Lab Report #1
By: Monica Lazaro 1W
Group Members:
Bryant White
Amanda Diaz
Introduction
In this experiment the inheritance of traits in Drosophila melanogaster were observed and
analyzed using mendelian laws. The purpose was to predict the offspring of th

Unit 15: Independence and Dependence Notes
Slide 1
This learning unit will cover the role of independence and methods to
test for independence and dependence in contingency tables.
Slide 2
Why is this important?
In epidemiology, it is important to know wh

Unit 14: Contingency and Joint Probability Tables Notes
Slide 1
This unit concerns contingency and joint probability tables.
Slide 2
Why is this important?
Contingency tables are used by epidemiologists to understand the relationship between exposures and

Unit 18: Risk Ratios and Odd Ratios Notes
Slide 1
This learning unit will cover risk ratios and odds ratios.
Slide 2
Why do we need to learn about risk ratios and ods ratios? Measuring the associations between exposures or
risk factors and diseases or oth

Unit 20: Z-Scores and the Normal Curve Notes
Slide 1
This learning unit will cover z scores and the normal curve.
Slide 2
Before we begin this unit, we need to recall 2 points of information we covered: In the measures of
relative position learning unit,

Unit 17: Assessing Test Performance Notes
Slide 1
This learning unit will cover Sensitivity, Specificity, Positive and Negative Predictive
Values and Prevalence.
Slide 2
Why is this important?
One of the things we do in Public Health is to screen for dise

Unit 21 (presentation): Sampling Distributions & Central Limit Theorem Notes
The kinds of questions we have dealt with so far are of the type: What is the probability that an
individual chosen at random from a population has a systolic BP of 130 or greate

Unit 23: Making Inferences Notes
Slide 1
In this learning unit, we will cover how to use sampling distributions to make inferences.
Slide 2
Why is this important?
The sampling distribution of the mean is the basis for many statistical tests.
This is one o

Unit 22: Binomial Distribution Notes
Slide 1
Using the Normal Curve Table, we can answer questions about means obtained
from samples for continuous measures like blood pressure. Suppose instead that
I consider a statistical population made up of a dichoto

Unit 13: Calculating Probability Notes
Slide 1
This unit concerns calculating probability.
Slide 2
In mathematical terms, we denote the probability of a characteristic A as P(A).
It is equal to the number of observations that satisfy A (N sub A) divided b

Unit 19 (Presentation): Normal Distribution Notes
This presentation concerns the normal distribution.
Up to this point in the course, weve talked about probabilities related to dichotomous variables
(such as being exposed or not exposed having a disease o

Unit 6: Distributions and Tables - Notes
Slide 1
One way to organize data is by tables.
Slide 2
So why is this important?
Raw data are difficult to interpret, as we showed earlier. One way of organizing
raw data is to put them in a table.
Slide 3
Suppose

Unit 11: Measures of Distributional Shapes - Notes
Slide 1
The next unit concerns measures of distributional shape.
Slide 2
Measures of distributional shape include skew and kurtosis.
Why is this important?
Although used rarely in description of data, the

Unit 7: Graphs - Notes
Slide 1
Another way we can represent data is by graphs.
Slide 2
Why is this important? Graphs provide visual ways of communicating information
that are usually more efficient than tables. A great deal of information about the
charac

Unit 9: Measures of Variability - Notes
Slide 1
This unit concerns measurement of variability.
Slide 2
Why is this important?
Statistics is concerned with variability. If there were no variability, everything would be
predictable and there would be no nee

Unit 10: Measures of Relative Position - Notes
Slide 1
In this unit we will introduce the measures of relative position.
Slide 2
Measures of relative position locate the positions of observations in a distribution. In this
learning unit we
introduce you t

Unit 8: Measures of Central Tendency - Notes
Slide 1
This unit concerns measures of central tendency
Slide 2
Why are these important? Measures of central tendency include the mean, median
and mode. As descriptors, such measures play a major role in statis

Unit 16 (Presentation): Dependence and Causation Notes
This presentation concerns Dependence and Causation.
We have talked about independence in joint probability tables and how by examining the joint and
marginal
probabilities in these tables, we can det

Unit 12 (Presentation): Probability Notes
As we already know, the discipline of biostatistics can be divided into two
parts: descriptive statistics and inferential statistics. Until now, we have been
learning about descriptive statistics. It is time to fo

Unit 24: Hypothesis Testing Notes
Slide 1
In this learning unit we will cover hypothesis testing.
Slide 2
Hypothesis testing is one of the two principal techniques of inferential statistics. The other one, which we
discuss later in the course, is confiden

4.1,4.2
4.3,4.4
It guarantees that the sampling distribution will approach normality
as the sample size increases.
4.5
45 50
Z=-2.5
4.6
4.7
COMPARE: Exercise 4.6 exact value = .38228

Sampling and Probability
Learning Objectives
Understand probability sampling
Compute and interpret unconditional and
conditional probabilities
Evaluate and interpret independence of events
2
Two Areas of Biostatistics
Goal: Statistical Inference
POPULA

Introduction
- Screen for disease by giving tests
0 Evaluate the test for accuracy in
predicting the disease.
- Use sensitivity, specificity, positive and
negative predictive values to measure
accuracy of a test.
Sensitivity
PSA 3 7 ng/rni Test +
PSA <

Formulas for Exam 2
Biostatistics I
Fall 2015
Basic formulas:
Z
t
x
s=
/ n
x2
( x ) 2
n 1
n
x
s/ n
Confidence interval when the population standard deviation is known:
L xZ
n
U xZ
n
Confidence interval when the population standard deviation is NOT known

Rewards good work ethic
Demystify statistics
10 assignments (10 points each)
10 Exercises (no points, meant to help)
3 open book quizzes (20 points each in class)
One group project & presentation (40 points)
EXTRA CREDIT (but no curve)
*
Evidence and data

Evaluating the Public Health Impact
of Health Promotion Interventions:
The RE-AIM Framework
Russell E. Glasgow, PhD, Thomas M. Vogt, MD, MPH, and Shawn M. Boles, PhD
Although the field of health promotion
has made substantial progress,1-13 our advances
ar