Data Analysis

The main purpose of this course is to present techniques of collecting and analyzing data. Quality and representativeness of data is a prerequisite for the success of a research. In this context, the design of a sample and the various sampling techniques, such as random, stratified, cluster and systematic, are presented. The collection of data is followed by the exploration of correlations, independency tests, investigation of the linearity of their relationship, etc. The techniques used for this purpose are presented and applied using the statistical package SPSS and Minitab. Finally, as part of the course case studies are presented, which include the design of the sample to the requirements of each study, the processing of data and finally the presentation of the results.

Objectives

Upon completion of the learning process the student will be able To know how to plan a survey To identify and choose the sampling techniques To identify data analysis techniques To process data by using modern statistical software To present the results of data analysis and To interpret the results of data analysis.

Prerequisites

Adequate knowledge of basic statistics (statistics a and b)

Syllabus

Judgmental sampling Simple Random Sampling Stratified Sampling Systetimatic Sampling Cluster Sampling Introduction to SPSS Descriptive Statistics and Graphs Hypothesis Testing Analysis of Variance Simple Linear Regression and Correlation Multiple Regression