PH 490 A Final Study Guide:

SPSS:
o What is it?
Statistical Package for the Social Sciences
A powerful tool used to manage and analyze data
Menu driven
o What can I do with it?
Create a data file
Edit data
Manage data
Compute new variables
Recod
CHEM 200/202 Fall 2015 Final Exam A December 12, 2015
CHEM Lab Section Number:
Name (printed):
Signature:
This exam consists of 36 questions all of equal value for a total of 225 points.
Make sure that your test has all of the pages. Please read each prob
A
0
Sample multiple choice questions: final
1. A mining company wants to test a claim concerning the mean weight of their silver
nuggets. They are testing the null hypothesis that the true mean is 3 ounces, against the
alternative that the mean is less th
Sample final problem 1
A survey was conducted to determine the average loss in home value in
a certain community. A random sample of 23 homes found a mean of
$13120 with a standard deviation of $1600. Assume the necessary
assumptions are met. Which of the
The Estimate number of total population in the U.S, based on gender ,2013 ( as of July 1st)
States
male
Female
Total Population
San Diego
1,614,107
1,597,145
3,211,252
sacromento
715,668
746,463
1,462,131
Fresno
477,422
477,850
955,272
Los Angeles
4,942,2
2/27/2017
Analysis and
Interpretation I
week 6
Topics
Epidemiologic Measures and Analysis
Describing patterns
Summary Measures
Interpretation of health statistics
Interpretation!
1
2/27/2017
Epidemiologic Measures
Epidemiology defined:
the study of distr
Reference 511 age, male, white, and LA county
According to CHIS website data, in 20112015, the rate for whites who are diagnosed with asthma is
11.6%, for African American is 21.7%, and for Latino is 14.9%. To compare, whites have the lowest
percentage
Health Data Analysis II
1
Topics
Types of rates in Public Health:
Fertility and Mortality rates
Incidence and prevalence rates
Unstable rates
2
Measures in Public Health
Some other measures especially for
assessing community health
7 measures: different
Percent of Stroke among Californians by SES
Variable
SES
Median % of
Stroke
CI
Gender
Male
Female
1824
2534
3544
4554
5564
65+
White
Black
Hispanic
Other
MultiRacial
<$15,000
$15,000$24,999
$25,000$34,999
$35,000$49,999
$50,000+
<H.S.
H.S. or G.E.
HW#3 Health Data Online Sources (20 points)
Due date: 2/27, 10 points for each question.
General instruction:
A single spreadsheet for each question (HW31 ~HW32) in a single Excel file.
Apply color to tables and charts (make them easy to read).
Put titl
www.statl19review.com
Free Response
Use the following to answer problems 14:
The following is a list of the top 20 in total rebounds in all games for men's basketball in the Mountain West
conference in the 20112012season.
91
154
115
156
127
166
131
172
www.stat119review.com
Free Response
Use the following to answer problems 14:
The following is a list of the top 20 in total rebounds in all games for mens basketball in the Mountain West
conference in the 20112012 season.
91
154
115
156
127
166
131
172
3.94 Water ows in a rectangular channel that is 2.0 m wide as
shown in Fig, P394. The upstream depth is 70 mm. The water
sulface rises 40 mm as it passes over a portion where the chan
nel bottom rises 10 mm. If viscous effects are negligible, what is
the
Step 1: Identify Your Three Variables
Variable
SPSS Variable Name
Explain what it Measures
Death Penalty
CAPPUN
Those in favor of or opposed to the death
penalty
Abortion
ABANY
Those in favor of or against abortion for any
reason
Gay Marriage
MARHOMO
Thos
Variable
SPSS Name
Explain exactly what
this variable
measures
The respondents
subjective class
identification
Level of
Measurement
1. Class
identification
CLASS
2. Degree
DEGREE
The highest degree
obtained by the
respondent
Ordinal
3. Education
EDUC
High
1
Statistics 101B
Week ten session one
Professor Esfandiari
Further clarification of the ATS manuscript on logistic
regression
Outcome variable is being in the honor program
1 = being in the honor program
0 = not being in the honor program
predictor
Week 6 Lecture Two
Statistics 101A
Prepared by: Professor Esfandiari
Edited by: Akram Almohalwas
The objective of this lecture part of the lecture is to introduce you to analysis of covariance or
modeling with categorical variables.
Analysis of Covariance
1
Statistics 101B
Week nine
Session three
Professor Esfandiari
Remember from last session
H0 in logistic regression: The following model is
appropriate
(x) = 1/1+ exp(cfw_ 0 1 x)
Ha in logistic regression: The above model is
inappropriate.
Remember
1
Statistics 101A
Week nine  Session three
Professor Esfandiari
Edited by: Professor Almohalwas
8.1.3 Explanation of Deviance
In logistic regression the concept of the residual sum of squares is replaced by a concept
known as the deviance . In the case o
1
Statistics 101B
Week eight, Session two
Professor Esfandiari
The objective of this part of the lecture is to revisit variance inflation factor
resulting from multicollinearity and discuss how this problem can be dealt
with.
As we discussed last time, V
1
Week nine session two
Logistic Regression
Professor Esfandiari
So far we have talked about situations in which the
outcome variable is quantitative. In this lecture we are
going to talk about a situation in which the outcome
variable is binom
Statistics 101B
Week eights
Session Three
Professor Esfandiari
The objective of this part of the lecture is to continue the subject of variable
selection.
Last session we talked a
1
Statistics 101B
Week nine Session one
Professor Esfandairi
The objective of this lecture is to review the major concepts that we have discussed after
the midterm and relate them to what you
Statistics 101B
Week eights
Session Three
Professor Esfandiari
The objective of this part of the lecture is to continue the subject of variable
selection.
Last session we talked a
Statistics 101A
Prepared by: Professor Esfandiari
Edited By: Akram Almohalwas
The objective of this lecture is to talk about checking assumptions for multiple linear
regression.
The assumptions of MLR are the same as SLR. However, there are cases where mo