BASIC STATISTIC (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; Analysis of Difference : Significance Testing;
5. Significance Test for Non Parametric Data;
6. Simple Linear Regression and Correlation;
7. Experimental Design;
8. Descriptive Statistics;
9. The Normality Checking;
10. Confidence Interval;
11. Hypothesis Testing : One Sample Test;
12. Analysis of Difference: Significance Testing;
13. Significance Test for Non Parametric Data;
14. Simple Linear Regression and Correlation;
15. Experimental Design.