Probability critical to inferential statistics. Make statistical inferences about population from sample. With sample you cannot prove that something is true
about the population and determine the likelihood that it is true. Statistical independence the p

Parul Singh
GCU 495
Assignment 1
Stephanie Deitricks
Assignment 1
How many observations are there? There are around 400 observations including 12
variables. It is related to one another, example people in Buckingham has more higher
glucose level than the

Parul Singh
GCU 495
Assignment 1
Stephanie Deitricks
Assignment 1
How many observations are there? There are around 400 observations including 12
variables. It is related to one another, example people in Buckingham has more higher
glucose level than the

Parul Singh
GCU 495
Assignment 3
Stephanie Deitricks
Assignment 3
The Dependent variable is the variable, which is being measured in the
experiment and evaluated. Our dependent variable is glucose. The independent variable is
the variable in which you hav

Hypothesis testing is closely related to estimation. The diff. is that now we are posing a hypothesis that is to be tested. A statement defining the value of a
population parameter. Null is statement that defines a hypothesis. For every null hypothesis, t

Parul Singh
GCU 495
Assignment 3
Stephanie Deitricks
Assignment 3
The Dependent variable is the variable, which is being measured in the
experiment and evaluated. Our dependent variable is glucose. The independent variable is
the variable in which you hav

Parul Singh
GCU 495
Assignment 2
Stephanie Deitricks
Assignment 2
Group Statistics
Independent Samples Test
The Graph
The zero is outside of the confidence interval, we reject the null hypothesis that the
population means are equal and the difference betw

Parul Singh
GCU 495
Assignment 2
Stephanie Deitricks
Assignment 2
Group Statistics
Independent Samples Test
The Graph
The zero is outside of the confidence interval, we reject the null hypothesis that the
population means are equal and the difference betw

# GCU495 - Spring 2014 - Assignment 2 hints
# TIME SERIES SMOOTHING #
timeseries = read.csv(file.choose()
t = timeseries$value
# make a sequence and plot the original data
day = seq(1:length(t)
plot(day,t,type='l')
#make a 3-term filter and add a line to

# PROBLEM SET 3 HINTS - GCU495 #
#import data - riskfactors - and see what's inside
risk = read.csv(file.choose(), header=T)
colnames(risk)
# sometimes public data sources use crazy negative values (like -999.99, or something) to indicate that the data is

# GCU495 - Spring 2014 - Assignment 2 hints
# TIME SERIES SMOOTHING #
timeseries = read.csv(file.choose()
t = timeseries$value
# make a sequence and plot the original data
day = seq(1:length(t)
plot(day,t,type='l')
#make a 3-term filter and add a line to

# PROBLEM SET 3 HINTS - GCU495 #
#import data - riskfactors - and see what's inside
risk = read.csv(file.choose(), header=T)
colnames(risk)
# sometimes public data sources use crazy negative values (like -999.99, or something) to indicate that the data is