Empirical research I
1. Background Reading
▪ Descriptive statistics
• Describe and explore data at hand
• Empirical distributions, measures of central tendency, variability, skewness,
correlations
▪ Inferential statistics
• Infer beyond data at hand (from sample to population)
• Testing hypotheses and deriving estimates
• Deal with conclusions under uncertainty
▪ Data is a set of values of subjects with respect to qualitative or quantitative variables.
▪ A Population is the entirety of all people, items or events we want to infer about (defined by
the analyst)
▪ Elements/Cases are the entities on which data are collected.
▪ A variable is a characteristic of interest of the elements (In a data table, elements are rows,
variables are columns.)
▪ A sample is a subset of elements/cases (e.g., people, items, or events) from a population
Standard deviation:
Variance = stdev squared
▪ quantiles are data (cutoff) values dividing the observed data distribution in intervals
containing a specific proportion of all observed data values.
▪ Common quantiles have special names: for instance quartile, decile, percentile.
▪ The x% percentile (or a centile) is a data value for which x% of all observed data are smaller
(or equal).
▪ 1 quartile = 0.25 quantile = 25 percentile
▪ 2 quartile = .5 quantile = 50 percentile (median)
▪ 3 quartile = .75 quantile = 75 percentile
, 2. First lecture slides
T-Test
1. Background Reading
▪ Descriptive statistics
• Describe and explore data at hand
• Empirical distributions, measures of central tendency, variability, skewness,
correlations
▪ Inferential statistics
• Infer beyond data at hand (from sample to population)
• Testing hypotheses and deriving estimates
• Deal with conclusions under uncertainty
▪ Data is a set of values of subjects with respect to qualitative or quantitative variables.
▪ A Population is the entirety of all people, items or events we want to infer about (defined by
the analyst)
▪ Elements/Cases are the entities on which data are collected.
▪ A variable is a characteristic of interest of the elements (In a data table, elements are rows,
variables are columns.)
▪ A sample is a subset of elements/cases (e.g., people, items, or events) from a population
Standard deviation:
Variance = stdev squared
▪ quantiles are data (cutoff) values dividing the observed data distribution in intervals
containing a specific proportion of all observed data values.
▪ Common quantiles have special names: for instance quartile, decile, percentile.
▪ The x% percentile (or a centile) is a data value for which x% of all observed data are smaller
(or equal).
▪ 1 quartile = 0.25 quantile = 25 percentile
▪ 2 quartile = .5 quantile = 50 percentile (median)
▪ 3 quartile = .75 quantile = 75 percentile
, 2. First lecture slides
T-Test
