8/8/2019 2013 S1 Final Exam
1/13
THE UNIVERSITY OF NEW SOUTH WALES
SCHOOL OF ECONOMICS
ECON 1203
BUSINESS AND ECONOMIC STATISTICS
FINAL EXAMINATION
SESSION 1, 2013
1. TIME ALLOWED – 2 HOURS
2. READING TIME
–
10
MINUTES
3. TOTAL AVAILABLE MARKS – 60
4. TOTAL NUMBER OF QUESTIONS – 3
5. PLEASE ATTEMPT ALL QUESTIONS. QUESTIONS ARE NOT OF EQUAL VALUE.
6. THE FIRST TWO QUESTIONS ARE EACH WORTH 18 MARKS. THE THIRD QUESTION
IS WORTH 24 MARKS. MARKS FOR PARTS OF QUESTIONS ARE SHOWN.
7. ON THE
FRONT
OF
YOUR
ANSWER
BOOK,
WRITE
THE
NUMBER
OF
EACH
QUESTION YOU HAVE ATTEMPTED.
8. STATISTICAL TABLES AND USEFUL FORMULAE ARE PROVIDED AT THE END OF
THE EXAMINATION PAPER.
9. ALL ANSWERS MUST BE WRITTEN IN PEN. PENCILS MAY BE USED ONLY FOR
DRAWING, SKETCHING OR GRAPHICAL WORK.
10. CANDIDATES MAY BRING THEIR OWN NON‐PROGAMMABLE CALCULATOR TO
THE EXAM.
11. THIS PAPER MAY BE RETAINED BY THE CANDIDATE.
8/8/2019 2013 S1 Final Exam
2/13
2
Question
1
[18
marks
in
total]
The Human Resource Department of a large company routinely surveys staff and
amongst the list of questions asked typically includes the number of hours of exercise
they participated in per week and their level of job satisfaction on a scale of 0 to 100
where 0 is the lowest and 100 the highest level of satisfaction. Past experience based on
many surveys
has
demonstrated
that
hours
of
exercise
has
a mean
of
3.5
hours
and
a
standard deviation of 4.5 hours while job satisfaction has a mean of 75 and a standard
deviation of 9.
(i) The Human Resource Department has previously found that the distribution of
job satisfaction scores to be approximately normally distributed. What key
features of this distribution would have led them to consider the normal
distribution to be a good approximation? [2 marks]
(ii) Assuming normality, what is the probability that a randomly drawn staff member
has a satisfaction score greater than 72? [2 marks]
(iii) Again assuming normality, which would be more unusual, a staff member with a
satisfaction score more than 95 or one with a score less than 60? Why? [2 marks]
(iv) Suppose we also assume hours of exercise to be normally distributed. What
proportion of staff will exercise less than one standard deviation below the mean
number of hours? What does this mean? Explain why the normal distribution is
not a good model for hours of exercise in this situation? [3 marks]
(v) Suppose the company has become worried about staff fitness levels and how
that impacts on their health and ultimately their productivity. A new policy
involving changed work arrangements and incentives are being considered that
are aimed at encouraging staff to increase their levels of exercise. Suppose the
initial plan is to ask for a group of volunteers to be subject to the new policy, the
treatment group;
and
for
their
exercise
levels
to
be
compared
to
a control
group
not subject to the new procedures and incentives. Do you think this is a good
approach to testing the effectiveness of the new guidelines? Explain. [2 marks]
(vi) Ultimately it was decided to implement the new policy for all staff. Assume that
if the new policies have an impact they will only change the distribution of hours
of exercise by increasing the population mean hours of exercise. Thus you can
assume the standard deviation remains unchanged. It is a year since these
changes were implemented and the company now wants to test whether the
changes have been effective in increasing mean hours of exercise. What would
be the null and alternative hypotheses? Suppose a random sample of 81 staff is
taken
and
their
average
hours
of
exercise
are
found
to
be
4.3
hours.
Test
the
hypothesis that the changes have been effective using a significance level of =
1%. Make clear all assumptions that are needed to justify your calculations. [6
marks]
(vii) Can you think of one problem with the strategy for testing the impact of the new
exercise policy that was outlined in (vi)? [1 mark]
8/8/2019 2013 S1 Final Exam
3/13
3
Question
2
[18
marks
in
total]
Real estate analysts routinely collect statistics on auction clearance rates where the
clearance rate is defined as the proportion of properties offered for auction that are
actually sold. They provide a good indicator of the state of the housing market and for
individual real estate agents they present evidence on how good they are at selling the
properties of
their
clients.
The
following
table
provides
a survey
of
outcomes
(sold
or
did not sell) for recent Sydney residential property auctions. These have been further
categorized by whether the property was a house or whether it was a unit.
Table
1:
Auction
outcomes
in
Sydney
according
to
property
type
Sold Did not sell Totals
House 297 162 459
Unit 54 61 115
Totals
351 223 574
(i) Given this sample what is the overall estimated clearance rate? [1 mark]
(ii) In recent times the clearance rates have been steady at 0.6 (or 60%). Do the
results in Table 1 provide evidence that actual clearance rates have increased?
Set up a formal hypothesis test stating the null and alternative hypotheses. Use a
5% significance level and perform the test making clear all assumptions that are
needed to justify your calculations? [5 marks]
(iii) Randall, a prominent real estate analyst has proclaimed in his newsletter that he
will not be convinced that the actual clearance rates have increased until the
surveyed rates reach 0.65 (or 65%). Randall’s position can be viewed as a
hypothesis test using the same null and alternative hypotheses used in part (ii)
but with
a different
significance
level.
Given
the
decision
rule
decided
upon
by
Randall, what is the implied significance level of his test? [2 marks]
(iv) What is a Type II error for the particular test used in (ii)? Calculate the probability
of a Type II error if the true population clearance rate is equal to 0.62. [2 marks]
(v) Find the 99% confidence interval for the population clearance rate. What does
this imply about whether the clearance rate has increased? Is this different from
what you concluded in (ii) and if so why? [3 marks]
(vi) If the outcome of whether the property sold or not was independent of the type
of property what would we expect to find in terms of the estimated clearance
rates for houses and units? Test the hypothesis that whether the property sold
or not
was
independent
of
the
type
of
property.
Use
a significance
level
of
1%.
Be sure to state clearly your hypothesis, decision rule and conclusion. [5 marks]
8/8/2019 2013 S1 Final Exam
4/13
4
Question
3
[24
marks
in
total]
At the recent finance committee meeting of a large supermarket chain there was a
discussion about whether to increase the budget allocated to advertising their home
brand range of canned tuna. The Advertising Manager presented evidence from a
sample of weekly sales figures where in some weeks the supermarket advertised in the
local newspapers
and
erected
in
‐store
displays
to
advertise
their
home
brand
tuna
while
in other weeks they did not advertise. The evidence presented was based on the
following simple linear regression model:
(1) salesi = 0 + 1adv i + ui
where: salesi is the weekly sales in thousands of dollars for week i ; adv i is an indicator
variable taking the value 1 if advertising took place in week i and taking on the value
zero otherwise; ui is the disturbance term; and 0 and 1 are unknown parameters.
Using a sample of 52 weeks, ordinary least squares was used to estimate model (1) and
results
and
a
portion
of
the
resultant
EXCEL
output
for
this
regression
analysis
are
provided in Table 2.
The General Manager was cautious and didn’t want to make a final decision on the
advertising budget before he received further analysis of the data from his marketing
research department. Eventually the General Manager received back a report based on
the following multiple regression model:
(2) salesi = 0 + 1adv i + 2 priceHi + 3 priceAi + 4 priceBi + ui
where the additional variables used in the regression are: priceHi is the price per can of
the home
brand
tuna
in
week
i ; and
priceAi
and
priceBi
are
the
prices
per
can
of
the
two
major competing brands of tuna in week i . Regression model (2) was estimated by
ordinary least squares and a portion of the resultant EXCEL output is reproduced below
in Table 3.
Table
2:
EXCEL
output
for
the
simple
linear
regression
of
tuna
sales
on
advertising
Regression Statistics
R Square 0.217
Standard Error 6.178
Observations
52
Coefficients
Standard
Error t Stat P‐value
Intercept 2.68 1.38 1.94 0.058
adv 6.56 1.76 3.73 0.000
8/8/2019 2013 S1 Final Exam
5/13
5
Table
3:
EXCEL
output
for
multiple
linear
regression
model
of
tuna
sales
Regression Statistics
R Square 0.523
Standard Error 4.977
Observations
52
Coefficients Standard Error t Stat P‐value
Intercept 18.83 9.29 2.03 0.048
adv 4.16 1.49 2.80 0.007
priceH ‐20.48 3.88 ‐5.28 0.000
priceA 3.86 3.28 1.18 0.246
priceB 7.02 4.40 1.60 0.117
(i) How would you interpret the regression parameters 0 and 1 in regression
model (1)?
[2
marks]
(ii) How would you interpret the regression estimate for 0 provided in Table 2?
Explain the meaning of “P‐value” in the output and interpret the calculated “P‐
value” reported for the intercept. [3 marks]
(iii) How would you interpret the regression estimate for 1 provided in Table 2? Test
the null hypothesis that 1=0 against the alternative that 1 > 0 making clear any
assumptions you need to make. Explain how the estimate of 1 and the resultant
test you performed supports the argument to increase advertising that was
made by the Advertising Manager. [5 marks]
(iv) Why do you think the General Manager was reluctant to make a decision on the
advertising based
on
the
results
for
regression
model
(1)
and
hence
requested
an
extended analysis of the relationship between sales and advertising (equation
(2)) that was subsequently reported in Table 3? [2 marks]
(v) Consider the results reported in Table 3. One of the following interpretations of
these results is correct. Which is it? Explain what is wrong with each of the other
interpretations. [4 marks]
a. Changing the price of brand A has no affect on the average weekly sales
of home brand tuna.
b. Every $1 increase in the price of home brand tuna is associated with a
decrease of $20,480 in average weekly sales of home brand tuna, all
other
independent
variables
being
equal.
c. Increasing the price of brand B tuna by $1 increases the weekly sales of
home brand tuna by $7,020.
(vi) What are the “Standard Error” and “R Square” statistics reported amongst the
“Regression Statistics” in the EXCEL output in Table 3? Does the R Square result
for regression model (2) mean that the model fits 52.3% of data points exactly?
Explain. [4 marks]
8/8/2019 2013 S1 Final Exam
6/13
6
(vii) Use model (2) to predict the sales in two weeks. In the first week assume priceH
=1.0, priceA= priceB=1.2 and adv =0. In the prediction for the second week keep
all the same values except set priceH=1.5. [2 marks]
(viii) Using the predictions calculated in (vii) sketch the demand curve for home brand
tuna (i.e. the relationship between sales and priceH assuming priceA= priceB=1.2
and
adv =0). Now
draw
a second
demand
curve
on
the
same
graph
but
where
adv =1 and interpret the two curves. [2 marks]
8/8/2019 2013 S1 Final Exam
7/13
7
USEFUL FORMULAE
Sample Mean:
n
i
iXn
X1
1
Sample Variance: 2
1
2 )(1
1XX
ns
n
i
i
Population Variance:2
1
2 )(1
N
i
iXN
Population Mean:
N
i
iXN 1
1
Additive Law of Probability: P A B P A P B P A B( ) ( ) ( ) ( ) or
P( A or B) = P( A) + P(B) – P( A and B)
Multiplicative Law of Probability: P A B P A B P B P B A P A( ) ( ) ( ) ( ) ( )
orP( A and B) = P( A|B) P(B) = P(B| A)P( A)
Binomial Distribution:xnx
xn qpCxXP )( ; E(X) = np; Var(X) = npq
Standardising transformations:
)(
XZ ,
n
XZ
/
)(
,
ns
Xt
/
)( ,
2
22 1
sn
Confidence intervals for :
n
zX
n
zX
22
, known
n
stX
n
stX
nn 1,2
1,2
, unknown
Confidence interval for p:n
qpzpp
n
qpzp
ˆˆˆ
ˆˆˆ
22 , where pq ˆ1ˆ
Confidence interval for σ2:
2
1,2/1
22
2
1,2/
2 )1()1(
nn
snsn
Goodness of Fit Test:
K
i i
ii
e
eo
1
22 )( , df = K-1
Independence Test:
K
i
H
j ij
ijij
e
eo
1 1
2
2)(
, df = (K-1)(H-1)
8/8/2019 2013 S1 Final Exam
8/13
8
Sample Correlation Coefficient:
22 )()(
))((
YYXX
YYXX
ss
sr
ii
ii
YX
XY
Least Squares Estimators of 1 and 0 in the equation: iii eXY 10
XY
XX
YYXX
s
s
i
ii
X
XY10221
ˆˆ;ˆ
:
R 1
1
∑
∑
Forecast Intervals:
2
2
,2
)(1
XX
XX
nstY
i
p
ep for E(YpXp)
22
,2
)(11
XX
XX
nstY
i
p
ep for Yp
where 2 n and)2(
1
2
n
e
s
n
i
i
e is the estimated standard error of the
regression.
Distribution of 0ˆ and 1
ˆ :
0ˆ
2
22
0)(
,XX
X
nN
i
ie and 1ˆ
22
1)(
,XX
Ni
e .
8/8/2019 2013 S1 Final Exam
9/13
9
Table 1:Binomial Probability: P(X = k)
pn k 0.05 0.10 0.15 0.20 0.25 0.30 0.35 0. 40 0.45 0.50 0.55 0.60 0.65 0.70 0.75 0.80 0.85 0.90 0.95
2 0 0. 9025 0. 8100 0. 7225 0. 6400 0. 5625 0. 4900 0. 4225 0. 3600 0. 3025 0. 2500 0. 2025 0. 1600 0. 1225 0. 0900 0. 0625 0. 0400 0. 0225 0. 0100 0. 0025
1 0. 0950 0. 1800 0. 2550 0. 3200 0. 3750 0. 4200 0. 4550 0. 4800 0. 4950 0. 5000 0. 4950 0. 4800 0. 4550 0. 4200 0. 3750 0. 3200 0. 2550 0. 1800 0. 0950
2 0. 0025 0. 0100 0. 0225 0. 0400 0. 0625 0. 0900 0. 1225 0. 1600 0. 2025 0. 2500 0. 3025 0. 3600 0. 4225 0. 4900 0. 5625 0. 6400 0. 7225 0. 8100 0. 9025
3 0 0. 8574 0. 7290 0. 6141 0. 5120 0. 4219 0. 3430 0. 2746 0. 2160 0. 1664 0. 1250 0. 0911 0. 0640 0. 0429 0. 0270 0. 0156 0. 0080 0. 0034 0. 0010 0. 0001
1 0. 1354 0. 2430 0. 3251 0. 3840 0. 4219 0. 4410 0. 4436 0. 4320 0. 4084 0. 3750 0. 3341 0. 2880 0. 2389 0. 1890 0. 1406 0. 0960 0. 0574 0. 0270 0. 0071
2 0. 0071 0. 0270 0. 0574 0. 0960 0. 1406 0. 1890 0. 2389 0. 2880 0. 3341 0. 3750 0. 4084 0. 4320 0. 4436 0. 4410 0. 4219 0. 3840 0. 3251 0. 2430 0. 1354
3 0. 0001 0. 0010 0. 0034 0. 0080 0. 0156 0. 0270 0. 0429 0. 0640 0. 0911 0. 1250 0. 1664 0. 2160 0. 2746 0. 3430 0. 4219 0. 5120 0. 6141 0. 7290 0. 8574
4 0 0. 8145 0. 6561 0. 5220 0. 4096 0. 3164 0. 2401 0. 1785 0. 1296 0. 0915 0. 0625 0. 0410 0. 0256 0. 0150 0. 0081 0. 0039 0. 0016 0. 0005 0. 0001 0. 0000
1 0. 1715 0. 2916 0. 3685 0. 4096 0. 4219 0. 4116 0. 3845 0. 3456 0. 2995 0. 2500 0. 2005 0. 1536 0. 1115 0. 0756 0. 0469 0. 0256 0. 0115 0. 0036 0. 0005
2 0. 0135 0. 0486 0. 0975 0. 1536 0. 2109 0. 2646 0. 3105 0. 3456 0. 3675 0. 3750 0. 3675 0. 3456 0. 3105 0. 2646 0. 2109 0. 1536 0. 0975 0. 0486 0. 0135
3 0. 0005 0. 0036 0. 0115 0. 0256 0. 0469 0. 0756 0. 1115 0. 1536 0. 2005 0. 2500 0. 2995 0. 3456 0. 3845 0. 4116 0. 4219 0. 4096 0. 3685 0. 2916 0. 1715
4 0. 0000 0. 0001 0. 0005 0. 0016 0. 0039 0. 0081 0. 0150 0. 0256 0. 0410 0. 0625 0. 0915 0. 1296 0. 1785 0. 2401 0. 3164 0. 4096 0. 5220 0. 6561 0. 8145
5 0 0. 7738 0. 5905 0. 4437 0. 3277 0. 2373 0. 1681 0. 1160 0. 0778 0. 0503 0. 0313 0. 0185 0. 0102 0. 0053 0. 0024 0. 0010 0. 0003 0. 0001 0. 0000 0. 0000
1 0. 2036 0. 3281 0. 3915 0. 4096 0. 3955 0. 3602 0. 3124 0. 2592 0. 2059 0. 1563 0. 1128 0. 0768 0. 0488 0. 0284 0. 0146 0. 0064 0. 0022 0. 0004 0. 0000
2 0. 0214 0. 0729 0. 1382 0. 2048 0. 2637 0. 3087 0. 3364 0. 3456 0. 3369 0. 3125 0. 2757 0. 2304 0. 1811 0. 1323 0. 0879 0. 0512 0. 0244 0. 0081 0. 0011
3 0. 0011 0. 0081 0. 0244 0. 0512 0. 0879 0. 1323 0. 1811 0. 2304 0. 2757 0. 3125 0. 3369 0. 3456 0. 3364 0. 3087 0. 2637 0. 2048 0. 1382 0. 0729 0. 0214
4 0. 0000 0. 0005 0. 0022 0. 0064 0. 0146 0. 0284 0. 0488 0. 0768 0. 1128 0. 1563 0. 2059 0. 2592 0. 3124 0. 3602 0. 3955 0. 4096 0. 3915 0. 3281 0. 2036
5 0. 0000 0. 0000 0. 0001 0. 0003 0. 0010 0. 0024 0. 0053 0. 0102 0. 0185 0. 0313 0. 0503 0. 0778 0. 1160 0. 1681 0. 2373 0. 3277 0. 4437 0. 5905 0. 7738
6 0 0. 7351 0. 5314 0. 3771 0. 2621 0. 1780 0. 1176 0. 0754 0. 0467 0. 0277 0. 0156 0. 0083 0. 0041 0. 0018 0. 0007 0. 0002 0. 0001 0. 0000 0. 0000 0. 0000
1 0. 2321 0. 3543 0. 3993 0. 3932 0. 3560 0. 3025 0. 2437 0. 1866 0. 1359 0. 0938 0. 0609 0. 0369 0. 0205 0. 0102 0. 0044 0. 0015 0. 0004 0. 0001 0. 0000
2 0. 0305 0. 0984 0. 1762 0. 2458 0. 2966 0. 3241 0. 3280 0. 3110 0. 2780 0. 2344 0. 1861 0. 1382 0. 0951 0. 0595 0. 0330 0. 0154 0. 0055 0. 0012 0. 0001
3 0. 0021 0. 0146 0. 0415 0. 0819 0. 1318 0. 1852 0. 2355 0. 2765 0. 3032 0. 3125 0. 3032 0. 2765 0. 2355 0. 1852 0. 1318 0. 0819 0. 0415 0. 0146 0. 0021
4 0. 0001 0. 0012 0. 0055 0. 0154 0. 0330 0. 0595 0. 0951 0. 1382 0. 1861 0. 2344 0. 2780 0. 3110 0. 3280 0. 3241 0. 2966 0. 2458 0. 1762 0. 0984 0. 0305
5 0. 0000 0. 0001 0. 0004 0. 0015 0. 0044 0. 0102 0. 0205 0. 0369 0. 0609 0. 0937 0. 1359 0. 1866 0. 2437 0. 3025 0. 3560 0. 3932 0. 3993 0. 3543 0. 2321
6 0. 0000 0. 0000 0. 0000 0. 0001 0. 0002 0. 0007 0. 0018 0. 0041 0. 0083 0. 0156 0. 0277 0. 0467 0. 0754 0. 1176 0. 1780 0. 2621 0. 3771 0. 5314 0. 7351
7 0 0. 6983 0. 4783 0. 3206 0. 2097 0. 1335 0. 0824 0. 0490 0. 0280 0. 0152 0. 0078 0. 0037 0. 0016 0. 0006 0. 0002 0. 0001 0. 0000 0. 0000 0. 0000 0. 0000
1 0. 2573 0. 3720 0. 3960 0. 3670 0. 3115 0. 2471 0. 1848 0. 1306 0. 0872 0. 0547 0. 0320 0. 0172 0. 0084 0. 0036 0. 0013 0. 0004 0. 0001 0. 0000 0. 0000
2 0. 0406 0. 1240 0. 2097 0. 2753 0. 3115 0. 3177 0. 2985 0. 2613 0. 2140 0. 1641 0. 1172 0. 0774 0. 0466 0. 0250 0. 0115 0. 0043 0. 0012 0. 0002 0. 0000
3 0. 0036 0. 0230 0. 0617 0. 1147 0. 1730 0. 2269 0. 2679 0. 2903 0. 2918 0. 2734 0. 2388 0. 1935 0. 1442 0. 0972 0. 0577 0. 0287 0. 0109 0. 0026 0. 0002
4 0. 0002 0. 0026 0. 0109 0. 0287 0. 0577 0. 0972 0. 1442 0. 1935 0. 2388 0. 2734 0. 2918 0. 2903 0. 2679 0. 2269 0. 1730 0. 1147 0. 0617 0. 0230 0. 0036
5 0. 0000 0. 0002 0. 0012 0. 0043 0. 0115 0. 0250 0. 0466 0. 0774 0. 1172 0. 1641 0. 2140 0. 2613 0. 2985 0. 3177 0. 3115 0. 2753 0. 2097 0. 1240 0. 0406
6 0. 0000 0. 0000 0. 0001 0. 0004 0. 0013 0. 0036 0. 0084 0. 0172 0. 0320 0. 0547 0. 0872 0. 1306 0. 1848 0. 2471 0. 3115 0. 3670 0. 3960 0. 3720 0. 2573
7 0. 0000 0. 0000 0. 0000 0. 0000 0. 0001 0. 0002 0. 0006 0. 0016 0. 0037 0. 0078 0. 0152 0. 0280 0. 0490 0. 0824 0. 1335 0. 2097 0. 3206 0. 4783 0. 6983
8 0 0. 6634 0. 4305 0. 2725 0. 1678 0. 1001 0. 0576 0. 0319 0. 0168 0. 0084 0. 0039 0. 0017 0. 0007 0. 0002 0. 0001 0. 0000 0. 0000 0. 0000 0. 0000 0. 0000
1 0. 2793 0. 3826 0. 3847 0. 3355 0. 2670 0. 1977 0. 1373 0. 0896 0. 0548 0. 0313 0. 0164 0. 0079 0. 0033 0. 0012 0. 0004 0. 0001 0. 0000 0. 0000 0. 0000
2 0. 0515 0. 1488 0. 2376 0. 2936 0. 3115 0. 2965 0. 2587 0. 2090 0. 1569 0. 1094 0. 0703 0. 0413 0. 0217 0. 0100 0. 0038 0. 0011 0. 0002 0. 0000 0. 0000
3 0. 0054 0. 0331 0. 0839 0. 1468 0. 2076 0. 2541 0. 2786 0. 2787 0. 2568 0. 2188 0. 1719 0. 1239 0. 0808 0. 0467 0. 0231 0. 0092 0. 0026 0. 0004 0. 0000
4 0. 0004 0. 0046 0. 0185 0. 0459 0. 0865 0. 1361 0. 1875 0. 2322 0. 2627 0. 2734 0. 2627 0. 2322 0. 1875 0. 1361 0. 0865 0. 0459 0. 0185 0. 0046 0. 0004
5 0. 0000 0. 0004 0. 0026 0. 0092 0. 0231 0. 0467 0. 0808 0. 1239 0. 1719 0. 2188 0. 2568 0. 2787 0. 2786 0. 2541 0. 2076 0. 1468 0. 0839 0. 0331 0. 0054
6 0. 0000 0. 0000 0. 0002 0. 0011 0. 0038 0. 0100 0. 0217 0. 0413 0. 0703 0. 1094 0. 1569 0. 2090 0. 2587 0. 2965 0. 3115 0. 2936 0. 2376 0. 1488 0. 0515
7 0. 0000 0. 0000 0. 0000 0. 0001 0. 0004 0. 0012 0. 0033 0. 0079 0. 0164 0. 0313 0. 0548 0. 0896 0. 1373 0. 1977 0. 2670 0. 3355 0. 3847 0. 3826 0. 2793
8 0. 0000 0. 0000 0. 0000 0. 0000 0. 0000 0. 0001 0. 0002 0. 0007 0. 0017 0. 0039 0. 0084 0. 0168 0. 0319 0. 0576 0. 1001 0. 1678 0. 2725 0. 4305 0. 6634
9 0 0. 6302 0. 3874 0. 2316 0. 1342 0. 0751 0. 0404 0. 0207 0. 0101 0. 0046 0. 0020 0. 0008 0. 0003 0. 0001 0. 0000 0. 0000 0. 0000 0. 0000 0. 0000 0. 0000
1 0. 2985 0. 3874 0. 3679 0. 3020 0. 2253 0. 1556 0. 1004 0. 0605 0. 0339 0. 0176 0. 0083 0. 0035 0. 0013 0. 0004 0. 0001 0. 0000 0. 0000 0. 0000 0. 0000
2 0. 0629 0. 1722 0. 2597 0. 3020 0. 3003 0. 2668 0. 2162 0. 1612 0. 1110 0. 0703 0. 0407 0. 0212 0. 0098 0. 0039 0. 0012 0. 0003 0. 0000 0. 0000 0. 0000
3 0. 0077 0. 0446 0. 1069 0. 1762 0. 2336 0. 2668 0. 2716 0. 2508 0. 2119 0. 1641 0. 1160 0. 0743 0. 0424 0. 0210 0. 0087 0. 0028 0. 0006 0. 0001 0. 0000
4 0. 0006 0. 0074 0. 0283 0. 0661 0. 1168 0. 1715 0. 2194 0. 2508 0. 2600 0. 2461 0. 2128 0. 1672 0. 1181 0. 0735 0. 0389 0. 0165 0. 0050 0. 0008 0. 0000
5 0. 0000 0. 0008 0. 0050 0. 0165 0. 0389 0. 0735 0. 1181 0. 1672 0. 2128 0. 2461 0. 2600 0. 2508 0. 2194 0. 1715 0. 1168 0. 0661 0. 0283 0. 0074 0. 0006
6 0. 0000 0. 0001 0. 0006 0. 0028 0. 0087 0. 0210 0. 0424 0. 0743 0. 1160 0. 1641 0. 2119 0. 2508 0. 2716 0. 2668 0. 2336 0. 1762 0. 1069 0. 0446 0. 0077
7 0. 0000 0. 0000 0. 0000 0. 0003 0. 0012 0. 0039 0. 0098 0. 0212 0. 0407 0. 0703 0. 1110 0. 1612 0. 2162 0. 2668 0. 3003 0. 3020 0. 2597 0. 1722 0. 0629
8 0. 0000 0. 0000 0. 0000 0. 0000 0. 0001 0. 0004 0. 0013 0. 0035 0. 0083 0. 0176 0. 0339 0. 0605 0. 1004 0. 1556 0. 2253 0. 3020 0. 3679 0. 3874 0. 2985
9 0. 0000 0. 0000 0. 0000 0. 0000 0. 0000 0. 0000 0. 0001 0. 0003 0. 0008 0. 0020 0. 0046 0. 0101 0. 0207 0. 0404 0. 0751 0. 1342 0. 2316 0. 3874 0. 6302
10 0 0. 5987 0. 3487 0. 1969 0. 1074 0. 0563 0. 0282 0. 0135 0. 0060 0. 0025 0. 0010 0. 0003 0. 0001 0. 0000 0. 0000 0. 0000 0. 0000 0. 0000 0. 0000 0. 0000
1 0. 3151 0. 3874 0. 3474 0. 2684 0. 1877 0. 1211 0. 0725 0. 0403 0. 0207 0. 0098 0. 0042 0. 0016 0. 0005 0. 0001 0. 0000 0. 0000 0. 0000 0. 0000 0. 0000
2 0. 0746 0. 1937 0. 2759 0. 3020 0. 2816 0. 2335 0. 1757 0. 1209 0. 0763 0. 0439 0. 0229 0. 0106 0. 0043 0. 0014 0. 0004 0. 0001 0. 0000 0. 0000 0. 0000
3 0. 0105 0. 0574 0. 1298 0. 2013 0. 2503 0. 2668 0. 2522 0. 2150 0. 1665 0. 1172 0. 0746 0. 0425 0. 0212 0. 0090 0. 0031 0. 0008 0. 0001 0. 0000 0. 0000
4 0. 0010 0. 0112 0. 0401 0. 0881 0. 1460 0. 2001 0. 2377 0. 2508 0. 2384 0. 2051 0. 1596 0. 1115 0. 0689 0. 0368 0. 0162 0. 0055 0. 0012 0. 0001 0. 0000
5 0. 0001 0. 0015 0. 0085 0. 0264 0. 0584 0. 1029 0. 1536 0. 2007 0. 2340 0. 2461 0. 2340 0. 2007 0. 1536 0. 1029 0. 0584 0. 0264 0. 0085 0. 0015 0. 0001
6 0. 0000 0. 0001 0. 0012 0. 0055 0. 0162 0. 0368 0. 0689 0. 1115 0. 1596 0. 2051 0. 2384 0. 2508 0. 2377 0. 2001 0. 1460 0. 0881 0. 0401 0. 0112 0. 0010
7 0. 0000 0. 0000 0. 0001 0. 0008 0. 0031 0. 0090 0. 0212 0. 0425 0. 0746 0. 1172 0. 1665 0. 2150 0. 2522 0. 2668 0. 2503 0. 2013 0. 1298 0. 0574 0. 0105
8 0. 0000 0. 0000 0. 0000 0. 0001 0. 0004 0. 0014 0. 0043 0. 0106 0. 0229 0. 0439 0. 0763 0. 1209 0. 1757 0. 2335 0. 2816 0. 3020 0. 2759 0. 1937 0. 0746
9 0. 0000 0. 0000 0. 0000 0. 0000 0. 0000 0. 0001 0. 0005 0. 0016 0. 0042 0. 0098 0. 0207 0. 0403 0. 0725 0. 1211 0. 1877 0. 2684 0. 3474 0. 3874 0. 3151
10 0. 0000 0. 0000 0. 0000 0. 0000 0. 0000 0. 0000 0. 0000 0. 0001 0. 0003 0. 0010 0. 0025 0. 0060 0. 0135 0. 0282 0. 0563 0. 1074 0. 1969 0. 3487 0. 5987
8/8/2019 2013 S1 Final Exam
10/13
10
Table 2:Binomial Probability: P(X ≤ k)
pn k 0.05 0.10 0.15 0.20 0.25 0.30 0.35 0.40 0.45 0.50 0.55 0.60 0.65 0.70 0.75 0.80 0.85 0.90 0.95
2 0 0. 9025 0. 8100 0. 7225 0. 6400 0. 5625 0. 4900 0. 4225 0. 3600 0. 3025 0. 2500 0. 2025 0. 1600 0. 1225 0. 0900 0. 0625 0. 0400 0. 0225 0. 0100 0. 0025
1 0. 9975 0. 9900 0. 9775 0. 9600 0. 9375 0. 9100 0. 8775 0. 8400 0. 7975 0. 7500 0. 6975 0. 6400 0. 5775 0. 5100 0. 4375 0. 3600 0. 2775 0. 1900 0. 0975
3 0 0. 8574 0. 7290 0. 6141 0. 5120 0. 4219 0. 3430 0. 2746 0. 2160 0. 1664 0. 1250 0. 0911 0. 0640 0. 0429 0. 0270 0. 0156 0. 0080 0. 0034 0. 0010 0. 0001
1 0. 9928 0. 9720 0. 9393 0. 8960 0. 8438 0. 7840 0. 7183 0. 6480 0. 5748 0. 5000 0. 4253 0. 3520 0. 2818 0. 2160 0. 1563 0. 1040 0. 0607 0. 0280 0. 0072
2 0. 9999 0. 9990 0. 9966 0. 9920 0. 9844 0. 9730 0. 9571 0. 9360 0. 9089 0. 8750 0. 8336 0. 7840 0. 7254 0. 6570 0. 5781 0. 4880 0. 3859 0. 2710 0. 1426
4 0 0. 8145 0. 6561 0. 5220 0. 4096 0. 3164 0. 2401 0. 1785 0. 1296 0. 0915 0. 0625 0. 0410 0. 0256 0. 0150 0. 0081 0. 0039 0. 0016 0. 0005 0. 0001 0. 0000
1 0. 9860 0. 9477 0. 8905 0. 8192 0. 7383 0. 6517 0. 5630 0. 4752 0. 3910 0. 3125 0. 2415 0. 1792 0. 1265 0. 0837 0. 0508 0. 0272 0. 0120 0. 0037 0. 0005
2 0. 9995 0. 9963 0. 9880 0. 9728 0. 9492 0. 9163 0. 8735 0. 8208 0. 7585 0. 6875 0. 6090 0. 5248 0. 4370 0. 3483 0. 2617 0. 1808 0. 1095 0. 0523 0. 0140
3 1. 0000 0. 9999 0. 9995 0. 9984 0. 9961 0. 9919 0. 9850 0. 9744 0. 9590 0. 9375 0. 9085 0. 8704 0. 8215 0. 7599 0. 6836 0. 5904 0. 4780 0. 3439 0. 1855
5 0 0. 7738 0. 5905 0. 4437 0. 3277 0. 2373 0. 1681 0. 1160 0. 0778 0. 0503 0. 0313 0. 0185 0. 0102 0. 0053 0. 0024 0. 0010 0. 0003 0. 0001 0. 0000 0. 0000
1 0. 9774 0. 9185 0. 8352 0. 7373 0. 6328 0. 5282 0. 4284 0. 3370 0. 2562 0. 1875 0. 1312 0. 0870 0. 0540 0. 0308 0. 0156 0. 0067 0. 0022 0. 0005 0. 0000
2 0. 9988 0. 9914 0. 9734 0. 9421 0. 8965 0. 8369 0. 7648 0. 6826 0. 5931 0. 5000 0. 4069 0. 3174 0. 2352 0. 1631 0. 1035 0. 0579 0. 0266 0. 0086 0. 0012
3 1. 0000 0. 9995 0. 9978 0. 9933 0. 9844 0. 9692 0. 9460 0. 9130 0. 8688 0. 8125 0. 7438 0. 6630 0. 5716 0. 4718 0. 3672 0. 2627 0. 1648 0. 0815 0. 0226
4 1. 0000 1. 0000 0. 9999 0. 9997 0. 9990 0. 9976 0. 9947 0. 9898 0. 9815 0. 9688 0. 9497 0. 9222 0. 8840 0. 8319 0. 7627 0. 6723 0. 5563 0. 4095 0. 2262
6 0 0. 7351 0. 5314 0. 3771 0. 2621 0. 1780 0. 1176 0. 0754 0. 0467 0. 0277 0. 0156 0. 0083 0. 0041 0. 0018 0. 0007 0. 0002 0. 0001 0. 0000 0. 0000 0. 0000
1 0. 9672 0. 8857 0. 7765 0. 6554 0. 5339 0. 4202 0. 3191 0. 2333 0. 1636 0. 1094 0. 0692 0. 0410 0. 0223 0. 0109 0. 0046 0. 0016 0. 0004 0. 0001 0. 0000
2 0. 9978 0. 9842 0. 9527 0. 9011 0. 8306 0. 7443 0. 6471 0. 5443 0. 4415 0. 3438 0. 2553 0. 1792 0. 1174 0. 0705 0. 0376 0. 0170 0. 0059 0. 0013 0. 0001
3 0. 9999 0. 9987 0. 9941 0. 9830 0. 9624 0. 9295 0. 8826 0. 8208 0. 7447 0. 6563 0. 5585 0. 4557 0. 3529 0. 2557 0. 1694 0. 0989 0. 0473 0. 0158 0. 0022
4 1. 0000 0. 9999 0. 9996 0. 9984 0. 9954 0. 9891 0. 9777 0. 9590 0. 9308 0. 8906 0. 8364 0. 7667 0. 6809 0. 5798 0. 4661 0. 3446 0. 2235 0. 1143 0. 0328
5 1. 0000 1. 0000 1. 0000 0. 9999 0. 9998 0. 9993 0. 9982 0. 9959 0. 9917 0. 9844 0. 9723 0. 9533 0. 9246 0. 8824 0. 8220 0. 7379 0. 6229 0. 4686 0. 2649
7 0 0. 6983 0. 4783 0. 3206 0. 2097 0. 1335 0. 0824 0. 0490 0. 0280 0. 0152 0. 0078 0. 0037 0. 0016 0. 0006 0. 0002 0. 0001 0. 0000 0. 0000 0. 0000 0. 0000
1 0. 9556 0. 8503 0. 7166 0. 5767 0. 4449 0. 3294 0. 2338 0. 1586 0. 1024 0. 0625 0. 0357 0. 0188 0. 0090 0. 0038 0. 0013 0. 0004 0. 0001 0. 0000 0. 0000
2 0. 9962 0. 9743 0. 9262 0. 8520 0. 7564 0. 6471 0. 5323 0. 4199 0. 3164 0. 2266 0. 1529 0. 0963 0. 0556 0. 0288 0. 0129 0. 0047 0. 0012 0. 0002 0. 0000
3 0. 9998 0. 9973 0. 9879 0. 9667 0. 9294 0. 8740 0. 8002 0. 7102 0. 6083 0. 5000 0. 3917 0. 2898 0. 1998 0. 1260 0. 0706 0. 0333 0. 0121 0. 0027 0. 0002
4 1. 0000 0. 9998 0. 9988 0. 9953 0. 9871 0. 9712 0. 9444 0. 9037 0. 8471 0. 7734 0. 6836 0. 5801 0. 4677 0. 3529 0. 2436 0. 1480 0. 0738 0. 0257 0. 0038
5 1. 0000 1. 0000 0. 9999 0. 9996 0. 9987 0. 9962 0. 9910 0. 9812 0. 9643 0. 9375 0. 8976 0. 8414 0. 7662 0. 6706 0. 5551 0. 4233 0. 2834 0. 1497 0. 0444
6 1. 0000 1. 0000 1. 0000 1. 0000 0. 9999 0. 9998 0. 9994 0. 9984 0. 9963 0. 9922 0. 9848 0. 9720 0. 9510 0. 9176 0. 8665 0. 7903 0. 6794 0. 5217 0. 3017
8 0 0. 6634 0. 4305 0. 2725 0. 1678 0. 1001 0. 0576 0. 0319 0. 0168 0. 0084 0. 0039 0. 0017 0. 0007 0. 0002 0. 0001 0. 0000 0. 0000 0. 0000 0. 0000 0. 0000
1 0. 9428 0. 8131 0. 6572 0. 5033 0. 3671 0. 2553 0. 1691 0. 1064 0. 0632 0. 0352 0. 0181 0. 0085 0. 0036 0. 0013 0. 0004 0. 0001 0. 0000 0. 0000 0. 0000
2 0. 9942 0. 9619 0. 8948 0. 7969 0. 6785 0. 5518 0. 4278 0. 3154 0. 2201 0. 1445 0. 0885 0. 0498 0. 0253 0. 0113 0. 0042 0. 0012 0. 0002 0. 0000 0. 0000
3 0. 9996 0. 9950 0. 9786 0. 9437 0. 8862 0. 8059 0. 7064 0. 5941 0. 4770 0. 3633 0. 2604 0. 1737 0. 1061 0. 0580 0. 0273 0. 0104 0. 0029 0. 0004 0. 0000
4 1. 0000 0. 9996 0. 9971 0. 9896 0. 9727 0. 9420 0. 8939 0. 8263 0. 7396 0. 6367 0. 5230 0. 4059 0. 2936 0. 1941 0. 1138 0. 0563 0. 0214 0. 0050 0. 0004
5 1. 0000 1. 0000 0. 9998 0. 9988 0. 9958 0. 9887 0. 9747 0. 9502 0. 9115 0. 8555 0. 7799 0. 6846 0. 5722 0. 4482 0. 3215 0. 2031 0. 1052 0. 0381 0. 0058
6 1. 0000 1. 0000 1. 0000 0. 9999 0. 9996 0. 9987 0. 9964 0. 9915 0. 9819 0. 9648 0. 9368 0. 8936 0. 8309 0. 7447 0. 6329 0. 4967 0. 3428 0. 1869 0. 0572
7 1. 0000 1. 0000 1. 0000 1. 0000 1. 0000 0. 9999 0. 9998 0. 9993 0. 9983 0. 9961 0. 9916 0. 9832 0. 9681 0. 9424 0. 8999 0. 8322 0. 7275 0. 5695 0. 3366
9 0 0. 6302 0. 3874 0. 2316 0. 1342 0. 0751 0. 0404 0. 0207 0. 0101 0. 0046 0. 0020 0. 0008 0. 0003 0. 0001 0. 0000 0. 0000 0. 0000 0. 0000 0. 0000 0. 0000
1 0. 9288 0. 7748 0. 5995 0. 4362 0. 3003 0. 1960 0. 1211 0. 0705 0. 0385 0. 0195 0. 0091 0. 0038 0. 0014 0. 0004 0. 0001 0. 0000 0. 0000 0. 0000 0. 0000
2 0. 9916 0. 9470 0. 8591 0. 7382 0. 6007 0. 4628 0. 3373 0. 2318 0. 1495 0. 0898 0. 0498 0. 0250 0. 0112 0. 0043 0. 0013 0. 0003 0. 0000 0. 0000 0. 0000
3 0. 9994 0. 9917 0. 9661 0. 9144 0. 8343 0. 7297 0. 6089 0. 4826 0. 3614 0. 2539 0. 1658 0. 0994 0. 0536 0. 0253 0. 0100 0. 0031 0. 0006 0. 0001 0. 0000
4 1. 0000 0. 9991 0. 9944 0. 9804 0. 9511 0. 9012 0. 8283 0. 7334 0. 6214 0. 5000 0. 3786 0. 2666 0. 1717 0. 0988 0. 0489 0. 0196 0. 0056 0. 0009 0. 0000
5 1. 0000 0. 9999 0. 9994 0. 9969 0. 9900 0. 9747 0. 9464 0. 9006 0. 8342 0. 7461 0. 6386 0. 5174 0. 3911 0. 2703 0. 1657 0. 0856 0. 0339 0. 0083 0. 0006
6 1. 0000 1. 0000 1. 0000 0. 9997 0. 9987 0. 9957 0. 9888 0. 9750 0. 9502 0. 9102 0. 8505 0. 7682 0. 6627 0. 5372 0. 3993 0. 2618 0. 1409 0. 0530 0. 0084
7 1. 0000 1. 0000 1. 0000 1. 0000 0. 9999 0. 9996 0. 9986 0. 9962 0. 9909 0. 9805 0. 9615 0. 9295 0. 8789 0. 8040 0. 6997 0. 5638 0. 4005 0. 2252 0. 0712
8 1. 0000 1. 0000 1. 0000 1. 0000 1. 0000 1. 0000 0. 9999 0. 9997 0. 9992 0. 9980 0. 9954 0. 9899 0. 9793 0. 9596 0. 9249 0. 8658 0. 7684 0. 6126 0. 3698
10 0 0. 5987 0. 3487 0. 1969 0. 1074 0. 0563 0. 0282 0. 0135 0. 0060 0. 0025 0. 0010 0. 0003 0. 0001 0. 0000 0. 0000 0. 0000 0. 0000 0. 0000 0. 0000 0. 0000
1 0. 9139 0. 7361 0. 5443 0. 3758 0. 2440 0. 1493 0. 0860 0. 0464 0. 0233 0. 0107 0. 0045 0. 0017 0. 0005 0. 0001 0. 0000 0. 0000 0. 0000 0. 0000 0. 0000
2 0. 9885 0. 9298 0. 8202 0. 6778 0. 5256 0. 3828 0. 2616 0. 1673 0. 0996 0. 0547 0. 0274 0. 0123 0. 0048 0. 0016 0. 0004 0. 0001 0. 0000 0. 0000 0. 0000
3 0. 9990 0. 9872 0. 9500 0. 8791 0. 7759 0. 6496 0. 5138 0. 3823 0. 2660 0. 1719 0. 1020 0. 0548 0. 0260 0. 0106 0. 0035 0. 0009 0. 0001 0. 0000 0. 0000
4 0. 9999 0. 9984 0. 9901 0. 9672 0. 9219 0. 8497 0. 7515 0. 6331 0. 5044 0. 3770 0. 2616 0. 1662 0. 0949 0. 0473 0. 0197 0. 0064 0. 0014 0. 0001 0. 0000
5 1. 0000 0. 9999 0. 9986 0. 9936 0. 9803 0. 9527 0. 9051 0. 8338 0. 7384 0. 6230 0. 4956 0. 3669 0. 2485 0. 1503 0. 0781 0. 0328 0. 0099 0. 0016 0. 0001
6 1. 0000 1. 0000 0. 9999 0. 9991 0. 9965 0. 9894 0. 9740 0. 9452 0. 8980 0. 8281 0. 7340 0. 6177 0. 4862 0. 3504 0. 2241 0. 1209 0. 0500 0. 0128 0. 0010
7 1. 0000 1. 0000 1. 0000 0. 9999 0. 9996 0. 9984 0. 9952 0. 9877 0. 9726 0. 9453 0. 9004 0. 8327 0. 7384 0. 6172 0. 4744 0. 3222 0. 1798 0. 0702 0. 0115
8 1. 0000 1. 0000 1. 0000 1. 0000 1. 0000 0. 9999 0. 9995 0. 9983 0. 9955 0. 9893 0. 9767 0. 9536 0. 9140 0. 8507 0. 7560 0. 6242 0. 4557 0. 2639 0. 0861
9 1. 0000 1. 0000 1. 0000 1. 0000 1. 0000 1. 0000 1. 0000 0. 9999 0. 9997 0. 9990 0. 9975 0. 9940 0. 9865 0. 9718 0. 9437 0. 8926 0. 8031 0. 6513 0. 4013
8/8/2019 2013 S1 Final Exam
11/13
Table 3: Standard Normal Probabilities: P(0 ≤ Z ≤ z)
z 0 1 2 3 4 5 6 7 8 9
0.0 0.0000 0.0040 0.0080 0.0120 0.0160 0.0199 0.0239 0.0279 0.0319 0.0359
0.1 0.0398 0.0438 0.0478 0.0517 0.0557 0.0596 0.0636 0.0675 0.0714 0.0753
0.2 0.0793 0.0832 0.0871 0.0910 0.0948 0.0987 0.1026 0.1064 0.1103 0.1141
0.3 0.1179 0.1217 0.1255 0.1293 0.1331 0.1368 0.1406 0.1443 0.1480 0.1517
0.4 0.1554 0.1591 0.1628 0.1664 0.1700 0.1736 0.1772 0.1808 0.1844 0.1879
0.5 0.1915 0.1950 0.1985 0.2019 0.2054 0.2088 0.2123 0.2157 0.2190 0.2224
0.6 0.2257 0.2291 0.2324 0.2357 0.2389 0.2422 0.2454 0.2486 0.2517 0.2549
0.7 0.2580 0.2611 0.2642 0.2673 0.2704 0.2734 0.2764 0.2794 0.2823 0.2852
0.8 0.2881 0.2910 0.2939 0.2967 0.2995 0.3023 0.3051 0.3078 0.3106 0.3133
0.9 0.3159 0.3186 0.3212 0.3238 0.3264 0.3289 0.3315 0.3340 0.3365 0.3389
1.0 0.3413 0.3438 0.3461 0.3485 0.3508 0.3531 0.3554 0.3577 0.3599 0.3621
1.1 0.3643 0.3665 0.3686 0.3708 0.3729 0.3749 0.3770 0.3790 0.3810 0.3830
1.2 0.3849 0.3869 0.3888 0.3907 0.3925 0.3944 0.3962 0.3980 0.3997 0.4015
1.3 0.4032 0.4049 0.4066 0.4082 0.4099 0.4115 0.4131 0.4147 0.4162 0.4177
1.4 0.4192 0.4207 0.4222 0.4236 0.4251 0.4265 0.4279 0.4292 0.4306 0.4319
1.5 0.4332 0.4345 0.4357 0.4370 0.4382 0.4394 0.4406 0.4418 0.4429 0.4441
1.6 0.4452 0.4463 0.4474 0.4484 0.4495 0.4505 0.4515 0.4525 0.4535 0.4545
1.7 0.4554 0.4564 0.4573 0.4582 0.4591 0.4599 0.4608 0.4616 0.4625 0.4633
1.8 0.4641 0.4649 0.4656 0.4664 0.4671 0.4678 0.4686 0.4693 0.4699 0.4706
1.9 0.4713 0.4719 0.4726 0.4732 0.4738 0.4744 0.4750 0.4756 0.4761 0.4767
2.0 0.4772 0.4778 0.4783 0.4788 0.4793 0.4798 0.4803 0.4808 0.4812 0.4817
2.1 0.4821 0.4826 0.4830 0.4834 0.4838 0.4842 0.4846 0.4850 0.4854 0.4857
2.2 0.4861 0.4864 0.4868 0.4871 0.4875 0.4878 0.4881 0.4884 0.4887 0.4890
2.3 0.4893 0.4896 0.4898 0.4901 0.4904 0.4906 0.4909 0.4911 0.4913 0.4916
2.4 0.4918 0.4920 0.4922 0.4925 0.4927 0.4929 0.4931 0.4932 0.4934 0.4936
2.5 0.4938 0.4940 0.4941 0.4943 0.4945 0.4946 0.4948 0.4949 0.4951 0.4952
2.6 0.4953 0.4955 0.4956 0.4957 0.4959 0.4960 0.4961 0.4962 0.4963 0.4964
2.7 0.4965 0.4966 0.4967 0.4968 0.4969 0.4970 0.4971 0.4972 0.4973 0.4974
2.8 0.4974 0.4975 0.4976 0.4977 0.4977 0.4978 0.4979 0.4979 0.4980 0.4981
2.9 0.4981 0.4982 0.4982 0.4983 0.4984 0.4984 0.4985 0.4985 0.4986 0.4986
3.0 0.4987 0.4987 0.4987 0.4988 0.4988 0.4989 0.4989 0.4989 0.4990 0.4990
3.1 0.4990 0.4991 0.4991 0.4991 0.4992 0.4992 0.4992 0.4992 0.4993 0.4993
3.2 0.4993 0.4993 0.4994 0.4994 0.4994 0.4994 0.4994 0.4995 0.4995 0.4995
3.3 0.4995 0.4995 0.4995 0.4996 0.4996 0.4996 0.4996 0.4996 0.4996 0.4997
3.4 0.4997 0.4997 0.4997 0.4997 0.4997 0.4997 0.4997 0.4997 0.4997 0.4998
3.5 0.4998 0.4998 0.4998 0.4998 0.4998 0.4998 0.4998 0.4998 0.4998 0.4998
3.6 0.4998 0.4998 0.4999 0.4999 0.4999 0.4999 0.4999 0.4999 0.4999 0.4999
3.7 0.4999 0.4999 0.4999 0.4999 0.4999 0.4999 0.4999 0.4999 0.4999 0.4999
3.8 0.4999 0.4999 0.4999 0.4999 0.4999 0.4999 0.4999 0.4999 0.4999 0.4999
3.9 0.5000 0.5000 0.5000 0.5000 0.5000 0.5000 0.5000 0.5000 0.5000 0.5000
0 z
8/8/2019 2013 S1 Final Exam
12/13
12
Table 4: Upper-tail Critical Values of t -Distribution: t(α, ν)
α
ν 0.100 0.050 0.025 0.010 0.005
1 3.078 6.314 12.706 31.821 63.657
2 1.886 2.920 4.303 6.965 9.925
3 1.638 2.353 3.182 4.541 5.841
4 1.533 2.132 2.776 3.747 4.604
5 1.476 2.015 2.571 3.365 4.032
6 1.440 1.943 2.447 3.143 3.707
7 1.415 1.895 2.365 2.998 3.499
8 1.397 1.860 2.306 2.896 3.355
9 1.383 1.833 2.262 2.821 3.25010 1.372 1.812 2.228 2.764 3.169
11 1.363 1.796 2.201 2.718 3.106
12 1.356 1.782 2.179 2.681 3.055
13 1.350 1.771 2.160 2.650 3.012
14 1.345 1.761 2.145 2.624 2.977
15 1.341 1.753 2.131 2.602 2.947
16 1.337 1.746 2.120 2.583 2.921
17 1.333 1.740 2.110 2.567 2.898
18 1.330 1.734 2.101 2.552 2.878
19 1.328 1.729 2.093 2.539 2.861
20 1.325 1.725 2.086 2.528 2.845
21 1.323 1.721 2.080 2.518 2.83122 1.321 1.717 2.074 2.508 2.819
23 1.319 1.714 2.069 2.500 2.807
24 1.318 1.711 2.064 2.492 2.797
25 1.316 1.708 2.060 2.485 2.787
26 1.315 1.706 2.056 2.479 2.779
27 1.314 1.703 2.052 2.473 2.771
28 1.313 1.701 2.048 2.467 2.763
29 1.311 1.699 2.045 2.462 2.756
30 1.310 1.697 2.042 2.457 2.750
40 1.303 1.684 2.021 2.423 2.704
60 1.296 1.671 2.000 2.390 2.660
120 1.289 1.658 1.980 2.358 2.617
∞ 1.282 1.645 1.960 2.326 2.576
0 t
8/8/2019 2013 S1 Final Exam
13/13
13
Table 5: Upper-tail Chi-square Critical Values: χ 2(α, ν)
α ν 0.995 0.99 0.975 0.95 0.9 0.1 0.05 0.025 0.01 0.005
1 3.93E-05 0.0002 0.0010 0.0039 0.0158 2.7055 3.8415 5.0239 6.6349 7.8794
2 0.0100 0.0201 0.0506 0.1026 0.2107 4.6052 5.9915 7.3778 9.2103 10.5966
3 0.0717 0.1148 0.2158 0.3518 0.5844 6.2514 7.8147 9.3484 11.3449 12.8382
4 0.2070 0.2971 0.4844 0.7107 1.0636 7.7794 9.4877 11.1433 13.2767 14.8603
5 0.4117 0.5543 0.8312 1.1455 1.6103 9.2364 11.0705 12.8325 15.0863 16.7496
6 0.6757 0.8721 1.2373 1.6354 2.2041 10.6446 12.5916 14.4494 16.8119 18.5476
7 0.9893 1.2390 1.6899 2.1673 2.8331 12.0170 14.0671 16.0128 18.4753 20.2777
8 1.3444 1.6465 2.1797 2.7326 3.4895 13.3616 15.5073 17.5345 20.0902 21.9550
9 1.7349 2.0879 2.7004 3.3251 4.1682 14.6837 16.9190 19.0228 21.6660 23.5894
10 2.1559 2.5582 3.2470 3.9403 4.8652 15.9872 18.3070 20.4832 23.2093 25.1882
11 2.6032 3.0535 3.8157 4.5748 5.5778 17.2750 19.6751 21.9200 24.7250 26.7568
12 3.0738 3.5706 4.4038 5.2260 6.3038 18.5493 21.0261 23.3367 26.2170 28.2995
13 3.5650 4.1069 5.0088 5.8919 7.0415 19.8119 22.3620 24.7356 27.6882 29.8195
14 4.0747 4.6604 5.6287 6.5706 7.7895 21.0641 23.6848 26.1189 29.1412 31.3193
15 4.6009 5.2293 6.2621 7.2609 8.5468 22.3071 24.9958 27.4884 30.5779 32.8013
16 5.1422 5.8122 6.9077 7.9616 9.3122 23.5418 26.2962 28.8454 31.9999 34.2672
17 5.6972 6.4078 7.5642 8.6718 10.0852 24.7690 27.5871 30.1910 33.4087 35.7185
18 6.2648 7.0149 8.2307 9.3905 10.8649 25.9894 28.8693 31.5264 34.8053 37.1565
19 6.8440 7.6327 8.9065 10.1170 11.6509 27.2036 30.1435 32.8523 36.1909 38.5823
20 7.4338 8.2604 9.5908 10.8508 12.4426 28.4120 31.4104 34.1696 37.5662 39.9968
21 8.0337 8.8972 10.2829 11.5913 13.2396 29.6151 32.6706 35.4789 38.9322 41.4011
22 8.6427 9.5425 10.9823 12.3380 14.0415 30.8133 33.9244 36.7807 40.2894 42.7957
23 9.2604 10.1957 11.6886 13.0905 14.8480 32.0069 35.1725 38.0756 41.6384 44.1813
24 9.8862 10.8564 12.4012 13.8484 15.6587 33.1962 36.4150 39.3641 42.9798 45.5585
25 10.5197 11.5240 13.1197 14.6114 16.4734 34.3816 37.6525 40.6465 44.3141 46.9279
26 11.1602 12.1981 13.8439 15.3792 17.2919 35.5632 38.8851 41.9232 45.6417 48.2899
27 11.8076 12.8785 14.5734 16.1514 18.1139 36.7412 40.1133 43.1945 46.9629 49.6449
28 12.4613 13.5647 15.3079 16.9279 18.9392 37.9159 41.3371 44.4608 48.2782 50.9934
29 13.1211 14.2565 16.0471 17.7084 19.7677 39.0875 42.5570 45.7223 49.5879 52.3356
30 13.7867 14.9535 16.7908 18.4927 20.5992 40.2560 43.7730 46.9792 50.8922 53.6720
40 20.7065 22.1643 24.4330 26.5093 29.0505 51.8051 55.7585 59.3417 63.6907 66.7660
50 27.9907 29.7067 32.3574 34.7643 37.6886 63.1671 67.5048 71.4202 76.1539 79.4900
60 35.5345 37.4849 40.4817 43.1880 46.4589 74.3970 79.0819 83.2977 88.3794 91.9517
70 43.2752 45.4417 48.7576 51.7393 55.3289 85.5270 90.5312 95.0232 100.4252 104.2149
80 51.1719 53.5401 57.1532 60.3915 64.2778 96.5782 101.8795 106.6286 112.3288 116.3211
90 59.1963 61.7541 65.6466 69.1260 73.2911 107.5650 113.1453 118.1359 124.1163 128.2989
100 67.3276 70.0649 74.2219 77.9295 82.3581 118.4980 124.3421 129.5612 135.8067 140.1695
0 Chi2
Top Related