One University Avenue
Lowell, Massachusetts 01854
phone:
978.934.2410
Alexander A. Olsen, PhD
fax:
978.934.3053
Professor of
Mathematical Sciences
email: [email protected]
Web site: http:/www.uml.edu/Dept/Math/
O ffi c e: O H 4 28
SYLLABUS 92.283 b
Topics for Week 5
92.283
A.A.Olsen
Correlation coefficient (r), coefficient of determination (rsquared), scatterplot, simple
regression analysis, least squaresbest fit line
Correlation and the regression equation
Correlation describes the strength of an
Topics for Week 3
92.283
A.A.Olsen
Quick Summary notes on Numeric descriptive statistics:
1)
Central tendency
Mean sample is symbol xbar, population symbol is ( mu) ; arithmetic average
found primarily for scale data; affected by outlier and skewed dist
Topics for Week 4
92.283
A.A.Olsen
Empirical rule, standard scores (zscores), normal distribution, intro. to correlation
analysis, bivariate data independent (x) and dependent (y)
Empirical Rule (689599.7 % Rule)
Empirical Rule : If the histogram of t
Skewness/Kurtosis
Skewness is the degree of departure from symmetry of a distribution. A
positively skewed distribution has a "tail" which is pulled in the positive
direction; if is a distribution of exam scores, it means there are many
more lower scores
92.283 Introduction to Statistics
Exam 2
Name:_Ross Marchegiani_
March 6, 2015
1. A random sample of 1001 University of California faculty members taken in December 1995
was asked, Do you favor or oppose using race, religion, sex, color, ethnicity or nati
Chapter 17: Tests of Significance: The Basics
Chapter 18: Inference in Practice
In the last lesson, we learnt how to use the sampling distributions of statistics to
approximate the parameters of populations in particular, their mean, or . We did this
by f
Chapter 8:
Producing Data: Sampling
Chapter 9:
Producing Data: Experiments
Now that we can describe data with (and interpret data from) distributions, the question
naturally arises: from where do we get our data? This is more of the realm of the
scientist
Chapter 4:
Scatterplots and Correlation
Chapter 5:
Regression
Remember that data are the observed values of variables taken by individuals in a
population. Until now, weve been looking at data that considers only the observed
values of a single variable,
Chapter 2:
Describing Distributions with Numbers
To further describe quantitative distributions, we can find certain measures, which are
results of functions applied to the data. We represent the number of observations in our
dataset as . If we look at ou
Chapter 3:
The Normal Distributions
So far, weve explored categorical and quantitative data and representations of it. This
week, we will continue looking at quantitative data and introduce an important new
model of it: the Normal distribution.
While a hi
Chapter 6:
Two Way Tables
Suppose that we want to compare two categorical variables. If we hope to analyze them
mathematically, we must look at proportions of individuals with pairs of values for the
variables. We do so by considering the number of indivi
BASIC STATISTICS
Descriptive Analysis (Graphical)
Dealing with Uncertainty
Everyday decisions are based on incomplete
information
Consider:
Will the job market be strong when I graduate?
Will the price of HELPs stock be higher in six months
than it is n
Chapter 1
INTRO TO STATISTICS
The term statistics refers to a set of mathematical procedures for organizing,
summarizing, and interpreting information.
Statistics serve to general purposes:
1. Statistics are used to organize and summarize the information

D R H J H M AD I H AH K H AL I D

a Mathematicians need to be clear and concise when
they communicate.
a The language of mathematics is better at
communicating quantitative information than day to
day language.
a How best do I communicate my work? T
STATISTICS
 a branch of mathematics dealing with the collection, analysis, interpretation, and presentation of masses of
numerical data (MerriamWebster)
 branch of mathematics that deals with the effective management and analysis of data.
 the science
Introduction to Statistics
STATISTICAL ANALYSIS
Introduction
to
Statistics
Page 1
Objectives
To define statistics
To discuss the wide range of
applications of statistics
To discuss key statistical concepts
To understand the branches of
statistics
To
STAT 520
SUARAY
Mathematical Statistics Ch4,5 Review
PROBLEM: Let X1,.X n ~ Unif ( , 0), > 0.
A. Find an unbiased estimator for based on Yn = min(X1,.X n ) . Call this estimator
.
1
B. Find a consistent estimator for based on the weak law of large number