Statistical Fridays J C Horrow, MD, MS STAT Clinical Professor, Anesthesiology Drexel University College of Medicine.

Slides:



Advertisements
Similar presentations
Data: Quantitative (Histogram, Stem & Leaf, Boxplots) versus Categorical (Bar or Pie Chart) Boxplots: 5 Number Summary, IQR, Outliers???, Comparisons.
Advertisements

Andrea M. Landis, PhD, RN UW LEAH
1 Important Terms Variable – A variable is any characteristic whose value may change from one individual to another A univariate data set consists of.
Example: In a heart study the systolic blood pressure was measured for 24 men aged 25 and for 30 men aged 40. Do these data show sufficient evidence to.
Designing Clinical Research Studies An overview S.F. O’Brien.
LSU-HSC School of Public Health Biostatistics 1 Statistical Core Didactic Introduction to Biostatistics Donald E. Mercante, PhD.
1 Chapter 1: Sampling and Descriptive Statistics.
Brian L. Strom, M.D., M.P.H. Chair and Professor, Department of Biostatistics and Epidemiology Director, Center for Clinical Epidemiology and Biostatistics.
Statistical Fridays J C Horrow, MD, MS STAT Clinical Professor, Anesthesiology Drexel University College of Medicine.
Stat 512 Day 4: Quantitative Data. Last Time p-values and statistical significance  What p-values tell us (and do not tell us) For now, approximating.
Statistical Fridays J C Horrow, MD, MS STAT Clinical Professor, Anesthesiology Drexel University College of Medicine.
Normality,Sampling & Hypothesis Testing and sample size estimation Jobayer Hossain, PhD Larry Holmes, Jr, PhD October 23, 2008 RESEARCH STATISTICS.
Statistical Fridays J C Horrow, MD, MSSTAT
Stat 2411 Statistical Methods Chapter 4. Measure of Variation.
REGRESSION AND CORRELATION
Research Methods in Psychology Pertemuan 3 s.d 4 Matakuliah: L0014/Psikologi Umum Tahun: 2007.
Cohort Studies Hanna E. Bloomfield, MD, MPH Professor of Medicine Associate Chief of Staff, Research Minneapolis VA Medical Center.
Understanding and Comparing Distributions
Objective: To test claims about inferences for two sample means, under specific conditions.
Chapter 1: Research Methods
Research Study Design. Objective- To devise a study method that will clearly answer the study question with the least amount of time, energy, cost, and.
Slide 13-1 Copyright © 2004 Pearson Education, Inc.
PREINDUCTION INTRAVENOUS LABETALOL FOR ATTENUATING INTUBATION STRESS RESPONSE DR. A. KARTHIK KILPAUK MEDICAL COLLEGE KILPAUK MEDICAL COLLEGE.
The Scientific Method in Psychology.  Descriptive Studies: naturalistic observations; case studies. Individuals observed in their environment.  Correlational.
Research Methods Unit II.
Chapter 1 Statistical Thinking What is statistics? Why do we study statistics.
Chapter 6: Random Errors in Chemical Analysis CHE 321: Quantitative Chemical Analysis Dr. Jerome Williams, Ph.D. Saint Leo University.
Estimation This is our introduction to the field of inferential statistics. We already know why we want to study samples instead of entire populations,
 Statistics The Baaaasics. “For most biologists, statistics is just a useful tool, like a microscope, and knowing the detailed mathematical basis of.
Lunch & Learn Statistics By Jay. Goals Introduce / reinforce statistical thinking Understand statistical models Appreciate model assumptions Perform simple.
OPERATIONAL DEFINITION a statement of the procedures used to define research variables.
June 11, 2008Stat Lecture 10 - Review1 Midterm review Chapters 1-5 Statistics Lecture 10.
Statistics with TI-Nspire™ Technology Module E. Lesson 2: Properties Statistics with TI-Nspire™ Technology Module E.
1 Statistics Statistics can be found in all aspects of life:
Diagram of a quasi-experimental design with two groups
Unit 3 Part 2 Surveys, Experiments, and Simulations Experiments.
Section 4.3 Using Studies Wisely By: Michelle Rondilla & Alexander Hasson Period 4.
Statistics notes 8/10/14 Bell Ringer: How could you organize an experiment so that the results showed something completely different from the truth?
Learning Objectives After this section, you should be able to: The Practice of Statistics, 5 th Edition1 DESCRIBE the shape, center, and spread of the.
Slide Slide 1 Chapter 10 Correlation and Regression 10-1 Overview 10-2 Correlation 10-3 Regression 10-4 Variation and Prediction Intervals 10-5 Multiple.
STAT 203 Observational Studies and Experiments Dr. Bruce Dunham Department of Statistics UBC Lecture 20.
Psychological Experimentation The Experimental Method: Discovering the Causes of Behavior Experiment: A controlled situation in which the researcher.
Introduction to General Epidemiology (2) By: Dr. Khalid El Tohami.
Journal Club February 7, 2014 Sadie T. Velásquez, MD.
Statistical methods for health sciences Descriptive statistics Hypotheses tests Analysis of variance Regression analysis Live event analysis Multivariate.
Collecting Sample Data Chapter 1 Section 4 Part 2.
Statistics Descriptive Statistics. Statistics Introduction Descriptive Statistics Collections, organizations, summary and presentation of data Inferential.
Statistics Use of mathematics to ORGANIZE, SUMMARIZE and INTERPRET numerical data. Needed to help psychologists draw conclusions.
Overview of probability and statistics
Statistical Core Didactic
ABSITE statistics: the absolute basics
Stat 2411 Statistical Methods
Observational Study vs. Experimental Design
Observational Studies and Experiments
Design of Experiments.
Common Core Math I Unit 6 One-Variable Statistics Introduction
Common Core Math I Unit 6 One-Variable Statistics Introduction
Common Core Math I Unit 6 One-Variable Statistics Introduction
Statistics Experimental Design
Scatter Plots and Best-Fit Lines
Observational Studies
Stat 2411 Statistical Methods Chapter 4. Measure of Variation.
Statistical significance using p-value
DENERHTN Trial design: Patients with resistant hypertension were randomized to renal denervation plus standardized stepped-care antihypertensive treatment.
Psychological Experimentation
Introduction to Producing Data
MGSE7.SP.3/MGSE7.SP.4: I can use measure of center and measures of variability for numerical data from random samples to draw informal comparative inferences.
Advanced Algebra Unit 1 Vocabulary
Sampling Distributions
End point Valsartan Valsartan+HCTZ p
Presentation transcript:

Statistical Fridays J C Horrow, MD, MS STAT Clinical Professor, Anesthesiology Drexel University College of Medicine

Session Review Sensitivity / specificity Predictive value Effect of disease prevalence The ROC curve

Session Overview Learn new concepts: Observations vary Observational vs. experimental data Graphing your data Example: 50 patients induced with TPL or PPF

Observations Vary Subject JH’s systolic BP is 151 mmHg. He applies 1 mL of 5% minoxidil to his scalp in a vain attempt to keep his remaining hair. 15 min later, his systolic BP is 148 mm Hg. Q: Did his BP decrease ? Q: May we state “BP decreased” ?

Observations Vary

When do things “differ”? Observations Vary

When do things differ? When statistical tests indicate so. Data nearly always “differ numerically” Only statistics tells us when numbers differ. There is no such thing as a difference that is not a statistical difference.

When do things differ? Only when they differ statistically.

Population v. Sample POPULATION : The theoretical cohort about which we wish to draw conclusions…………….. Examples: Patients with heart disease Pregnant women with hypertension Patients with antithrombin deficiency 1

SAMPLE: The specific subjects for whom we have measurements………………… Patients with heart disease 25 patients with classic angina Pregnant women with hypertension 45,420 pregnant women taking Atacand Patients with antithrombin deficiency The patient seen in clinic yesterday Population v. Sample

Population v. Sample: Models Statistical Model : –Device by which we infer properties about a population based on information obtained in a sample ALL MODELS ARE WRONG. Some are useful.

Statistical Model Example: Let x = TPL dose (mg/kg) at induction Let y = decrease in SPB at induction y =     x 

Types of Data Observational Experimental Retrospective Survey data Lack intervention Lack active randomization Prospective Active randomization Intervention Controls / blinding

Types of Data Observational Experimental ASSOCIATION CAUSATION Fifty (50) patients receive TPL or Propofol for induction. The  SPB for each is recorded. Fifty (50) patients are randomly assigned to receive either TPL or Propofol for induction. The  SBP for each is recorded.

Graphing Data Histograms Scatterplots Boxplots

Example: SBP data 100 measurements total: 25 SBP before TPL 25 SBP after TPL 25 SBP before PPF 25 SBP after PPF Calculate  SBP for each

HISTOGRAM

Histogram by Treatment

Scatterplot: before v. after

Scatterplot by treatment group

PPF TPL Min Max Median Upper QuartileLower Quartile Boxplot of  SBP by treatment

Min Max Median Q1 Q3

Min Max Median Q1 Q3

Session Review New concepts: Observations vary Observational vs. experimental data Graphing your data Example: 50 patients induced with TPL or PPF Homework: 20 patients given spinals for C-section