1. 1 STAT 6020 Introduction to Biostatistics Fall 2005 Dr. G. H. Rowell Class 1

2. 2 General Information  Student Introductions  Handout Syllabus  Preview text books  Background Reading Chapter 1 – Altman

3. 3 Chapter 1: Statistics in Medical Research  Homework: Read Chapter 1 Read mainly for the big picture  Think about Steps in a Research Project Statistical Inference concept Importance of Randomization Reasons to eliminate bias

4. 4 Chapter 2: Types of Data  Overview Categorical Data Numerical Data Other Types Censured Data Variability Importance of the Type of Data Dealing with Numbers

5. 5 Ch 2: Categorical Data  Def:  Two Categories  More Than Two Categories Nominal - no obvious ordering  Ex: Ordinal - ordered data  Ex.

6. 6 Ch 2: Numerical Data  Discrete Data  Continuous Data

7. 7 Ch 2. Other Types of Data  Ranks  Percentages  Rates/Ratios  Scores & Scales

8. 8 Ch 2. Censored Data  Important Concept – Ch 13  Def:  Left Censoring  Occurs when

9. 9 Ch 2: A Few Other Points  Variability  Importance of Data Type  Dealing with Numbers Presenting Results Rounding

10. 10 Ch 2: Homework  Read Chapter 2 Use this ppt as a guide for key points Know your terminology  Make a list of terms, including definitions  This can be a good study guide

11. 11 Ch 3: Describing Data  Once you identify the type of data then you can select a method to describe the data  Decision 1: Categorical or Numerical  If Categorical – how many categories, ordered or not  If Numerical – continuous or discrete

12. 12 Ch 3: Categorical Data – Two Broad Ways to Describe  # 1: Numerical Descriptions  Single Variables Frequencies, relative frequencies, percents Cumulative frequencies  Two or More Variables (Show Relationships) Contingency tables

13. 13 Ch 3: Categorical Data – Two Broad Ways to Describe  # 2: Graphical Demonstrate basic trends, proportion  Bar chart, pie charts, … Show relationships  Side-by-side bar charts (compare groups)  Stacked bar/column chart, subset pie charts, …

14. 14 Ch 3: Quantitative Data – Two Broad Ways to Describe  # 1: Numerical Descriptions Measure of Center  Mean, median, mode Measures of Spread  Range, standard deviation, IQR, … Measures of location  Percentile, rank, z-score

15. 15 Ch 3: Quantitative Data – Two Broad Ways to Describe  # 2: Graphical Demonstrate basic shape  Histogram, Stem-and-leaf plot, dotplot, … Show spread  Boxplot, dotplot, histogram, … Show relationships  Scatterplot, …

16. 16 Ch 3: Describing Data Example

17. 17 Ch 3: Transformations ***  Linear Transformations new variable = slope*variable+ y-int. y=mx+b, y=mx, y=x+b  Non-linear Transformation Log transformation – very common *** This may be a new area for some of you. It can be a powerful method.

18. 18 Ch 3: Homework  Read Pages 42 – 44 (Data Presentation)  Work # 3.1, 2, 3

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