Foundations of applied statistical methods/ Hang Lee
Material type:
TextPublication details: New York: Springer, 2014Description: x,161 p. : ill. ; 24 cmISBN: 9783319024011Subject(s): Mathematical statistics | Statistics | Research--Statistical methods DDC classification: 519.5 | Item type | Current library | Call number | Status | Date due | Barcode | Item holds |
|---|---|---|---|---|---|---|
General Books
|
Central Library, Sikkim University General Book Section | 519.5 LEE/F (Browse shelf(Opens below)) | Available | P41341 |
Machine generated contents note: 1.1. Types of Data --
1.2. Description of Data Pattern --
1.2.1. Distribution --
1.2.2. Description of Categorical Data Distribution --
1.2.3. Description of Continuous Data Distribution --
1.2.4. Stem-and-Leaf --
1.3. Descriptive Statistics --
1.3.1. Statistic --
1.3.2. Central Tendency Descriptive Statistics for Quantitative Outcomes --
1.3.3. Dispersion Descriptive Statistics for Quantitative Outcomes --
1.3.4. Variance --
1.3.5. Standard Deviation --
1.3.6. Property of Standard Deviation After Data Transformations --
1.3.7. Other Descriptive Statistics for Dispersion --
1.3.8. Dispersions Among Multiple Data Sets --
1.3.9. Caution to CV Interpretation --
1.3.10. Box and Whisker Plot --
1.4. Descriptive Statistics for Describing Relationships Between Two Outcomes --
1.4.1. Linear Correlation Between Two Continuous Outcomes --
1.4.2. Contingency Table to Describe an Association Between Two Categorical Outcomes --
1.4.3. Odds Ratio. Contents note continued: 1.5. Two Useful Probability Distributions --
1.5.1. Gaussian Distribution --
1.5.2. Density Function of Gaussian Distribution --
1.5.3. Application of Gaussian Distribution --
1.5.4. Standard Normal Distribution --
1.5.5. Binomial Distribution --
1.6. Study Questions --
Bibliography --
2.1. Population and Sample --
2.1.1. Sampling and Non-sampling Errors --
2.1.2. Sample- and Sampling Distributions --
2.1.3. Standard Error --
2.2. Statistical Inference --
2.2.1. Data Reduction and Related Nomenclature --
2.2.2. Central Limit Theorem --
2.2.3. The t-Distribution --
2.2.4. Testing Hypotheses --
2.2.5. Accuracy and Precision --
2.2.6. Interval Estimation and Confidence Interval --
2.2.7. Bayesian Inference --
2.2.8. Study Design and Its Impact to Accuracy and Precision --
2.3. Study Questions --
Bibliography --
3.1. Independent Samples t-Test for Comparing Two Independent Means --
3.1.1. Independent Samples t-Test When Variances Are Unequal. Contents note continued: 3.1.2. Denominator Formulae of the Test Statistic for Independent Samples t-Test --
3.1.3. Connection to the Confidence Interval --
3.2. Paired Sample t-Test for Comparing Paired Means --
3.3. Use of Excel for t-Tests --
3.4. Study Questions --
Bibliography --
4.1. Sums of Squares and Variances --
4.2.F-Test --
4.3. Multiple Comparisons and Increased Type-1 Error --
4.4. Beyond Single-Factor ANOVA --
4.4.1. Multi-factor ANOVA --
4.4.2. Interaction --
4.4.3. Repeated Measures ANOVA --
4.4.4. Use of Excel for ANOVA --
4.5. Study Questions --
Bibliography --
5.1. Inference of a Single Pearson's Correlation Coefficient --
5.1.1.Q & A Discussion --
5.2. Linear Regression Model with One Independent Variable: Simple Regression Model --
5.3. Simple Linear Regression Analysis --
5.4. Linear Regression Models with Multiple Independent Variables --
5.5. Logistic Regression Model with One Independent Variable: Simple Logistic Regression Model. Contents note continued: 5.6. Consolidation of Regression Models --
5.6.1. General and Generalized Linear Models --
5.6.2. Multivariate Analyses and Multivariate Model --
5.7. Application of Linear Models with Multiple Independent Variables --
5.8. Worked Examples of General and Generalized Linear Modes --
5.8.1. Worked Example of a General Linear Model --
5.8.2. Worked Example of a Generalized Linear Model (Logistic Model) Where All Multiple Independent Variables Are Dummy Variables --
5.9. Study Questions --
Bibliography --
6.1.Comparing Two Proportions Using 2x2 Contingency Table --
6.1.1. Chi-Square Test for Comparing Two Independent Proportions --
6.1.2. Fisher's Exact Test --
6.1.3.Comparing Two Proportions in Paired Samples --
6.2. Normal Distribution Assumption-Free Rank-Based Methods for Comparing Distributions of Continuous Outcomes --
6.2.1. Permutation Test --
6.2.2. Wilcoxon's Rank Sum Test --
6.2.3. Kruskal-Wallis Test --
6.2.4. Wilcoxon's Signed Rank Test. Contents note continued: 6.3. Linear Correlation Based on Ranks --
6.4. About Nonparametric Methods --
6.5. Study Questions --
Bibliography --
7.1. Censored Observations --
7.2. Probability of Survival Longer Than Certain Duration --
7.3. Statistical Comparison of Two Survival Distributions with Censoring --
7.4. Study Question --
Bibliography --
8.1. Sample Size for Interval Estimation of a Single Mean --
8.2. Sample Size for Hypothesis Tests --
8.2.1. Sample Size for Comparing Two Means Using Independent Samples z- and t-Tests --
8.2.2. Sample Size for Comparing Two Proportions --
8.3. Study Questions --
Bibliography --
9.1. Review Exercise 1 --
9.2. Review Exercise 2 --
9.2.1. Part A (30 Points): Questions 1-15 "True/False" Questions, Please Explain/Criticize Why If You Chose to Answer False (2 Points Each) --
9.2.2. Part B (15 Points): Questions 16.1-16.3 --
9.2.3. Part C (15 Points): Questions 17-19 --
9.2.4. Part D (10 Points): Questions 20-21 --
9.2.5. Part E (5 Points): Question 22. Contents note continued: 9.2.6. Part F (20 Points): Questions 23-26.
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