The aim of the course is to introduce the student to the techniques of statistical inference mainly used in the social sciences, giving greater emphasis to the understanding of concepts rather than mathematical formalization.
At the end of the course the student:
- has become familiar with the basic concepts of Statistical Inference
- is able to perform analysis of inferential data and use the main statistical mode
At the end of the course the student:
- has become familiar with the basic concepts of Statistical Inference
- is able to perform analysis of inferential data and use the main statistical mode
teacher profile teaching materials
- Frequency distributions: absolute frequencies, relative frequencies, percentages, cumulated frequencies. Classes of modalities for quantitative variables.
- Statistical plots: bar charts, pie charts, stem and leaf, histograms, time series plot.
- Position indexes: mean, median, mode. Position index properties.
- Variability indexes: variance, standard deviation, coefficient of variation, range. Concentration.
- Box-plot
- Data transformation. Linear transformation. Standardization.
- Contingency tables. Pearson chi-square index. Independence and dependence on average.
- Covariance and correlation.
- Simple linear regression model.
- Statistical indexes for social science.
The course will focus on the main statistical function on Excel. In particular:
Pivot tables . Plots: bar charts, pie charts, histograms, plots for two variables. Position indexes: mean, mediann and mode. Variability indexes: variance and deviazione standard. Covariance, correlation, regression.
or, in alternative,
Diamond I., Jefferies J. (2001). Introduzione alla Statistica per le Scienze Sociali, McGraw-Hill, Milano.
For the course of Laboratory of Data Analysis students can refer to the Prof.ssa Marella's material available on her web site.
Programme
- Introduction.- Frequency distributions: absolute frequencies, relative frequencies, percentages, cumulated frequencies. Classes of modalities for quantitative variables.
- Statistical plots: bar charts, pie charts, stem and leaf, histograms, time series plot.
- Position indexes: mean, median, mode. Position index properties.
- Variability indexes: variance, standard deviation, coefficient of variation, range. Concentration.
- Box-plot
- Data transformation. Linear transformation. Standardization.
- Contingency tables. Pearson chi-square index. Independence and dependence on average.
- Covariance and correlation.
- Simple linear regression model.
- Statistical indexes for social science.
The course will focus on the main statistical function on Excel. In particular:
Pivot tables . Plots: bar charts, pie charts, histograms, plots for two variables. Position indexes: mean, mediann and mode. Variability indexes: variance and deviazione standard. Covariance, correlation, regression.
Core Documentation
Monti A.C. (2009). Statistica per le Scienze Giuridiche e Sociali, ESI, Napoli.or, in alternative,
Diamond I., Jefferies J. (2001). Introduzione alla Statistica per le Scienze Sociali, McGraw-Hill, Milano.
For the course of Laboratory of Data Analysis students can refer to the Prof.ssa Marella's material available on her web site.
Reference Bibliography
Monti A.C. (2009). Statistica per le Scienze Giuridiche e Sociali, ESI, Napoli. or, in alternative, Diamond I., Jefferies J. (2001). Introduzione alla Statistica per le Scienze Sociali, McGraw-Hill, Milano. For the course of Laboratory of Data Analysis students can refer to the Prof.ssa Marella's material available on her web site.Type of delivery of the course
traditionalAttendance
optionalType of evaluation
Multiple choice test. Analysis of a data matrix.