HR Statistical Techniques
Code  Completion  Credits  Range  Language 

51XPNSMP  Z,ZK  4  2P+1C  Czech 
 Lecturer:
 Tutor:
 Supervisor:
 Department of Pedagogical and Psychological Studies
 Synopsis:

The Bc course in Statistical methods in HR management at Masaryk Institute of Advanced Studies will aim to train you to solve realworld statistical problems. The course has a particular focus on modern computationallyintensive methods and their use in the analysis of data. Topics include basic statistical principles; graphic presentation; descriptive measures of central tendency, dispersion, and location; inferential statistics and hypothesis testing; analysis and inference of linear correlation coefficient, slope of regression line, design od experiments, response surface methodology, robust design, random effects model, and statistics quality control methods. Students will apply statistical concepts to real world situations. Current technology will be utilized in examining statistical information.
 Requirements:
 Syllabus of lectures:

This course covers the following topics:
An overview of statistics,
Data description: scales of measurement, how to describe data graphically for categorical data (pie chart, bar chart) and graphs for quantitative variables (histogram, stemandleaf plot and time plot)
How to describe data by summary statistics: measures of central tendency and variability
How probability and probability distributions are involved in statistics
How binomial distributions are involved in statistics
The role that normal distributions play in statistics
Simple random sampling and sampling distribution of sample mean, central limit theorem, normal approximation to the binomial
Confidence interval for population mean, Sample size needed for estimating the population mean with a specified confidence level and specified width of the interval
Hypothesis testing: in terms of how to set up Null and Alternative hypotheses, understanding Type I and Type II errors, performing a statistical test for the population mean
How to compute power of a test and choosing the sample size for testing population mean
pvalue, how to compute it and how to use it
How to compare the mean of two populations for independent samples: using pooled variances ttest versus separate variances ttest
How to compare the mean of two populations for paired data
How to compare two population proportions
Using contingency table and the Chisquare test of independence
Using an Ftest to compare the variances of two populations
Analyzing data using multiple regression methods links.
 Syllabus of tutorials:

1. Random variables, numerical characteristics
2. Regression and correlation analysis
3. Statistical testing of hypothesis
4. Design of Experiments: binary form factorial designs
5. Robust Design
6. Statistical quality control
 Study Objective:
 Study materials:

1. Kožíšek, J., Stieberová, B.: Statistika v příkladech, Verlag Dashofer, Praha 2012.
2. Hindls, R., Hronová, S. et al. Statistika pro ekonomy. Professional publishing. 2007
 Note:
 Further information:
 No timetable has been prepared for this course
 The course is a part of the following study plans:

 BPMprez.forma od 10/11 (compulsory elective course)
 BPMprez.forma od 11/12 (compulsory elective course)
 BPMprez.forma od 12/13 (compulsory elective course)
 BPMprez.forma od 13/14 (compulsory elective course)
 BPMprez. forma od 14/15 (compulsory elective course)