DATA & STATISTICAL ANALYSIS (2/2 SCU)

Learning Outcomes:

On successful completion of this course, students will be able to: describe the statistical data in food science; explain the visualization of statistical data in food science application; calculate the numerical measurement, probability and probability distribution and other statistical calculation of data in food science; use statistical inference method in food science application; analyze the statistical data in food science application using MINITAB or SPSS.

Topics:

1. Descriptive Statistics (Numerical Measurement and Visualizing and Interpretation Data);
2. The Normal Distribution;
3. Confidence Interval;
4. Hypothesis Testing : One Sample Test;
5. Analysis of Difference : Significance Testing;
6. Significance Test for Non Parametric Data;
7. Simple Linear Regression and Correlation;
8. Experimental Design;
9. Descriptive Statistics;
10. The Normality Checking;
11. Confidence Interval;
12. Hypothesis Testing : One Sample Test;
13. Analysis of Difference: Significance Testing;
14. Significance Test for Non Parametric Data;
15. Simple Linear Regression and Correlation;
16. Experimental Design.