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BIO733 : Applied Biostatistics

Course Overview

Course Synopsis

This course will provide researchers with the practical skills to use to cutting-edge methods in Epidemiology and Biostatistics. They will be introduced to the concept of causal inference using observational data. Thestudents will be able to correctly select the appropriate statistical analytical method to address specific research questions, conduct the selected statistical analysis using SAS software for statistical analysis, present and interpret the results appropriately and draw valid and insightful conclusions.

Course Learning Outcomes

This course aims to enable you to apply advanced biostatistical methods to address research questions.

  • Determine the appropriate statistical analytical technique for different epidemiological study designs and datasets
  • Conduct statistical analysis using advanced techniques on complex datasets with different types of variables.
  • Correctly interpret results and draw valid conclusions addressing the research question.


Course Calendar

1 Introduction to Biostatistics
3 Basic Terminology - II
4 Data
2 Basic Terminology - I
5 Variables
6 Measurement Scales - I
7 Measurement Scales - II
8 Types of Statistics
9 Sampling and Statistical Inference
10 Basic Terminology for sampling
11 Types of Sampling Methods
12 Simple Random Sampling
13 Stratified Random Sampling
14 Cluster Sampling
15 Systematic Sampling
16 Non-Probability Sampling Methods
17 Convenience Sampling
18 Describing Data with Tables - I
19 Describing Data with Tables - II
20 Describing Data with Tables - III
21 Contingency Tables
22 Describing Data with Charts - I
23 Describing Data with Charts - II
24 Describing Data with Charts - III
25 Box and Whisker Plot
26 Microsoft Excel Demo
27 Describing Data: From its Shapes
28 Describing Data: From its peak
29 Describing Shape: From Box and Whisker Plot
30 Descriptive Statistics: Measures of Central Tendency
31 Arithmetic Mean
32 Median
33 Mode
34 Appropriate Use of Measures of Location
35 Quantiles (Cut Points)
36 Examples of Quantiles
37 Measures of Dispersion
38 Absolute Measures of Dispersion
39 Examples for Absolute Measures of Dispersion
40 Relative Measures of Dispersion
41 Examples of Measures of Dispersion
42 Appropriate usage of the Measures of Dispersion
43 Calculating Skewness and making decision using Numerical measures
44 Calculating Kurtosis and making decision using Numerical measures
45 Counting Rules
46 Permutations
47 Combinations
48 Probability: Introduction
49 Probability: Basic Terminology - I
50 Probability: Basic Terminology - II
51 Probability: Axioms of Probability
52 Probability: Additive rule
53 Probability: Multiplicative Rule for Independent Events
54 Conditional Probability
55 Bernoulli Distribution I
56 Bernoulli Distribution II
57 Bernoulli Distribution III
58 Bernoulli Distribution IV
59 Bernoulli Distribution V
60 Continuous Probability Distribution I
61 Continuous Probability Distribution II
62 Continuous Probability Distribution III
63 Continuous Probability Distribution IV
64 Continuous Probability Distribution V
65 Continuous Probability Distribution VI
66 Continuous Probability Distribution VII
67 Continuous Probability Distribution VIII
68 Introduction to Sampling
69 Introduction to Sampling I
70 Introduction to Sampling II
71 Introduction to Sampling IV
72 Stratified Random Sampling.
73 Stratified Random Sampling I
74 Stratified Random Sampling II
75 Stratified Random Sampling III
76 Stratified Random Sampling IV
77 Standard Error
78 Sampling Distribution of the sample mean
79 Expectated value and variance of the sampling distribution of the sample mean
80 Sampling Distribution of the differnece between two means
81 Expected value and variance of the sampling distribution of the difference between two sample means
82 Sampling Distribution of a sample Proportion
83 Expected value and variance of the sampling distribution of a sample proportion
84 Sampling distribution of the difference of the two sample proportion
85 Estimation
86 Point Estimation
87 Interval Estimation
88 Using Tables and MS Excel to obtain probability
89 Confidence Interval for Single Mean
90 Confidence Interval for the difference between Two population Means
91 Confidence Interval for the Single Proportion
92 Confidence Interval for the Difference of two proportions
93 A Tutorial to SPSS - I
94 A Tutorial to SPSS - II
95 A Tutorial to SPSS - III
96 A Tutorial to SPSS - IV
97 A Tutorial to SPSS - V
98 A Tutorial to SPSS - VI
99 A Tutorial to SPSS - VII
100 A Tutorial to SPSS - VIII
101 A Tutorial to SPSS - IX
102 A Tutorial to SPSS - X
103 A Tutorial to SPSS - XI
104 A Tutorial to SPSS - XII
105 A Tutorial to SPSS - XIII
106 Using SPSS to report Descriptive Statistics
107 Basic Concepts of Hypothesis Testing
108 Test Statistics
109 Types of Errors
110 Significance Level
111 Decision Rule
112 Conclusion
113 Assumptions for Testing of Hypothesis
114 Flow Chart for Hypothesis Testing
115 Testing Normality Assumption
116 Testing Hypothesis for Single Mean - I
117 Testing Hypothesis for Single Mean - II
118 Testing Hypothesis for Single Mean - III
119 Testing Hypothesis for Single Mean - IV
120 Testing Hypothesis for Single Mean
121 Testing Difference of Means in two independent samples
122 Testing Difference of Means in two independent samples (Equal Variances Assuming)
123 Testing Difference of Means in two independent samples (UnEqual Variances Assuming)
124 Testing Difference of Means in two independent samples(non-Parametric)-I
125 Testing Difference of Means in two independent samples (non-Parametric) - II
126 Testing Difference of Means in Two dependent samples - I
127 Testing Difference of Means in Two dependent samples - II
128 Testing Difference of Means in two dependent samples - III
129 Testing Difference of Means in two dependent samples - IV
130 Analysis of Variance
131 Testing Assumptions of ANOVA
132 Performing ANOVA
133 Multiple Comparison Tests
134 Types of Multiple Comparison Test
135 Performing and Interpreting Multiple Comparison Tests
136 Bonferroni Correction
137 Kruskal Wallis Test - I
138 Kruskal Wallis Test - II
139 Two-Way ANOVA
140 Discussion of dataset for Two-way ANOVA
141 Performing and Interpreting Two-Way ANOVA
142 Multiple Comparison Tests in Two-Way ANOVA
143 Performing and Interpreting Multiple Comparison tests for Two-Way ANOVA
144 Testing Hypothesis for Single Proportion
145 Testing Hypothesis for Two Proportions
146 Testing Hypothesis for More than Two Proportions
147 Contingency table analysis
148 Fisher's Exact Test - I
149 Fisher's Exact Test - II
150 Using P-Values
151 Tests for Goodness of fit - I
152 Tests for Goodness of fit - II
153 Measuring Relative Risk
154 Measuring Odds Ratio
155 Comparing Odds Ratio and Relative Risk
156 Measuring Morbidity
157 Measuring Mortality 1
158 Correlation
159 Assumptions used for Correlation
160 Types of correlation and their usage
161 Partial Correlation
162 Multiple Correlation
163 Calculating and interpeting Correlation
164 Testing Hypothesis about Correlation coefficient
165 Regression
166 Assumptions for Regression Model
167 Steps in Regression Analysis
168 Understanding Dependence relationship using Scatter Plots
169 Principle of Leasst Squares
170 Least Squares line
171 Obtaining a regression Line using SPSS
172 ANOVA in Regression
173 Decision making Using ANOVA in regression
174 Calculating and Interpreting results for ANOVA in regression usign SPSS
175 Evaluating a regression Equation
176 Confidence intervals for individual parameters
177 Coefficient of Determination
178 Making Prediction using regression Model
179 Testing the regression Assumptions
180 Multiple Linear Regression Model
181 Obtaining and Interpreting a multiple linear regression equation
182 Detecting Outliers, Influential and leverage values
183 SPSS tutorial to Multiple regression
184 Regression with Qualitative Independent variable
185 Performing and Interpreting Regression with Qualitative Independent Variable
186 Variable Selection procedures
187 Forward Selection
188 Backward Elimination
189 Stepwise Regression
190 An SPSS Tutorial to Variable selection procedures
191 Introduction to Survival Analysis
192 Survival Analysis: Basic Terminology
193 Censoring
194 Types of Censoring
195 Right Censoring
196 Left Censoring
197 Interval Censoring
198 SPSS tutorial to model building
199 SPSS Tutorial to Assumption testing
200 SPSS Tutorial to variable Selection