ESME506 QUANTITATIVE DATA ANALYSIS IN EDUCATION
Course Code: | 8220506 |
METU Credit (Theoretical-Laboratory hours/week): | 4 (3.00 - 2.00) |
ECTS Credit: | 10.0 |
Department: | Elementary Science and Math. E. |
Language of Instruction: | English |
Level of Study: | Graduate |
Course Coordinator: | Prof.Dr. SEMRA SUNGUR |
Offered Semester: | Fall Semesters. |
Course Objectives
Comprehend basic concepts in statistics
Develop skills in understanding and applying descriptive statistical techniques.
Develop skills in understanding and applying inferential statistical techniques
Comprehend statistical assumptions
Understand standardized distributions (z-scores)
Understand the concept of the distribution of sample means and z for a sample mean
Develop an ability to use computers for statistical analysis of data.
Course Content
This course focuses on understanding and application of basic concepts and principles of descriptive and inferential statistics pertaining educational research. Topics covered in this course include review of descriptive statistics, correlation and regression analyses, and comparisons of means.
Course Learning Outcomes
Describe common statistical terms (e.g. statistic, parameter, descriptive statistics, inferential statistics, and sampling error) correctly in a statistical context
Identify the scale of a measurement of a variable
Identify whether a given variable is continuous or discrete
Create frequency distribution tables and appropriate graphs for given data
Compute the mean, median and mode as measures of central tendency
Compute measures of variability
Describe a data set (a set of scores) using appropriate descriptive statistics
Apply the appropriate inferential statistical technique to situations covered in class
Interpret the results of an inferential test
Summarize the results of inferential statistical techniques using APA style
Distinguish between parametric and nonparametric statistical tests
Describe the basic assumptions of a given statistical test
Determine when each of these assumptions is violated
Compute a z score for a given raw score
Interpret a z score for a given raw score
Use a unit normal table to determine the proportion of scores above or below any given z-scores
Distinguish between a population and a sample, and between parameters
and statistics.
Describe properties of the distribution of sample means in general situations, using the Central Limit Theorem.
Compute a z for a sample mean
Use the z score for a sample mean and unit normal table to determine how likely a given sample mean is to occur
Compute descriptive and inferential statistics using a computer program (i.e. SPSS).
Interpret the SPPS output for a given descriptive and/or inferential statistics