John Lorge
N13495925
John Lorge
Answer Sheet, Homework 2
1.
a) The histogram seems to have a reasonably bell shaped distribution with no outliers.
b) The mean is 98.6 degrees Fahrenheit.
c) Yes, the histogram mean is reasonably close to the 98.6 mean. Whi
HW 1
1) A group of college students believes that herbal tea has remarkable restorative
powers. To test this belief, they make weekly visits to a local nursing home,
visiting with the residents and serving them herbal tea. The nursing home staff
reports t
+
Machine Level Programming:
x86-64 History
+
Intel x86 Processors
Dominate laptop/desktop/server market
Evolutionary design
Backwards compatible up until 8086, introduced in 1978
Added more features as time goes on
Complex instruction set computer (CISC)
4.8 (Continuous Distribution);
a) Using following values :
Y
0
FY 0
1
2
3
4
5
6
7
8
9
10
0.04
0.08
0.12
0.16
0.2
0.16
0.12
0.08
0.04
0
The diagram will be:
b) looking at the graph, we can see it is symmetric, therefore without computing the integral and
b
Stat 2470, Exam #1, Fall 2014
Name _
Instructions: Show all work. Use exact answers or appropriate rounding conventions. If you use your
calculator, you can show work by saying which calculator commands you used.
1. a. Determine the mean and standard devi
Manana Asatiani
3.14,
Y= the number required of the next applicant
p(y)=ky for y=1,.,5
a)
5
p(y) = 1 => k + 2k + 3k + 4k + 5k = 1 15k=1 k=1/15
y=1
3
b) The probability that at most three forms are required will be p(y) =k+2k+3k
y=1
=6k=6*1/15= 6/15=0.4
c
7/23/2017
Question 1
1pts
1) In the oil industry, water that mixes with crude oil during production and transportation must
be removed. Chemists have found that the oil can be extracted from the water/oil mix
electronically. Researchers at the University
Name
Begg,Jonathan Edward
Budaeva,Aleftina S
Chen,Jesse
Davidoff,Elena
Davis,Christian
Frenkel,Andrew
Garcia,Luis
Gioia,Dom
Khiskiadze,Victoria
Kong,Renee Jiahui
Laurenzi,James
Lin,Yanyu
Liu,Henry
Mitchell,Kenneth J
Salgueiro,Celio C
Schafer,Matthew R
Tal
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Inferences Based on Two Samples Solutions
STAT-UB.0103 Statistics for Business Control and Regression Models
Comparing Two Populations
1. Here are boxplots of the passing distances (in meters) for a bike rider with and without a
helmet. Is there evidence
Condence Intervals Solutions
STAT-UB.0103 Statistics for Business Control and Regression Models
Condence Interval
1. A random sample of 36 measurements was selected from a population with unknown mean
and known standard deviation = 18. The sample mean is
STAT 226 F - HANDOUT 5
SAMPLING DISTRIBUTION AND CENTRAL LIMIT THEOREM
1. Biscuits. University of Louisville researchers J. Usher, S. Alexander, and D. Duggins examined
the process of ﬁlling plastic pouches of dry blended biscuit mix (Quality Engineering,
Sampling Distributions
Content
1. The Concept of a Sampling Distribution
2. Properties of Sampling Distributions:
Unbiasedness
3. The Sample Distribution of the Sample
Mean and the Central Limit Theorem
Learning Objectives
Establish that a sample statist
The Central Limit Theorem Solutions
STAT-UB.0103 Statistics for Business Control and Regression Models
The Central Limit Theorem
1. You draw a random sample of size n = 16 from a population with mean = 100 and standard
deviation = 20. From this, you compu
Statistics for Business Control,
Regression and Forecasting Models
Instructor: Xi Chen
1
Course Information
Instructor: Xi Chen ([email protected] )
Office: KMC 8-50
Office Hours: Tue, Thu: 11:00 AM to 12:00 AM
Teaching Fellow: Sen Tian ([email protected]
Chapter 8
Inferences Based on Two
Samples: Confidence Intervals
and Tests of Hypothesis
Content
1. Target Parameter: difference between two
population means
2. Comparing Two Population Means:
Independent Sampling
3. Comparing Two Population Means: Paired
Discrete Random Variables Solutions
STAT-UB.0103 Statistics for Business Control and Regression Models
Discrete random variables: PDF & Expectation
1. Consider the following game:
1. You pay $6 to ip a coin.
2. If the coin lands heads, you get $10; otherw
Chapter: 2
Methods for Describing
Sets of Data
What we will learn?
1. Describe data using graphs
2. Describe data using numerical measures
(summary table and statistics)
2
Data Presentation
Data
Presentation
Qualitative
Data
Quantitative
Data
Summary
Tabl
Course Outline Spring 2014
STAT-UB.0103.004 Statistics for Business Control and Regression Models
Meeting Time & Place
Lectures: Tuesday, Thursday, Friday: 9:30 AM 10:45 AM
Final Exam: May 14th (Thursday) 8:00 AM 9:50 AM
Midterm 1: Feb 27th (Friday) 9:30
Statistics for Business and
Economics
Chapter 12
Multiple Regression and Model
Building
Learning Objectives
Introduce a multiple regression model as a
means of relating a dependent variable y to
two or more independent variables
Different multiple regress
Statistics for Business and
Economics
Chapter 11
Simple Linear Regression
1
Introduction
Usually one of the variables is naturally
seen as causing, influencing, or
predicting the other variable
X variable
independent variable, predictor, explanatory
va
Complementary Events / Counting Solutions
STAT-UB.0103 Statistics for Business Control and Regression Models
Probability
1. When rolling a die, event the outcome is even. What is the probability of the event ?
Solution: There are 6 elementary outcomes, al
Introduction to Linear Regression Solutions
STAT-UB.0103 Statistics for Business Control and Regression Models
Linear Regression
1. Consider two variables measured on 294 restaurants in the 2003 Zagat guide:
y = typical dinner price, including one drink a
Objective(s) of Statistical
Analysis:
Data Reduction
Inference
Identification of Associations/Relationships
Statistical thinking will one day be
necessary for the efficient citizenship as the
ability to read and write H.G. Wells
Age of Data Explosion h
Section 9.2 - Linear Regression
Algebraically, a regression line is the same as the equation for a
line: y = a + bX (where a is the y-intercept and b is the slope
of the line). n = number of points in the scatter diagram.
However, to make sure we get the