8
Hypothesis Testing:
OneSample Case for
the Mean
Key Concepts
Hypothesis testing
Hypothesis
Null hypothesis
Alternative hypothesis
Type i error
Type II error
Level of significance (alpha level)
Region of rejection
Critical values
J
Totailed (nondirection
SECTION 4:
Combining data sets using MERGE, UPDATE, PROC APPEND. Using
FIRST. and LAST.BY variables and lN= to select records.
A. Example data: The Childrens Health Study
3
Research questions
1
2.
Does air pollution have adverse respiratory health effects
17
;K
Key Concepts
Linear Regression:
Estimation and Hypothesis
Testing
Linear regression equation
Regression eoetficieitt (Ii)
Regression constant lo I
Standard error of estimate
Hontoseechisiteit
Standard error ot the regression coetttcieni
Conditional
11
x
Key Concepts
Hypothesis Testing:
Two-Sample Case for
the Mean
Independent samples
Standard error of the difference
between means
Confidence interval for the difference
between means
Pooled estimate of the population variance
Assumption of homogeneity
Week 6 SAS Functions
CGH312 Data Analysis
Using SAS
1
SAS Functions
SAS provides a large library of functions
for manipulating data during DATA step execution.
A SAS function is often categorized by the type of
data manipulation performed:
2
Array
Charact
Week 2 Inputting Data
CGH312 Data Analysis
Using SAS
1
The DATA Statement
The DATA statement begins a DATA step and provides
the name of the SAS data set being created.
DATA
DATAoutput-SAS-data-set;
output-SAS-data-set;
INFILE
INFILE'raw-data-file-name';
SECTION 7:
A.
Testing hypotheses about means using t-tests and about medians
using non-parametric tests
Hypothesis testing in general
Objective framework for making scientific conclusions based on a sample
Uses proof by contradiction (innocent until prove
Computing New Variables in SAS
The SAS Data Step is a powerful and flexible programming tool that is used
to create a new SAS dataset. A Data Step is required to create any new
variables or modify existing ones in SAS. The Data Step allows you to assign
a
Normal Distribution
CGH301 Principles of Biostatistics
1
Normal Distribution
An underlying distribution based on the normal
curve.
The normal distribution is one of the most
commonly used underlying distributions in
inferential statistics.
The frequenc
CGH301 Lab
1
Z-test for Proportions
(Example 1)
A national study of homeless young people (ages
18 to 24) found that half (50%) are female. Is our
Los Angeles sample similar to the national study
in terms of gender at the .05 level of
significance?
Infor