1.3 Density Curves and Normal Distributions Density Curve software can describe distribution by fitting a smooth curve to the data less arbitrary than choosing classes for histogram idealization that pictures the overall pattern of the data but ignor

Computer Problem Set 2 #1 Descriptive Statistics- Gas Mileage You dont have to hand in anything for #1. 1. Type in the gas mileage data starting in cell A1 (or just copy and paste).
13 15 16 16 17 19 20 22 23 23 23 24 25 25 26 28 28 28 29 32
2. Sele

Computer Problem Set 1 #1 Bar Graph 1. Insert the following data into an Excel worksheet. Education Less than high school High school graduate Some college Associate degree Bachelors degree Advanced degree Count (millions) 4.6 11.6 7.4 3.3 8.6 2.5 Pe

2.6 The Question of Causation Often the goal in a study is to establish that changes in the explanatory variable cause changes in the response variable. What constitutes good evidence of causation? What different types of links between x and y can ex

2.3
Least-Squares Regression
correlation measures the direction and strength of the linear relationship between two quantitative variables we would like to summarize the overall pattern by drawing a line on the scatterplot A regression line is a st

2.2
Correlation
scatterplots display the relationship between two variables linear (straight-line) relationships are important because they are quite common linear relationship is strong if points lie close to a straight line linear relationship is

1.2
Describing Distributions with Numbers Measures of Center
The Mean x The mean x of a set of observations is equal to the sum of their values divided by the number of observations. If the n observations are x1, x2, , xn, their mean is: x1 + x 2 +

1.2
Describing Distributions with Numbers Measures of Center
The Mean x The mean x of a set of observations is equal to the sum of their values divided by the number of observations. If the n observations are x1, x2, , xn, their mean is: x1 + x 2 +

Chapter 1 Introduction statistics- the science of learning from data data are numbers with a context- must know your field measurements from study are of little value without tools of statistics individuals- objects described by set of data (people,

3 Statistics notes from book 1.1 Individuals are objects described in a set of data. Sometimes people. When the objects that we want to study are not people, call them cases Variable any characteristic of an individual. A variab

Chapter 2- Looking at Data we often care about the relationship between two variables to study the relationship, we measure both variables on the same individuals Two variables measured on the same individuals are associated if some values of one var

PAM 210 Final Exam Preview Here is the Final Exam information: Tuesday, December 16 from 7:00-9:30 pm in Morrison Hall 146 Bring a calculator. Bring batteries for your calculator. Make sure your calculator is in floating decimal mode. You are not all

Book PS #4 Note that there are five questions on this problem set (two pages). #1) A student wonders if tall women tend to date taller men than do shorter women. Here are the data (height in inches): women (x) men (y) 66 72 64 68 66 70 65 68 70 71 65

Normal Quantile Plots How can you tell whether or not a distribution is normal? histogram or stemplot can tell us whether or not distribution is obviously nonnormal if distribution appears roughly symmetric and unimodal, need a more sensitive way to

PAM 210 Spring 2008 Professor Owens Problem Set 3 The Suggested Solutions 1)
relationship of crime/ violence concern between students with college plan and without
95
crime/violence concern for students w/o college plan
90
85
80
75
70
65
60 6

PAM 210 Spring 2008 Professor Owens Problem Set 2 The Suggested Solution 1) breathing rates X ~ N(12, 2.3) a) P(9.7<=X<=14.3)=P(9.7-12)/2.3<=Z<=(14.3-12)/2.3)=P(1<=Z<=1)=0.8413-0.1587=0.6826 (or, based on the empirical rule of a normal distribution,

PAM 210 Spring 2008 Professor Owens Problem Set 1: Suggested Answer 1) a) Population: every individual U.S. citizens from Generation X. Sample: randomly selected a sample from the population. Necessary variables: age, ethnicity, gender, parents occup

PAM 210
Second Prelim Review hollis e. cornell auditorium, goldwin smith hall (arts quad on east ave)
Different Types of Samples
Book covers five (one very general)
Probability Sample
Simple Random Sample Stratified Random Sample Multistage Sam

Cost
How much? - $138 million to create and run the REACH program. Who paid? - The majority of funds were produced or solicited by USAID.
Who spent it? -63 grants totaling $68 million were awarded to 29 NGOs to deliver health services, train health

PAM 210 Professor Owens Problem set 5 3.11 Subjects: random persons called by interviewer Factors/treatment: if interviewer provided name, university, name and university, and if interviewer said he/she would provide results; overall treatment is th

PAM 210 Professor Owens Problem Set 4 2/17/08 1)
Employment rate and food stamp participation tend towards opposite directions along the time series. As employment rate decreases, food stamp participation increases, and vice versa. 2) correlation co

Professor Owens PAM 210 Problem Set 3 2/10/08 1)
The direction for both relationships is negative and their strengths are quite strong. 2) a. mean=
n
i =1
n
xi
mean for students with college plans: 86.854 mean for students without college plans:

Professor Owens PAM 210 Problem Set 2 2/1/08 Question #1 a.
z score =
xi x s
;
14.3 12 =1 2 .3
9.7 12 = 1 2.3
z-score 1= .8413; z-score -1= .1587 area between 9.7 and 14.3 = .6826 b. ;
16.6 12 =2 2 .3
7.4 12 = 2 2.3
z-score 2= .9772; z-

PAM 210 Professor Owens Problem Set 1 1/26/08
Question #1:
a) Population of Interest: Generation X Collection of Sample: send surveys to a random sample of persons from Generation X asking if they are interested in starting their own business Variab

PAM 210 Professor Owens Problem set 6 3/9/08 1) a. mean: 16 Sd: 36 b. mean: -12 sd:
108
c. mean: 9 sd: 6 d. mean: sd: e. mean: sd: 4.46) a. probability that more than one person lives in this household: .73 b. .3 c. .67 4.52) a. .144 b. approve=a di

4.5
General Probability Rules Previous Probability Rules
1) The probability P(A) of any event A satisfies 0 P(A) 1. 2) All possible outcomes together must have probability 1. P(S) = 1. 3) Two events A and B are disjoint if they have no outcomes i