University of Maryland School of Nursing: NRSG 795
Analysis #4: Multiple linear and logistic regression and sensitivity and specificity (10 points)
Background and Objectives
We asked young adults at our emergency clinic to complete a short survey at the e
Module 3 Project
The data we are about to use in this project is the score of standardized test scores over several years. The
population is the total number of students who took part of the test and had a score. The variable of interest
is tests score an
Math 110 Introduction to Statistics
Project
Question2
a) I choose to design an adjustable hat that will fit at 95% of men. Hat is a very
popular among young adult males. It is a clothing style for many teenagers.
From my research I found that about 60% of
Article #3
The pew Researches Institute published on their web sit the percentage of American
who favor the recent supreme court requesting employers, including most
religiously affiliated institutions, to cover birth control as part of their health care
According to the text, Statistics is the science of planning
studies and experiments, obtaining data, and then
organizing, summarizing, presenting, analyzing, interpreting,
and drawing conclusions based on the data. Write a paper
at least 3 pages long det
In chapter 5 we will find probabilities for normally distributed random
this will be done by converting the data points - x values to zscores as
how to convert an xvalue to a zscore
zscore = (X-mean)/sd
how to conovert a zscore to an xvalue
x= Z*sd + mean
parameter
s known? mean
m
m
p
m1-m1
m1-m1
p1-p2
yes
no
n/a
yes
no
n/a
x(bar)
x(bar)
p(hat)
x1(bar)-x2(bar)
x1(bar)-x2(bar)
p1(hat)-p2(hat)
upper
15.0631
center
7
lower
-1.0631
(Z*sd/E)^2
(1.96*20/6)^2
42.6844444444
p1(hat)
p2(hat)
0.0764166
0.0972599
se=
chapter 6: applying the central limit theorem to the parameter of prop
the distribution of sample proportions p(hat) will follow a normal dist
and standard error = sqrt(p*(1-p)/n)
as long as n*p>=10 and n*(1-p)>=10
EX: n = 70, p = .9
n*p= 70*.9 =63 and n*
2.4 identifying outliers using the IQR method
IQR = interquartile range
Q3-Q1
10
An outlier is any point in the data set such that it is either
ABOVE
Q3+1.5*IQR
85+1.5*10
100
Q1-1.5*IQR
75-1.5*10
60
or
BELOW
any point below 60 or above 100 is an outlier
I
chapter 2
2.4
how to detect outliers using the IQR
IQR = Q3 - Q1
any value above Q3+ 1.5*IQR
or
below Q1- 1.5*IQR is an oultlier
be able to understand boxplots
2.5
paired data (x,y)
x: explantory variable
y: response
relationship can be depicted in a scat
p is the true proportion
p has a
hypothesis testing
parameter
p
review
6.1/6.4 applying the central limit theorem
parameter
mean
p
p(hat)
m
x(bar)
m
x(bar)
6.2/6.5
s known
n/a
yes
no
finding cofidence intervals
basic form of a confidence interval
upper
po
2.3
I. the 95% rule
for bellshaped and symmetric data approximately 95% of the da
upper
x(bar)+2s
x(bar) = sample mean
center
x(bar)
mstandsforpopulation
lower
x(bar)2s
s stands for sample stan
II. How to find and interpret zscores
the zscore reprsents th
sd =
z = (.28-.25)/.01936
1.5492
z = (p(hat)-p0)/se
se = sqrt(p0*(1-p0)/n
p(hat) = .58, p0 = .5
n = 60
se = sqrt(p0*(1-p0)/n
z = (p(hat)-p0)/se
6.4 distribution of sa
central limit theorem
the distribuiton of n
mean equal to the m
and standard error =
EX:
Chapter 6 - 13 sections, but really 3 main concepts
in all of chapter 6 we are applying the central limit theo
I. find the mean, se, and distribution for a given parame
parameter
m
normal
p
normal
m1-m1
normal
p1-p2
normal
General Form of a confidence int
chapter 6 - Distributions, Confidence Intervals, Hypothesis testing
parameter
m
m
p
p1-p2
m1-m1
mean
x(bar)
x(bar)
p(hat)
p1(hat)p2(hat)
sknown
yes
no
n/a
yes
x1(bar)x2(bar)
yes
m1-m1
x1(bar)x2(bar)
no
to find a confidence interval for a
0.0681385144
uppe
in statistics, we wish to estimate a parameter
parameter
symbol
mean
m
proportion
p
correlation
r
standard deviation
s
slope
B
mean1-mean2
m1-m1
general form of a confidence interval
upper
point estimate + E
center
point estimate
lower
point estimate - E
Experiment vs Observational Study
In an experiment the researcher breaks the subjects into two groups:
the exeperimental group is given a treatment andt the control group i
and/or the explanatory varaible is actively manipulated
in an observational the re
in statistics, we wish to estimate a parameter
parameter
symbol
mean
m
proportion
p
correlation
r
standard deviation
s
slope
B
mean1-mean2
m1-m1
general form of a confidence interval
upper
point estimate + E
center
point estimate
lower
point estimate - E
parameters
mean
m
proportion
p
std. deviation
s
correlation
r
slope
B
difference
three possible hypothesis setups
h0: parameter = constant
ha: parameter not = constant
two-tailed test
possible results of a hypothesis test
reject H0 and accept Ha
or
do not
in statistics, we wish to estimate a parameter
parameter
symbol
mean
m
proportion
p
correlation
r
standard deviation
s
slope
B
mean1-mean2
m1-m1
general form of a confidence interval
upper
point estimate + E
center
point estimate
lower
point estimate - E
MATH 117
CRN: 34549
Elementary Statistics
M W F 11:00-11:50
Spring 2016
Science South 124
MONTGOMERY COLLEGE
Department of Mathematics
Takoma Park/Silver Spring Campus
I.
Instructor Information
Name: Mr. Stephen Kcenich
Telephone Number: (240)-567-1437/44
Project 1: Statistics in the Media
Children with their own cellphone:
This article is measuring how children receive cellphones at a young age. This variable is
quantitative. The cases are age and safety. There are specific statistics given that seem to
b
CHAPTER 1
1
Section 1.1 Solutions
1.1
(a) The cases are the people who are asked the question.
(b) The variable is whether each person supports the law or not. It is categorical.
1.3
(a) The cases are the teenagers in the sample.
(b) The variable is the r
Assignment 6: Corporate Culture
The following table lists ten cultural attributes that are frequently observed in successful,
innovative companies. The factors are chosen to be - as near as possible - orthogonal; i.e., each
can be encouraged without distu
Assignment 8: Change Management
Q1: Paradox: Jeff and Wayne hired their own replacements, yet they still had difficulty in giving
up control. Why was this? Illustrate this issue in particular in the case of Daves conflict with
Wayne.
Q2: Paradox: Despite
Assignment 7: Hiring and Firing
Q1: Is it better to hire someone you know than to hire a total stranger? How do you avoid the
Cassandra Problem when you are under pressure to hire quickly?
Q2: Imagine you are Jeff and Wayne. Create a set of interview ques
Assignment 6: Corporate Culture
The following table lists ten cultural attributes that are frequently observed in successful,
innovative companies. The factors are chosen to be - as near as possible - orthogonal; i.e., each
can be encouraged without distu
Assignment 5: Partners
Q1: Bad partners can destroy your company, but good partners are invaluable. Taking a partner as
an equal when you start a company immediately halves your potential upside; is this initial
dilution worth it? You are considering star
Assignment 4: Angels
Q1: Paradox: money and/or advice, is there a trade-off? Angels provide funding AND mentoring.
Is one fine without the other? What are the most important factors that you should take into
account when a) finding, and b) working with an
Assignment 3: Bootstrapping
Read the relevant sections in the book and view the related videos and then consider.
Q1: Paradox: Bootstrapping allows founders to have more control and give up less of their
company to investors, yet in a rapidly changing wor