2
MODULE 6:
SAMPLING DISTRIBUTIONS
FOR SAMPLE STATISTICS
Module 6.1 Objectives
Students will be able to
o understand the concept
o describe the concept
Module 6.1:
Sampling Distributions
of Sample Statistics
of sample statistics which are
random variable
Exam 2 Review
Review Guide
Sampling variation
Types of sampling methods
How to calculate probabilities
Randomization in clinical trials
Definitions/calculations for screening measures
Normal distribution key attributes
Binomial distribution key attributes
Exam 3 Review
Module 7
Hypothesis Testing
What is a hypothesis?
Atentativeexplanationthataccountsforasetoffactsandca
n betestedbyfurtherinvestigation.
In statistics, we set up two hypotheses:
Null Hypothesis (Ho): no difference, no association, no effe
Questions 1-5 are based on the following paragraph.
Bio-engineers have developed a substance that stimulates the natural production of growth hormone by livestock animals
so that they grow faster and bigger. To test the efficacy of the new bio-engineered
Questions 1-2 refer to the information given below
The Department of Education is interested in gaining information concerning the financial aid of students at private and
public universities. One of the goals is to determine the proportion of students wh
Exam 1 Review
Announcements
Exam 1 Thursday!
Read online instructions
3 hours
30 questions
Can only take once
Must start with enough time to finish by closing time
Have tech support number written down!
Please ask your questions tonight I may not be abl
Question 1 am: pts
Which eflhs fails-Hing statistics are used For variables measured on an internal scale?
It] 'FI'e-Iquenitq.r and relaln'e- frequency
'5 interquatllls range and raldnte- frequency
IE mean and standard dea-iatien
Ifj median and relative e
PHC 4069 Biostatistics in Society
Exam 3 review
Hanze Zhang
Hypothesis testing and confidence intervals:
^
Confidence Interval
for p
_
Confidence Interval for x
^
One-sample z-test for p
^ ^
Two-sample z-test for p1-p2
^ ^
Confidence Interval for p1-p2
_
MODULE 5:
RANDOM VARIABLES AND
PROBABILITY DISTRIBUTIONS
Module 5.5:
Probability
Distributions
in Graphics
Module 5.5 Objectives
Students will be able to
o
use standard normal table to determine probabilities
for events defined by normally distributed co
MODULE 5:
RANDOM VARIABLES AND
PROBABILITY DISTRIBUTIONS
Module 5.3 Objectives
Students will be able to
o use logical-deductive reasoning to derive a
Binomial probability distribution for a Binomial
random variable.
Module 5.3:
Binomial
Probability
Distr
MODULE 5:
Module 5.1 Objectives
RANDOM VARIABLES AND
PROBABILITY DISTRIBUTIONS
Students will be able to
o understand the concept of random variables
o define and identify discrete variables and
Module 5.1:
Random Variables
Random Variables
continuous var
MODULE 6:
SAMPLING DISTRIBUTIONS
FOR SAMPLE STATISTICS
Module 6.3:
Central Limit
Theory (CLT)
The Central Limit Theorem (CLT)
Module 6.3 Objectives
Students will be able to
o understand how the central limit theorem
applies to sample statistics as rules
MODULE 5:
RANDOM VARIABLES AND
PROBABILITY DISTRIBUTIONS
Module 5.2:
Discrete and Binomial
Random Variables
Module 5.2 Objectives
Students will be able to
o
understand the concept of discrete random variables
o
describe Bernoulli experiments.
o
identify
College of Public Health
University of South Florida
Department of Epidemiology and Biostatistics
Syllabus
Course Name:Biostatistics in Society
(Note: This syllabus may be changed or amended due to unforeseen circumstances)
Prefix & Number:PHC 4069
Sectio
MODULE 1:
FUNDAMENTAL
CONCEPTS
Module 1.3: Study designs
Learning Objectives
Describe the basic research study designs used in public
health
Compare and contrast experimental and observational
designs
Study design
In conducting a study, we examine the e
MODULE 1:
FUNDAMENTAL
CONCEPTS
Module 1.1: What are
Data and Where Do They
Come From ?
Course objectives
At the end of the course you are expected to:
Understand the basic notion of biostatistics in research
Know designs used to conduct research
Under
MODULE 1.
FUNDAMENTAL
CONCEPTS
Module 1.2: Populations vs.
Samples
Learning Objectives
Differentiate between a sample and population
Explain the advantages of using samples in public health
research
Describe the types of bias in public health research
MODULE 5:
RANDOM VARIABLES AND
PROBABILITY DISTRIBUTIONS
Module 5.4:
Continuous Random
Variables and
Normal Distribution
Module 5.4 Objectives
Students will be able to
o
understand the concept of continuous random
variables.
o
use logical-deductive reaso
2
MODULE 6:
SAMPLING DISTRIBUTIONS
FOR SAMPLE STATISTICS
0.14
Students will be able to
o understand
how a Binomial distribution can be
approximated by a Normal distribution
Binomial (n=100, P=0.1)
Normal (=0.1, =0.03)
0.12
0.1
P [X]
Module 6.2:
Normal
Ap
MODULE 4:
PROBABILITY AND
APPLICATION
Module 4.3 Objectives
Students will be able to:
o understand the concept of conditional
probability.
Module 4.3:
Conditional Probability
o understand how probability to describe
sensitivity, specificity, positive pre
PHC 4069 Biostatistics in Society
Module 6 Help Session
Sampling distributions for sample statistics
Hanze Zhang
Sampling distribution of a sample
statistic
What is is: the probability distribution for
the values of the sample statistic based on
a random
PHC 4069 Biostatistics in Society
Module 7 hypotheses and confidence intervals
Hanze Zhang
Two types of statistics
Descriptiv
e
Statistics
Inferentia
l
Collecting
,
organizin
Summariz
g
ing,
presentin
g
Hypothes
es
Relations
hips
prediction
s
Two types of
MODULE 3:
SUMMARY STATISTICS TO
DESCRIBE DATA
DISTRIBUTIONS
Chapter Objectives
Students will be able to
Calculate measures of location and interpret
the results;
3.1 Measures of location
Calculate measures of variation and interpret
the results.
Measure
MODULE 2:
EXPLORATORY DATA
ANALYSIS
Chapter Objectives
Students will be able to
Explain the concept of distribution and
describe its characteristics.
Perform graphical and statistical analyses to
Module 2.1: Using Graphs and
Descriptive Statistics to
Un
Summarizing Quantitative Data
MODULE 2:
EXPLORATORY DATA
ANALYSIS
2.2 Quantitative Data
Discrete
Continuous
Discrete data can
only be discrete
values such as
count or integers,
and can be listed
or placed in order
Continuous data
can be any value
on an in
Course objectives
MODULE 1:
FUNDAMENTAL
CONCEPTS
At the end of the course you are expected to:
Understand the basic notion of biostatistics in research
Know designs used to conduct research
Understand some key elements in research
Module 1.1: What are
MODULE 1.
FUNDAMENTAL
CONCEPTS
Learning Objectives
Differentiate between a sample and population
Explain the advantages of using samples in public health
research
Describe the types of bias in public health research
Differentiate between a parameter a
MODULE 3:
SUMMARY STATISTICS TO
DESCRIBE DATA
DISTRIBUTIONS
Measures of Variability
It is often desirable to consider measures of variability
(dispersion), as well as measures of location.
For example, in assessing a health care cost provided by a hospi
Which of the following
statements
is not true regarding Type I and Type II errors?
Type II error occurs when we fail to reject a false null hypothesis.
, Type II error occurs when we fail to reject a false alternative
hypothesis.
Type-I error occurs when
1. To apply Central Limit Theorem on sample proportions
and the population
following
proportion
in One Sample Proportion
test, the sample size
under null hypothesis need to satisfy certain conditions. Which of the
scenarios meet the requirement?
Correct!
Module 1
An investigator wants to determine if state universities have student bodies that more
closely match the gender and ethnic composition of the U.S. population than private
universities. He obtains gender and ethnicity data from a random sample of