Presentation is loading. Please wait.

Presentation is loading. Please wait.

AUSTRALIA INDONESIA PARTNERSHIP FOR EMERGING INFECTIOUS DISEASES Introduction to data analysis: Case studies with iSIKHNAS data Day 1 1/ 69.

Published byRosaline McLaughlin Modified over 8 years ago

Similar presentations

Presentation on theme: "AUSTRALIA INDONESIA PARTNERSHIP FOR EMERGING INFECTIOUS DISEASES Introduction to data analysis: Case studies with iSIKHNAS data Day 1 1/ 69."— Presentation transcript:

1 AUSTRALIA INDONESIA PARTNERSHIP FOR EMERGING INFECTIOUS DISEASES Introduction to data analysis: Case studies with iSIKHNAS data Day 1 1/ 69

2 AUSTRALIA INDONESIA PARTNERSHIP FOR EMERGING INFECTIOUS DISEASES Introduction to course Relevance of data analysis to policy Objectives of course Pre-requisites

3 AUSTRALIA INDONESIA PARTNERSHIP FOR EMERGING INFECTIOUS DISEASES Learning approach

4 AUSTRALIA INDONESIA PARTNERSHIP FOR EMERGING INFECTIOUS DISEASES Steps in data analysis Objective Data management Descriptive analysis Hypothesis testing

5 AUSTRALIA INDONESIA PARTNERSHIP FOR EMERGING INFECTIOUS DISEASES Key concepts for sampling (1) Sampling verse census Bias Sampling variability

6 AUSTRALIA INDONESIA PARTNERSHIP FOR EMERGING INFECTIOUS DISEASES Key concepts for sampling (2) Datasets and variables

7 AUSTRALIA INDONESIA PARTNERSHIP FOR EMERGING INFECTIOUS DISEASES Key concepts for sampling (3) Distributions

8 AUSTRALIA INDONESIA PARTNERSHIP FOR EMERGING INFECTIOUS DISEASES Case study 1: Introduction

9 AUSTRALIA INDONESIA PARTNERSHIP FOR EMERGING INFECTIOUS DISEASES Case study 1: Objectives Objectives – Exercise 1 – Exercise 2

10 AUSTRALIA INDONESIA PARTNERSHIP FOR EMERGING INFECTIOUS DISEASES Case study 1: Data management Download iSIKHNAS data Preserve data

11 AUSTRALIA INDONESIA PARTNERSHIP FOR EMERGING INFECTIOUS DISEASES Key concepts on errors Missing data – Blank cells in data – Missing observations Incorrect data – Random errors – Systematic errors

12 AUSTRALIA INDONESIA PARTNERSHIP FOR EMERGING INFECTIOUS DISEASES Case study 1: Data management Exercises 3: Missing data Exercise 5: Create new data

13 AUSTRALIA INDONESIA PARTNERSHIP FOR EMERGING INFECTIOUS DISEASES Key concepts on descriptive statistics Variable types Continuous variables – Measures of central tendency – Measures of dispersion

14 AUSTRALIA INDONESIA PARTNERSHIP FOR EMERGING INFECTIOUS DISEASES Case study 1: Description of data Exercise 6: Descriptive statistics Exercise 6b: Descriptive statistics without analysis ToolPak Exercise 7: Plotting (histograms)

15 AUSTRALIA INDONESIA PARTNERSHIP FOR EMERGING INFECTIOUS DISEASES Summary of case study 1

16 AUSTRALIA INDONESIA PARTNERSHIP FOR EMERGING INFECTIOUS DISEASES The end of day 1

17 AUSTRALIA INDONESIA PARTNERSHIP FOR EMERGING INFECTIOUS DISEASES

Download ppt "AUSTRALIA INDONESIA PARTNERSHIP FOR EMERGING INFECTIOUS DISEASES Introduction to data analysis: Case studies with iSIKHNAS data Day 1 1/ 69."

Similar presentations

Quantitative Techniques Lecture 1: Economic data 30 September 2004.

Quantitative Techniques Lecture 1: Economic data 30 September 2004.
Sample Size And Power I Jean B. Nachega, MD, PhD Department of Medicine & Centre for Infectious Diseases Stellenbosch University

Sample Size And Power I Jean B. Nachega, MD, PhD Department of Medicine & Centre for Infectious Diseases Stellenbosch University
MA 102 Statistical Controversies Monday, January 28, 2002 Today: Discussion of Statistical Thought, First Ideas About Data, and Exercises. Introduction.

MA 102 Statistical Controversies Monday, January 28, 2002 Today: Discussion of Statistical Thought, First Ideas About Data, and Exercises. Introduction.
Datasets and Variables We want to answer questions We want to use data for this purpose Observations of characteristics of cases Case: person, city, organization,

Datasets and Variables We want to answer questions We want to use data for this purpose Observations of characteristics of cases Case: person, city, organization,
DATA ANALYSIS I MKT525. Plan of analysis What decision must be made? What are research objectives? What do you have to know to reach those objectives?

DATA ANALYSIS I MKT525. Plan of analysis What decision must be made? What are research objectives? What do you have to know to reach those objectives?
Programme in Statistics (Courses and Contents). Elementary Probability and Statistics (I) 3(2+1)Stat. 101 College of Science, Computer Science, Education.

Programme in Statistics (Courses and Contents). Elementary Probability and Statistics (I) 3(2+1)Stat. 101 College of Science, Computer Science, Education.
Lect 10b1 Histogram – (Frequency distribution) Used for continuous measures Statistical Analysis of Data ______________ statistics – summarize data.

Lect 10b1 Histogram – (Frequency distribution) Used for continuous measures Statistical Analysis of Data ______________ statistics – summarize data.
Engineering Probability and Statistics - SE-205 -Chap 1 By S. O. Duffuaa.

Engineering Probability and Statistics - SE-205 -Chap 1 By S. O. Duffuaa.
MA 102 Statistical Controversies Monday, February 18, 2002 Today: Discuss Chapter 9 concepts and exercises Review Part 1 of the text Test 1 question types.

MA 102 Statistical Controversies Monday, February 18, 2002 Today: Discuss Chapter 9 concepts and exercises Review Part 1 of the text Test 1 question types.
Thomas Songer, PhD with acknowledgment to several slides provided by M Rahbar and Moataza Mahmoud Abdel Wahab Introduction to Research Methods In the Internet.

Thomas Songer, PhD with acknowledgment to several slides provided by M Rahbar and Moataza Mahmoud Abdel Wahab Introduction to Research Methods In the Internet.
Data and Data Collection Quantitative – Numbers, tests, counting, measuring Fundamentally--2 types of data Qualitative – Words, images, observations, conversations,

Data and Data Collection Quantitative – Numbers, tests, counting, measuring Fundamentally--2 types of data Qualitative – Words, images, observations, conversations,
1. An Overview of the Data Analysis and Probability Standard for School Mathematics? 2.

1. An Overview of the Data Analysis and Probability Standard for School Mathematics? 2.
Target population-> Study Population-> Sample 1WWW.HIVHUB.IR Target Population: All homeless in country X Study Population: All homeless in capital shelters.

Target population-> Study Population-> Sample 1WWW.HIVHUB.IR Target Population: All homeless in country X Study Population: All homeless in capital shelters.
AUSTRALIA INDONESIA PARTNERSHIP FOR EMERGING INFECTIOUS DISEASES Introduction to data analysis: Case studies with iSIKHNAS data Day 3 Beef self-sufficiency.

AUSTRALIA INDONESIA PARTNERSHIP FOR EMERGING INFECTIOUS DISEASES Introduction to data analysis: Case studies with iSIKHNAS data Day 3 Beef self-sufficiency.
● Midterm exam next Monday in class ● Bring your own blue books ● Closed book. One page cheat sheet and calculators allowed. ● Exam emphasizes understanding.

● Midterm exam next Monday in class ● Bring your own blue books ● Closed book. One page cheat sheet and calculators allowed. ● Exam emphasizes understanding.
EPE/EDP 557 Key Concepts / Terms –Empirical vs. Normative Questions Empirical Questions Normative Questions –Statistics Descriptive Statistics Inferential.

EPE/EDP 557 Key Concepts / Terms –Empirical vs. Normative Questions Empirical Questions Normative Questions –Statistics Descriptive Statistics Inferential.
Practice 1 Tao Yuchun Medical Statistics

Practice 1 Tao Yuchun Medical Statistics
The Research Design. Experimental Design Definition A description of what a researcher would like to find out and how to find it out. Pre-requisites 1.Identification.

The Research Design. Experimental Design Definition A description of what a researcher would like to find out and how to find it out. Pre-requisites 1.Identification.
Chapter 21 Basic Statistics.

Chapter 21 Basic Statistics.
Introduction to Biostatistics and Bioinformatics Exploring Data and Descriptive Statistics.

Introduction to Biostatistics and Bioinformatics Exploring Data and Descriptive Statistics.

Similar presentations

Ads by Google