Course outline
1
DATA AND SAMPLING
1.1
Types of data
1.2
Levels of measurement
1.3
Structure of the data
1.4
Key terms
1.5
Sampling techinques
1.6
Presenting data with tables and charts
1.7
Describing data numerically
Practices - part I
2
PROBABILITY
2.1
Undestanding terminology
2.2
Contigency table and probability
2.3
Random variables and probability distributions
2.4
Application to portfolio management
2.5
Applications of Binomial distribution
2.6
Applications of Poisson distribution
2.7
Applications of normal (Gaussian) distribution
Practices - part II
3
HYPOTHESIS TESTING
3.1
Single population mean
3.2
Two population means
3.3
Single population proportion
3.4
Two population proportions
3.5
Single population variance
3.6
Two population variances
Practices - part III
4
REGRESSION ANALYSIS
4.1
Sample regression line
4.2
Least squares estimates
4.3
Variables selection and transformation
4.4
Significance testing
Practices - part IV
5
BUSINESS FORECASTING
5.1
Qualitative methods
5.2
Time-series models
5.3
Decomposition of a time-series
5.4
Forecast horizon and form
5.5
Choice of the forecasting model
5.6
Forecast accuracy
6
DECISION MAKING
7
QUALITY CONTROL
Business Statistics
Practices - part IV