Isabel Tern
Professor Mohammad Mirzaagha
Statistics 1
Part 3 Extra Credit
In inferential statistics we draw inferences, make statements, and reach conclusions
about an entire population by using sample results. The two types of inferential statistics
meth
Isabel Tern
Professor Mohammad Mirzaagha
Statistics 1
Extra Credit
Statistics deals with data: collection, organization, presentation, description, and
interpretation. Collecting data is the most important part of statistics and it has to be collected
car
If we have an idea what the value of a particular population parameter is, we can test
to see if thats a valid idea or not using the hypothesis testing procedures. If our hypothesis
involves just one population mean, we use the following steps to guide us
Project # 1
Regression
Date:_
Section: _
Name: _
Use the data and plot them as a scattered diagram on the provided graphs below.
Rather plotting the data, you can use excel to do scattered diagram and then copy graphs and paste it to this document
Answer
1. The table below presents the arterial blood pressures, in millimeters of mercury (mm Hg), for a
sample of 16 children of diabetic mothers:
68.5 73.6 77.8 80.5 82.2 83.0 84.9 85.3
85.7 86.1 86.6 87.8 89.9 91.5 93.7 98.8
(a) The five number summary of th
STAT 1, MT Exam 2, Fall 2011
11/21/2011
Instructions. Write your name and section in the space below, read these instructions but dont
start the exam before you are told so. You are allowed to use a calculator however you need to
show your work to get ful
Chapter 14. Descriptive Methods in
Regression and Correlation
Section 14.1
Linear Equations with One
Independent Variable
Assume that we are trying to explain a quantitative variable y with
another quantitative variable x. Then, we use the following terms
STAT 1, Discrete RVs
1. Let X denote the number of cars of the households in a town of about 5,000 households.
(a) Using the probability distribution of X which is given below, compute the mean and
standard deviation of X.
x
p(x) xp(x) x2 p(x)
0
0:20
0
0
STAT 1, Normal Approximation to Binomial, Spring 2016
Let X denote a random variable with B(n; p) distribution.
Then, we know that the mean of
p
X is
= np, while its standard deviation is
= np(1 p). We have seen many examples
during the lectures that when
Stat 1, Formula Sheet for Test #1, Spring 2016
P
Sample mean: x = ( xi )=n, where n is the sample size.
s2x
=
P
(
P
x2
n 1
x)2
n
(computing formula).
qP
P
x2 ( x)2 =n
Sample standard deviation: sx =
(computing formula).
n 1
Sample variance:
z-score of a s
STAT 1, Regression-Correlation Formulae, Fall 2013
P
Sample mean: x = ( xi )=n, where n is the sample size.
Notation and summation expressions used in linear regression and correlation coe cient.
Quantity
Sxy
Sxx
Syy
Dening formula
P
(xi x)(yi y)
P
(xi x)
Hypothesis is a claim: testing whether or not a claim is valid.
Ex most people get their jobs thru networking
Is a proportion , most more than 50%
p>.50
the average payload of truck on the 99 is 18 000 lbs
M = 18 000
Rare event rule : if the probability o
Stat 1 Introduction to Statistics
Practice Test for Exam 1 Chapters 1, 2 & 3
Directions: Show all work in the space provided. You are allowed to use 1 page of handwritten notes (double-sided). You may use a scientific calculator (please, do not use the
ca
Stat 1 Introduction to Statistics
Practice Test for Midterm Exam 3 (Chapters 6, 7 & 8)
Directions: Show all work in the space provided. You are allowed to use 1 page of hand-written
notes (double-sided). Use the back of the test if you wish. You may use a
Stat 1 Introduction to Statistics
Practice Test for Midterm Exam 2 Chapters 4 & 5
Directions: Show all work in the space provided. You are allowed to use 1 page of handwritten notes (double-sided). Use the back of the test if you wish. You may use a scien
Lecture 2:
Collecting Sample Data
CRamirez - Lecture 2: Copyright 2010, 2007,
1.1 - 1
Key Concept
If sample data are not collected in an
appropriate way, the data may be so
completely useless that no amount of
statistical torturing can salvage them.
Met
Lecture 1
Introduction to Statistics
CRamirez - Lecture 1: Copyright 2010, 2007,
1.1 - 1
Preview
Polls, studies, surveys and other data
collecting tools collect data from a small
part of a larger group so that we can
learn something about the larger group
Chapter 11
Inferences on Two Samples
Using TWO Samples
to compare
TWO Populations
Overview
The goal of this chapter is to compare two sets of data,
representing two populations, in order to test claims
about how the two populations compare to each other.
Unit 3
Chapter 9, 10 & 11
Inferential Statistics
Using samples to make
predictions about a population
Section
9.1
Confidence
Interval
Estimates for
the Population
Mean
( Known)
Carefully obtaining individuals to
participate in a survey or appropriate
desi
Chapter
10
Hypothesis
Tests
Regarding a
Parameter
Steps in Hypothesis Testing
1. A claim is made.
Steps in Hypothesis Testing
1. A claim is made.
2. Evidence (sample data) is collected in
order to test the claim.
Steps in Hypothesis Testing
1. A claim is
Section
8.1
Distribution
of the Sample
Mean
Sampling Distributions
Demonstration:
Open Lab 5: Central Limit Theorem
http:/media.pearsoncmg.com/ph/esm/esm_s
ullivan_stats_2/applets/Lab_Manual_Apple
ts/lab_5/index.html
Sampling Distributions
Demonstration:
Additional Topics
Chapter 12 & 13
(12.2) Chi-square Test for Independence
&
One-Way Analysis of Variance (ANOVA)
Introducing Chi-Square
Several important statistical tests use a probability
distribution known as chi square, denoted .
distributions for
We
Chapter 4
Describing the Relation
Between Two Variables
Ch. 4
Revisted
Regression & Correlation
Correlation
Definition: Correlation is a relationship
between two variables
Explanatory
(Independent) Variable
x
Hours of Training
Score on SAT
Height
Response