Statistics in Criminology and Criminal Justice: Analysis and InterpretationJones & Bartlett Learning, 2005 - 423 lappuses Thoroughly updated and revised, this edition provides criminal justice students with a firm knowledge base in the theory and application of statistical analyses. Students will be introduced to methods of identifying and classifying data, followed by explanations and demonstrations of statistical procedures. They will learn what statistical techniques are appropriate for particular data, why procedures give the results they do, and how to interpret the output of statistical analyses. The book features updated statistical output, clear explanations of how to perform the analyses being discussed, revised data files, additional data sets to increase students' ability to conduct research on their own, and extensive use of flowcharts and examples to maximize students' comprehension of the topic. |
No grāmatas satura
1.–5. rezultāts no 85.
. lappuse
... Chapter Resources 79 4 Measures of Central Tendency Univariate Descriptive Statistics 83 Measures of Central Tendency 83 Mode 84 Median 89 Mean 95 Selecting the Most Appropriate Measure of Central Tendency 97 Conclusion 99 Chapter ...
... Chapter Resources 79 4 Measures of Central Tendency Univariate Descriptive Statistics 83 Measures of Central Tendency 83 Mode 84 Median 89 Mean 95 Selecting the Most Appropriate Measure of Central Tendency 97 Conclusion 99 Chapter ...
. lappuse
... Chapter Resources 123 6 The Form of a Distribution Moments of a Distribution 129 Number of Modes 130 Skewness 130 Analysis of Skew 131 Kurtosis 133 Analysis of Kurtosis 134 The Importance of Skew and Kurtosis Design of the Normal Curve ...
... Chapter Resources 123 6 The Form of a Distribution Moments of a Distribution 129 Number of Modes 130 Skewness 130 Analysis of Skew 131 Kurtosis 133 Analysis of Kurtosis 134 The Importance of Skew and Kurtosis Design of the Normal Curve ...
. lappuse
... Chapter Resources 192 201 What Is Association ? 201 Nominal Level Data 205 Ordinal Level Data 209 Tau 214 Gamma 221 Somers ' d 223 Spearman's Rho 226 Interval Level Data 229 Pearson's r 231 Conclusion : Selecting the Most Appropriate ...
... Chapter Resources 192 201 What Is Association ? 201 Nominal Level Data 205 Ordinal Level Data 209 Tau 214 Gamma 221 Somers ' d 223 Spearman's Rho 226 Interval Level Data 229 Pearson's r 231 Conclusion : Selecting the Most Appropriate ...
. lappuse
... Chapter Resources 274 Regression Regression 277 Assumptions 279 Analysis and Interpretation 282 Steps in OLS Regression Analysis 286 Other OLS Regression Information Limitations of OLS Regression 291 Multicollinearity 291 Assessing ...
... Chapter Resources 274 Regression Regression 277 Assumptions 279 Analysis and Interpretation 282 Steps in OLS Regression Analysis 286 Other OLS Regression Information Limitations of OLS Regression 291 Multicollinearity 291 Assessing ...
. lappuse
... Chapter Resources 380 17 Analysis of Variance ( ANOVA ) ANOVA 383 Assumptions 384 Calculation and Interpretation 385 Post Hoc Tests Conclusion 391 390 Chapter Resources 392 383 18 Putting It All Together 395 The Relationship Between ...
... Chapter Resources 380 17 Analysis of Variance ( ANOVA ) ANOVA 383 Assumptions 384 Calculation and Interpretation 385 Post Hoc Tests Conclusion 391 390 Chapter Resources 392 383 18 Putting It All Together 395 The Relationship Between ...
Saturs
Measures of Central Tendency | 83 |
Measures of Dispersion | 107 |
The Form of a Distribution | 129 |
Introduction to Bivariate Descriptive Statistics | 149 |
Measures of Existence and Statistical Significance | 167 |
Tobit Regression | 319 |
Known Probability of Error | 364 |
Chisquare Test for Independence | 377 |
Analysis of Variance ANOVA | 383 |
392 | |
Bieži izmantoti vārdi un frāzes
ANOVA assuming the null assumption calculated cell central tendency Chapter Resources chart Chi-square coefficient column Correlation criminal justice critical value crosstab data set deadly force degrees of freedom delinquents dependent variable determine dichotomous difference discussed in Chapter examine example Expected Count Figure formula Frequency Percent Gamma graphs groups hypothesis testing important independent inferential analyses interpretation interval level data juvenile Kurtosis Lambda level of measurement logistic regression logit mean measure of central measures of association median mode multicollinearity multivariate nominal level nominal level data normal curve null hypothesis OLS regression one-tailed ordinal level data Pearson's percentage police perform predicting probability problem ratio level data Recoded VICTIM reject the null relationship respondent sampling distribution scores Select skewed Spearman's Rho SPSS square standard deviation standard error statistical analysis statistical procedures statistically significant step t-test theory tion Total Type II error univariate Valid variance Z score