1) Course Details

This course begins with a case study that clearly demonstrates why we need statistical data analysis methods. Then, it continues with the definition of different data types and, in its simplest form, the interpretation of the scatter plot graph showing the relationship between the two numerical data. Since the most common data type of a scientist working in experimental studies will be numerical data type, the normal distribution of numerical data is examined in detail. Inference from numerical data sets is discussed with confidence interval and hypothesis testing. Development of regression equations that predict the output variable using input variables are described. The topics covered are also supported by sample data sets that are processed with the help of a statistical software program.

 

 2) Course Aim

The aims of this course are:

a)    To introduce the basics of the statistics science,

b)    to create awareness about experimental design and sampling in order to obtain reliable data from experimental studies,

c)    To introduce the statistical methods to be used in the analysis of the data obtained from the experiments.

 

 3) Who Is This Course For?

This course is for scientists with a spirit of research and development who want to draw causal conclusions between variables through experimental studies and develop products and processes at the desired level.

 

4) What Skills Do I Need?

There is no need to know advanced math for this course. It is a course that any undergraduate graduate can easily understand and apply to their field of study.

 

5) How Does the Course Work?

The course consists of lectures and sample data sets for the application of lectures in a statistical analysis software package.

 

6) What You'll Get

The person taking this course will learn how to use statistical methods in the planning, implementation and analysis of the experimental work.

Description: Statistics and Data Analysis