University:
California State University, San Bernardino
Course:
ADMN 2100 | Applied Business Statistics
Academic year:

2024
Views:

219

Pages:

2
Author:

Mikael N.

Methods and Techniques * Research Methods Overview of qualitative and quantitative research methods. - Data collection techniques: surveys, interviews, experiments, observations. * Sampling Techniques Random sampling, stratified sampling, cluster sampling. Sample size determination and significance. * Data Analysis Techniques - Descriptive statisties: measures of central tendency and variability. - Inferential statistics: haypothesis testing, confidence intervals. * Statistical Tools - Excel functions for data analysis. - Introduction to statistical software such as SPSS, SAS, or R. * Experimental Design - Basics of experimental design: control groups, independent variables, dependent variables. - validity and reliability considerations. * Qualitative Analysis - Coding techniques in qualitative data analysis. - Thematic analysis, content analysis, grounded theory. * Data Visualization - Graphical representation of data: histograms, scatter plots, pie charts. - Importance of clear and effective data presentation. * Ethical considerations - Research ethics: informed consent, confidentiality, avoiding bias. - Responsible data handling and reporting.