Applied Biostats
Descriptive Statistics: Summarize a sample (statistic) selected from a
population.
Inferential Statistics: Make inferences about population (parameter)
Variable Types
Dichotomous var
BS704 Assignment 1
Goals of the Assignment
Install R on your computer,
Enter data into an Excel spreadsheet for analysis,
Convert the Excel spreadsheet into a comma separated values (.csv) file for
BS704 Assignment 6
Goals of the Assignment
Conduct and interpret tests of hypothesis to compare groups with respect to
continuous and dichotomous outcomes by hand and using R.
Dataset for Analysis
A
BS704 Assignment 2
Goals of the Assignment
Distinguish variable types for analysis,
Create new variables using R,
Use R to generate descriptive statistics for different variable types, and
Summari
BS704 Homework 11
This assignment focuses on correlation and linear regression. R commands for computing the
correlation and running a linear regression model are described in Section 4.1 of the cours
BS704 Assignment 12
Goals of the Assignment
Interpret slope and y-intercept of simple linear regression model with a categorical
predictor,
Interpret slopes of multiple linear regression models,
In
BS704 Assignment 9
Goals of the Assignment
Conduct and interpret chi square goodness of fit tests by hand and using R, and
Conduct and interpret chi square tests of independence by hand and using R.
BS704 Assignment 10
Goals of the Assignment
Perform and interpret sample size calculations by hand and using R.
Description of the Study
A group of researchers are interested in estimating the mean a
BS704 Assignment 5
Goals of the Assignment
Compute confidence intervals for a mean and proportion by hand,
Compute confidence intervals for a mean and proportion using R,
Create new continuous vari
BS704 Assignment 8
Goals of the Assignment
Conduct and interpret analysis of variance in R, and
Conduct and interpret pairwise post-hoc tests in R.
Dataset for Analysis
This homework uses a masked d
BS704 Assignment 13
Goals of the Assignment
Perform logistic regression in R and interpret the results, and
Perform survival analysis in R and interpret the results.
Dataset for Analysis
These data
BS704 Assignment 3
Goals of the Assignment
Distinguish variable types for analysis,
Create new variables using R,
Use R to generate and compare frequency distributions of clinical risk factors in k
Standard summary: n, Mean, sd
Quartiles:
Q1 = LQ = first (lower) quartile holds approx. 25% of the scores at or
below it and
Q3 = UQ = third (upper)quartile holds approx. 25% of the scores at or
above
Normal Distribution
The normal distribution is symmetric about the mean:
(i.e., P(X > m) = P(X < m) = 0.5).
ii) The mean and variance, m and s2, completely characterize the normal
distribution.
iii) T
Central Limit Theorem for Non-Normal Distributions
=standard error(variability in sample mean)
Estimation
Goal - To make valid inferences about the population parameter based on a single
random sample
Percentiles of the Normal Distribution
The kth percentile is defined as the score that holds k percent of the scores below it.
For example: 90th percentile is the score that holds 90% of the scores be
Example Interpretation: Weare95%confidentthatthetrueproportionofpatients
onantihypertensivemedicationisbetween33%and36%
*when comparing Cis: suggests real significant difference if there is no overlap
Lecture 1
Observational studies inferences limited to descriptions and associations;
with carefully designed analysis can make stronger inferences (statistical
adjustment)
Case report: Detailed report
Experimental studies cause and effect
A type of experimental study where patients are randomized to receive
one of several comparison treatments.
- Advantages: Gold standard from a statistical point
BS704 Assignment 4
Goals of the Assignment
Use R to generate and summarize descriptive statistics on a sample of patients participating
in a study to evaluate the impact of an interactive web based a