1. Introduction
Definition
Development of biometry
Statistical and scientific method
Studying statistics
2. Data in horticulture
Variables and Derived variables
Distribution
Population and samples
Random samples ─coefficient of data
Presentation, summarization and characterization of data
3. Description statistics
Measure central tendency
Measure of dispersion
Standard error of the mean
Coefficient of variability
4. Probability distribution
Simple considerations of probability
The binomial distribution
The Poisson distribution
The normal probability distribution
The chi-square distribution
5. Sampling distribution
Random samples from a normal distribution
The distribution of sample various and standard deviations
Confidence intervals for the population mean
Confidence intervals for the population variance
6. Hypothesis test
Introduction
Test of significance
Steps of statistical test of hypothesis
Type Ｉ errors, Type Ⅱ errors in hypothesis test
7. One-sample test of hypothesis
Hypothesis test that a population mean is a specific value
Non-parametric statistics and hypothesis test
The one-sample Wilcoxon Signed-Rank test
8. Comparisons involving two sample means
Test for 2 or morn means
Comparisons of 2 sample means independent and equal variances
Confidence intervals of 2 means difference
Meaningful paired test
Independent samples and unequal variance
Hypothesis test of equality of variance
Stein’s 2-stage sample
9. Nonparametric test involving 2 sample means
The signed test
The Wilcoxon signed-rank test
The Kolmogorov-Sminov 2 sample test
10. Chi-square the X2 test criterion
The Chi-square test of goodness of fit
The Chi-square test of independency
Homogeneity of Chi-square
Additivity of Chi-square
11. The analysis of variance
Introduction
The F-distribution
Heterogeneity among sample means
Partitioning the total sum of squares and degree of freedom
Comparisons among means: a prior test
Comparisons among means: a posterior tests
Assumptions of analysis of variance
Bartlett’s test
12. Multiple comparison
Introduction
The least significant difference
Scheffe’s test
Turkey’s procedure
The S-N-K test
Duncan’s new multiple range test
Waller –Duncan’s Bayesian K ration t test
Choices
13. Linear Regression
Introduction
Models of regression
Test of significance in regression
Utilization of regression
14. The simple linear correlation
Correlation and regression
Correlation coefficient
Correlation analysis
Application of correlation