Statistics and data interpretation for social work
Social sciences Social service Statistics MATHEMATICS / Probability & Statistics / General sähkökirjat
Springer Pub. Co.
2012
1st ed.
EISBN 9780826107213
Pt. I: Introduction and descriptive statistics. Introduction and overview.
Data presentation.
Central tendency.
Measures of variability.
Shape of distribution.
The concept of relationship and relationship between categorical variables.
The odds ratio and other measures for categorical variables.
Correlation and regression.
Standardized mean difference.
Research design and causality.
Controlling for confounding variables.
Pt. II: Inferential statistics and data interpretation. An introduction to inferential statistics.
Confidence intervals for means and proportions.
The logic of statistical significance tests.
The large sample test of the mean and new concepts.
Statistical power and selected topics.
The t distribution and one-sample procedures for means.
Independent samples t test and dependent samples t test.
One-sample tests of proportions.
The chi-square test of independence.
Analysis of variance.
More significance tests and reasoning with test results.
An overview of selected multivariate procedures.
Generalizability, importance, and a data interpretation model.
Data presentation.
Central tendency.
Measures of variability.
Shape of distribution.
The concept of relationship and relationship between categorical variables.
The odds ratio and other measures for categorical variables.
Correlation and regression.
Standardized mean difference.
Research design and causality.
Controlling for confounding variables.
Pt. II: Inferential statistics and data interpretation. An introduction to inferential statistics.
Confidence intervals for means and proportions.
The logic of statistical significance tests.
The large sample test of the mean and new concepts.
Statistical power and selected topics.
The t distribution and one-sample procedures for means.
Independent samples t test and dependent samples t test.
One-sample tests of proportions.
The chi-square test of independence.
Analysis of variance.
More significance tests and reasoning with test results.
An overview of selected multivariate procedures.
Generalizability, importance, and a data interpretation model.
