Stat 21 - Ibser - Quiz 1 - Feb 2, 2009 This quiz should be handed in during your section either Monday Feb 9 or Tuesday Feb 10. Your quiz will be scored for your own feedback, but you will get full points if you simply answer every question. In order to p
Quiz 2
Stat 21
1
Problem 1
We look at returns (in percentages) of the S&P 500 (SP) and the Dow Jones (DJ) from 2004 through February 11, 2009. This data split into 2 groups: before and after August 2007. Plots of the indices, their returns, and scatterplo
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- 0 ,0 1 , 3)
Neono ! i lf 3
ot (, 03 i) + 7 8 ff ,l JJ 9 0 a+ 7 8 r
= n 6X:
-(ne^n(x)
Ap/ l y , a/ t ,: e ", t , t ;nt p r.,uol s f D J
,f
Per,*l L
l:goa
x , ,= 3 8 s t
* ( -. r n
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thc , ,rlwle
Summation and Correlation The correlation coecient r can be written either 1 n (xi x) (yi y ) n i=1 SDx SDy The proof is as follows: 1 n (xi x) (yi y ) n i=1 SDx SDy 1 = n SDx SDy
n
or
1 n
n i=1
xi yi xy
SDx SDy
xi yi xi y xyi + xy
i=1
= = = =
1 n SDx S
STAT 21
SP 09
QUIZ 3 Solution
1. (3pts) (1) (1pt) standard unit of x = 0.33 (2) (1pt) multiply by r = 0.27 (3) (1pt) convert from standard unit to real data = 101. 2. (5pts) (1) (2pts) standard of unit of x = -0.2 multiply by r = -0.14 convert out of stan
Fall 2015 Statistics 21 Exam Cheat Sheet
Michael Tu
v A randomized controlled double blind study: [Steps] Define a research question and response variable Obtain a group of eligible
study units Randomly assign them to a treatment and control group Give pl
Statistics 21: Quiz 5
Due: April 20, 2009 Name: Student ID:
Instructions: Show your work this means provide a formula, plug in the appropriate numbers, and then give a nal solution. It is good practice to attempt to complete the quiz in 50 minutes. Good l
Stat 21 Fall 2013: Review problems for the nal: Solutions
1. Given below is a distribution table for the 1993 salaries (in thousands of dollars) of the top 60 small companies (according
to Forbes magazine). Each interval contains the right endpoint and no
Stats 21 Homework #12: (Katie Li)
#3 Exercise Set B Pg. 187
Answer: Person B makes the smaller r.m.s error (The error is smaller by 0.8)
because he took the correlation coefficient into account by using the regression
method. The error is smaller by sqrt
Stats 21 Homework #11 (Katie Li)
#2a pg. 167
Answer: About 79 percent; compare to example 2, the percentile rank for this
question is higher by 10 percent because the correlation is stronger (0.4 vs.
0.6). There is more regression to the mean in example 2
Stats 21 Homework #13 (Katie Li)
#2 Pg.214
Answer: y=1,600x-81,400; With every additional inch in height, the income
goes up by $1,600. When a person is 0 inches tall, he does not have a positive
income (but -$81,400 income!)
(0.2*20,000)/2.5= 1,600
y-21,
Stats 21 Homework #15 (Katie Li)
#3 Exercise A, Pg. 241
Answer- Most often: 7; least often: 2 and 12
It doesnt matter if the pair of dice is thrown 100 times or 1000 times, the total(s)
that appear most often and least often should theoretically stay the
Stats 21 Homework #18
#4 Pg. 261
Answer:
False. The binomial formula does not apply here because the trials are not
independent because its done without replacement. Since the trials are not
independent, p is not constant as 8/11 for every trial, so the c
Stats 21 HW #22
#11 Pg. 329
Answer:
a.) Number of 2s
b.) Sum of draws
Number of 2s:
Expected: 50
Observed:54
54-50=4
SE: Sqrt(100)*1*(Sqrt(.5*.5)= 5
1SE/5=X/4
X=0.8 SE
*Since the observed value is bigger than the expected, it is 0.8 SE above the expected
Stats 21 Homework #17
#11 Pg. 253
Answer:
a.) 0.0129 or 11/850, or about 1%
13/52*(12/51)*(11/50)= 0.0129
b.) (39/52)(38/51)(37/50)= 0.4135 or 703/1700, or about 41%
c.) This question is the opposite of the first one; 1-0.0129= 0.987 or 839/850, or
98.7%
Stats 21 Homework #19
#9 Pg. 286
Answer: (ii). By making 100 draws, we get a greater percentage of chance error,
meaning that there is a greater chance (percentage, in this case) to draw more blue
than red as opposed to drawing from the box 200 times. By
Stats 21 Assignment 24:
#1 Exercise Set A Pg. 361
Answer:
Population box [no need give or take]
Population Percentage- 40%
Sample- draws [need give or take]
Sample Size- 1,000
Sample Number- number of 1s among the draws
Sample Percentage- percentage of 1s
Stats 21 Homework #21
#2 Pg. 303
Answer: 99.7%
Box: 0 0 0 0 1
Expected Value: (1/5)(100)= 20
SE: [Sqrt(100)*Sqrt(1/5*4/5)]=4
(8-20)/4= -3
(32-20)/4=3
Between -3 and 3, we get 99.7% on the normal table.
#3 Pg. 319 (do with continuity correction so you are
Stats 21 Homework #16 (Katie Li)
1) Two cards are dealt from a deck of cards. Find the chance that neither card is
a diamond. Explain.
Answer: (39/52)(38/51) or 0.5588
There are 52 cards in a deck, in which 13 are diamond and 39 are not. The
probability t
Stats 21 Homework #20
#1 Pg. 304
Answer:
a.) Smallest: 100; Biggest: 1,000
The sum of draws can be as small as 100 if we draw 1 every single time across the
100 times that we are drawing a card. Similarly, the sum of draws can be as big as
1,000 if we dra
Stats 21 Homework #23
#5 Exercise A Pg. 349
Yes. Conducting polls by telephone could bring about bias, because people who use
telephone may be different from people who do not use telephone. (However, since a
vast majority of people are telephone subscrib
1
S TAT W 2 1 S P R I N G 2 0 1 6
Introductory Probability and Statistics for Business
Instructor: Shobhana Murali Stoyanov
ABOUT THE COU RSE
Statistics W21 is a service course designed primarily for Business students. Neither linear algebra
nor calculus
Stats 21 Homework #10
(Katie Li)
#4 Exercise A Pg. 161
Answer: $ 24,700
X= Years of education completed
Y= Income
X bar= 14 Sx = 2.4
Y bar= 32,000 Sy= 26,000
Zx (x in standard units)= (12-14)/2.4
= -5/6= -0.83333
Zy (y in standard units) = r*Zx
Zy= 0.34(-
Stats 21 Homework #7
Katie Li
#6 Pg. 106
a.) (650*500)+(600*500)/1000= 625
b.) The SD would be more than 125 because when we combine men and
women together, there is more variety involved, therefore the spread would
be bigger than 125.
#11 Pg. 106
Answer:
AMS 5
REGRESSION
Regression
The idea behind the calculation of the coefficient of correlation is
that the scatter plot of the data corresponds to a cloud that
follows a straight line. This idea can be formalized by regression
methods.
In this class we wil
Question 1:
A tennis player hires you to do an analysis on his serve shots. He wants to know on
average how much over the net does the ball go. Our tennis player wants the ball to go
as close to the net as possible without hitting it. Lets call this measu
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MENU
HOME
TEXT TABLE OF CONTENTS
ONLINE LECTURES
ASSIGNMENTS
CALCULATOR
TOOLS & DEMOS
BINOMIAL HISTOGRAM
CALCULATOR
CHI-SQUARE DISTRIBUTION
CONTROLLING FOR VARIABLES
CONFIDENCE INTERVALS
CORRELATION AND REGRESSION
HISTOGRAM
LAW OF LARGE NUMBERS
NORMAL AP
MENU
HOME
TEXT TABLE OF CONTENTS
ONLINE LECTURES
ASSIGNMENTS
CALCULATOR
TOOLS & DEMOS
BINOMIAL HISTOGRAM
CALCULATOR
CHI-SQUARE DISTRIBUTION
CONTROLLING FOR VARIABLES
CONFIDENCE INTERVALS
CORRELATION AND REGRESSION
HISTOGRAM
LAW OF LARGE NUMBERS
NORMAL AP