Course Code: UZKA0BB06
ECTS: 6
Subject Description:
Sampling methods. Estimating single population parameters, estimating population variance, estimating two population parameters and population variance.
Estimation from stratified sample
Methods and steps of hypothesis testing; Type I and Type II errors in hypothesis testing. Hypothesis testing for one and two population parameters.
Non-parametric hypothesis testing: Contingency Analysis, One-way Analysis of Variance (ANOVA) and Goodness-of-Fit Test.
Simple correlation and regression analysis: interpretation and estimation of regression parameters. Linear, exponential and power regression functions.
Multiple correlation and regression: interpretation and estimation of regression parameters, reliability and testing of regression function, Analysis of Variance.
Time series analysis; components of time series, analytical trend, interpretation of the parameters of linear and exponential trend function, calculation of moving average.
Analysis of seasonality; Forecasting Time-Series Data, assumptions and features of forecasting
Statistics for Business (UZKA0BB06)(6cr)
Sampling methods. Estimating single population parameters, estimating population variance, estimating two population parameters and population variance.
Estimation from stratified sample
Methods and steps of hypothesis testing; Type I and Type II errors in hypothesis testing. Hypothesis testing for one and two population parameters.
Non-parametric hypothesis testing: Contingency Analysis, One-way Analysis of Variance (ANOVA) and Goodness-of-Fit Test.
Simple correlation and regression analysis: interpretation and estimation of regression parameters. Linear, exponential and power regression functions.
Multiple correlation and regression: interpretation and estimation of regression parameters, reliability and testing of regression function, Analysis of Variance.
Time series analysis; components of time series, analytical trend, interpretation of the parameters of linear and exponential trend function, calculation of moving average.
Analysis of seasonality; Forecasting Time-Series Data, assumptions and features of forecasting