has associated significance tests which are discussed in the respective Statistical Associates "Blue Book" volumes dealing with each procedure.

The full content is now available from Statistical Associates Publishers: http://www.statisticalassociates.com.

Below is the unformatted table of contents.

Table of Contents

Significance Testing 15
Overview 15
Types of significance tests 15
Parametric tests 15
Key Concepts and Terms 16
When significance testing applies 16
Significance and Type I Errors 19
Confidence limits 19
Power and Type II Errors 20
One-tailed vs. two-tailed tests 20
Assumptions of significance testing in general 22
Random sampling 22
Adequate sample size 22
Significance is not importance 22
À priori testing 23
Appropriate alpha significance level 23
Absence of intervening and common anteceding causes 23
Frequently asked questions about significance testing in general 23
How is significance related to effect size? 24
Should I "fail to accept" or should I "reject" the null hypothesis? 24
If cases in my sample are weighted, am I getting accurate significance values? 24
Is significance the same for multistage random samples as for simple random samples? 24
Binomial Test of Significance 26
Overview 26
Key Concepts and Terms 26
Implementing the binomial test in SPSS 27
Selections 27
Normal approximation of the binomial test 30
Assumptions of the binomial test 31
Dichotomous distribution 31
Data distribution 31
Random sampling 31
Student's t-Test of Difference of Means 32
Overview of the t-test 32
SPSS t-test types 32
Key Concepts and Terms 33
Formula 33
Critical value 33
Confidence limits 34
One-sample t-test 34
Example 34
Interpretation 35
Independent sample t-test 35
Example 36
Interpretation (with Levene's test) 36
The independent samples assumption 37
Paired sample t-test for non-independent samples 37
Overview 37
Example 38
Interpretation 38
Assumptions for t-tests 39
Normal distribution 39
Random sampling 39
Similar variances 39
Dependent/independent samples 40
Effect size measures 40
Frequently Asked Questions 40
What are common alternatives to the t-test? 40
What non-parametric test do I use instead of the t-test if my data cannot meet the assumption of normality? 41
Normal Curve Tests of Means and Proportions 42
Overview 42
Key Concepts and Terms 42
Deviation scores 42
Standard deviation 42
Variance 43
Standard error 43
Confidence limits 43
Binomial distribution 44
Normal distribution 44
Normal curve means tests ("hypothesis tests") 46
Confidence interval 47
Manual computation of z values for normal curve tests 49
Assumptions for normal curve tests 50
Interval data 51
Sample size should not be small 51
Homogeneity of variances 51
Random sampling 51
Chi-Square Significance Tests 52
Overview 52
Pearson's chi-square 52
Overview 52
SPSS output 53
Yates correction for continuity 56
Crosstabulation control variables and chi-square 57
Chi-square goodness-of-fit test 58
Likelihood ratio chi-square 61
Mantel-Haenszel (linear by linear) chi-square 62
Assumptions for chi-square tests 63
Random sampling 63
Independence 64
Known distribution 64
Non-directional hypotheses 64
Finite values 64
Normal distribution of deviations 64
Data level 64
Frequently asked questions about chi-square 65
and 165 more pages of topics on significance testing.

Dettagli prodotto

  • Formato: Formato Kindle
  • Dimensioni file: 6528 KB
  • Lunghezza stampa: 228
  • Editore: Statistical Associates Publishers; 1 edizione (26 agosto 2012)
  • Venduto da: Amazon Media EU S.à r.l.
  • Lingua: Inglese
  • ASIN: B0092TUPUA
  • Da testo a voce: Abilitato
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  • Posizione nella classifica Bestseller di Amazon: #191.813 a pagamento nel Kindle Store (Visualizza i Top 100 a pagamento nella categoria Kindle Store)

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3.0 su 5 stelle good enough 1 giugno 2014
Di rw#5 - Pubblicato su Amazon.com
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helped me to understand concepts better and price was good too. GOOD FOR THE BEGINNER BECAUSE IT HELPS SET THE PACE
5.0 su 5 stelle Very Good e-book 29 agosto 2013
Di Jorge De Leon - Pubblicato su Amazon.com
Formato:Formato Kindle|Acquisto verificato
Currently I am teaching in Med. School, at San Carlos University, Guatemala. This course is for Associate and Professors, They don't need all the theory and formulas, they need to know how to do the analysis of their data, and all the variants they have. So this book is very useful for this purpose. In general this book can be used for any kind of postgraduate course

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