STATISTICS IN FOOD TECHNOLOGY (2/1 CREDITS)

Learning Outcomes:

On successful completion of this course, students will be able to: LO1 – Explain statistical principles in food science and technology applications; LO2 – Employ appropriate data collection and analysis in the field of food science and technology; LO3 – Construct visual representation of data with statistical results; LO4 – Utilize artificial intelligence tools for data analysis and academic research data visualization.

Topics:

1. Descriptive Statistics;
2. Normality Test;
3. Descriptive and normality test;
4. T-test and Mann-Whiteney;
5. Confidence Interval;
6. Sampling size; Student T test;
7. ANOVA and Kruskall-Wallis;
8. Regression and correlation;
9. Regression;
10. Correlation Analysis;
11. Chi-square goodness of fit and cross tabulation;
12. Principle Component Analysis;
13. Analysis of Variance;
14. Conjoint Test;
15. Non Parametric Test;
16. Principle Component Analysis (PCA);
17. Artificial Intelligence (AI) for Statistical Analysis.