Bivariate Data part 1 (both
variables are categorical)
When two variables are measured on a single
experimental unit, the resulting data are called
bivariate data (height and weight).
You can describe each variable individually, and you
can also explore
Bivariate Data part 1 (both
variables are categorical)
When two variables are measured on a single
experimental unit, the resulting data are called
bivariate data (height and weight).
You can describe each variable individually, and you
can also explore
Bivariate Data part 1 (both
variables are categorical)
When two variables are measured on a single
experimental unit, the resulting data are called
bivariate data (height and weight).
You can describe each variable individually, and you
can also explore
Bivariate Data part 1 (both
variables are categorical)
When two variables are measured on a single
experimental unit, the resulting data are called
bivariate data (height and weight).
You can describe each variable individually, and you
can also explore
Bivariate Data part 1 (both
variables are categorical)
When two variables are measured on a single
experimental unit, the resulting data are called
bivariate data (height and weight).
You can describe each variable individually, and you
can also explore
Bivariate Data part 1 (both variables are
categorical)
Example : Data were collected to measure the effect of
the body weight on the blood pressure in individuals
aged between 15 and 30.
Sample unit: individual aged between 15 and 30.
Variables measured i
DEPARTMENT OF MATHEMATICS AND STATISTICS
UNIVERSITY OF MASSACHUSETTS AT AMHERST
STATISTICS 111
SYLLABUS
SPRING 2017
Instructor: Brian Burrell, 1244 LGRT, ph: 545-0924, email: [email protected]
Textbook: Seeing Through Statistics (3rd edition) by Jess
Group Names:
Sam Asamoah (Hachem), Kevin Boino (Nguyen), Steve Ravazzoli (Wu Mengyuan),
Ryan Saul (Hachem)
Topic:
Number of hours a person spends on their phone per day
Method:
Estimation of population a mean
Cellphones have seemingly become a necessity f
To download Minitab - 30-day free trial - go to:
http:/www.onthehub.com/minitab/
If you are Mac user , you have to choose Minitab Express , if you are Window user - Minitab 17
is a better choice.
Lab 1 Minitab .
Refer to the data: Blood Pressure for men a
Chapter 4.1-4.4. Probability .
Remember the objective:
Probability
1.
Population
Sample
2.
Describe the
sample data
3.
Probability
Compute measures of
variability
4.
1
Why the price of a car insurance changes when you turn
24?
The price depends on how lik
Bivariate Data part 1 (both variables are
categorical)
Example : Data were collected to measure the effect of
the body weight on the blood pressure in individuals
aged between 15 and 30.
Sample unit: individual aged between 15 and 30.
Variables measured i
My UMass Amherst
H
Course material
STATISTC
240
J.Jeneralczuk
Spring17
SPIRE#19893
.
Chapter 3 - part 1
Handout -Chapter 3.2 and 3.4
Handout -Chapter 3.2 and 3.4
Jane Norton
Help & Resources
My UMass Amherst
H
Course material
STATISTC
240
J.Jeneralczuk
Spring17
SPIRE#19893
.
Summary .pdf
Chapter 3 - part 1
Summary .pdf
Jane Norton
Help & Resources
Stat 111/Spring 2017
Practice Midterm Exam
1. The following questions apply to the aspirin/heart attack study described in Chapter 1.
a) Was this an observational study or a randomized experiment?
b) On the basis of this study, can you conclude that an as
Stat 111/Spring 2017 Practice Midterm Exam KEY
1. The following questions apply to the aspirin/heart attack study described in Chapter 1.
a) Was this an observational study or a randomized experiment?
randomized
b) On the basis of this study, can you conc
Stat 525
Fall 2016 Midterm Exam Practice Problems.
Location and Time:
The Midterm Exam is Wednesday, Oct. 26, 7:00 9:00 pm, in Lederle Lowrise Room A301.
This is in the lowrise building across the courtyard from Lederle Tower.
Coverage:
The Midterm Exam w
Statistics 525: Regression Analysis, Fall 2016
NOTE: The SAS programming language is required for this course. SAS is not available for
Macintosh computers. See information on SAS below under "Computing".
Instructor:
Erin Conlon
Contact:
Office LGRT 1436,
Stat 525
Fall 2016 Midterm Information
Location and Time:
The Midterm Exam is Wednesday, Oct. 26, 7:00 9:00 pm, in Lederle Lowrise Room A301.
This is in the lowrise building across the courtyard from Lederle Tower.
Coverage:
The Midterm Exam will cover Te
Stat 525: Fall 2016 IE Project Topics
The following are descriptions of projects for the IE component of Stat 525. The
number of groups w i l l be limited due to time constraints when projects are presented
in class at the end of the semester.
1. Baseball
The Integrative Experience (IE) component of Stat 525, Fall 2016
-See Due Dates Below, with Assignment Information.
-The TA for the course is available to help with computing questions. See the website for office
hours of the TA.
Integrative Experience
St
Robert Bucchianeri
September 16, 2015
Stats 240
Chapter 1 Notes:
1. Statistics is the science of collecting, analyzing, presenting, and interpreting data, as well
as of making decisions based on such analyses.
2. The whole set of numbers that represents t
Chapter 8.1/8.2:
1. The assignment of values to a population parameter based on a value of the corresponding
sample statistic is called estimation.
a. is called the true population mean and p is called the true population proportion.
b. Ex: to estimate th
Chapter 5.1 5.3:
1. The process of randomly selecting a family is called a random or chance experiment.
a. A random variable is a variable whose value is determined by the outcome of a
random experiment.
i. A random variable that assumes countable values
Chapter 9.2 l-lypotltesis tests about It: a known
Case I. If the following three conditions are fulfilled:
I. The population standard deviation 6 ist known
2. The sample size is small (i.e. a < 30)
3. The )OpllltlllOIt from which the sample is selected is