# ST306 - UNISWA Library - University of Swaziland

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```UNIVERSITY OF SWAZILAND FINAL EXAMINATION PAPER 2013 TITLE OF PAPER
SAMPLE SURVEY THEORY
COURSE CODE
ST306
TIME ALLOWED
TWO (2) HOURS
REQUIREMENTS
CALCULATOR AND STATISTICAL TABLES
INSTRUCTIONS
1
Question 1 [20 marks, 3+3+3+3+4+4]
(a) For each of the following surveys, describe the target population, sampling frame, sampling unit,
and observation unit. Discuss any possible sources of selection bias or inaccuracy of responses.
(i) A student wants to estimate the percentage of mutual funds whose shares went up in price
last week. She selects every tenth fund listing in the mutual fund pages of the newspaper and
calculates the percentage of those in which the share price increased.
•
(ii) A sample of 8 architects was chosen in a city with 14 architects and architectural firms. To
select a survey sample, each architect was contacted by telephone in order of appearance in
the telephone directory. The first 8 agreeing to be interviewed formed the sample.
(iii) To estimate how many hooks in the library need rebinding, a librarian uses a random number
table to randomly select 100 locations on library shelves. He then walks to each location, looks
at the book that resides at that spot, and records whether the book needs rebinding or not.
(iv) A survey is conducted to find the average weight of cows in a region. A list of all farms is
available for the region, and 50 farms are selected at random. Then the weight of each cow
at the 50 selected farms is recorded.
(b) Senturia et al. (1994) describe a survey taken to study how many children have access to guns in
their households. Questionnaires were distributed to all parents who attended selected clinics in the
Chicago area during a 1-week period for well or sick-child visits.
(i) Suppose the quantity of interest is percentage of the households with guns. Describe why this
is a cluster sample. What is the psu? The ssu? Is it a one-stage or two-stage cluster sample?
How would you estimate the percentage of households with guns and the standard error of
(ii) What is the sampling population for this study? Do you think this sampling procedure results
in a representative sample of households with children? Why, or why not?
Question 2 [20 marks, 10+5+5]
(a) Foresters want to estimate the average age of trees in a stand.
because one needs to count the tree rings on a core taken from
older the tree, the larger the diameter, and diameter is easy to
the diameter of all 1132 trees and find that the population mean
select 20 trees for age measurement.
Tree No.
1
2
3
4
5
6
7
8
9
10
Diameter, x Age, y Tree No.
12.0
11.4
7.9
9.0
10.5
7.9
7.3
10.2
11.7
11.3
125
119
83
85
99
117
69
133
154
168
2
11
12
13
14
15
16
17
18
19
20
Determining age is cumbersome
the tree. In general, though, the
measure. The foresters measure
equals 10.3. They then randomly
Diameter, x Age, y
5.7
8.0
10.3
12.0
9.2
8.5
7.0
10.7
9.3
8.2
61
80
114
147
122
106
82
88
97
99
Estimate the population mean age of trees in the stand and give an approximate standard error for
(b) An accounting firm is interested in estimating the error rate in a compliance audit it is conducting.
The population contains 828 claims, and the firm audits an SRS of 85 of those claims. In each of
the 85 sampled claims, 215 fields are checked for errors. One claim has errors in 4 of the 215 fields,
1 claim has three errors, 4 claims have two errors, 22 claims have one error, and the remaining 57
claims have no errors. (Data courtesy of Fritz Scheuren.)
(i) Treating the claims as psu's and the observations for each field as ssu's, estimate the error
rate for all 828 claims. Give a standard error for your estimate.
(ii) Estimate (with SE) the total number of errors in the 828 claims.
Question 3 [20 marks, 4+4+12]
(a) Mayr et al. (1994) took an SRS of 240 children aged 2 to 6 years who visited their pediatric
outpatient clinic. They found the following frequency distribution for free (unassisted) walking
among the children:
Age (months)
9 10 11 12 13 14 15 16 17 18 19 20
Number of children 13 35 44 69 36 24 7 3 2 5 1 1
(i) Find the mean, standard error, and a 95% CI for the average age for onset of free walking.
(ii) Suppose the researchers want to do another study in a different region and want a 95%
confidence interval for the mean age of onset of walking to have margin of error 0.5. Using
the estimated standard deviation for these data, what sample size would they need to take?
(b) The following data are from a stratified sample of faculty, using the areas biological sciences,
physical sciences, social sciences, and humanities as the strata. Proportional allocation was used in
this sample.
Stratum
Number
Number
of
Faculty of
Faculty
Members in Members in
Sample
Stratum
Biological sciences
Physical sciences
Social sciences
Humanities
Total
102
310
217
178
807
7
19
13
11
50
The frequency table for number of publications in the strata is given below.
3
Number of
Refereed Publications
o
1
2
3
4
5
6
7
8
Number of Faculty Members
Biological Physical Social Humanities
1
10
9
8
220
2
001
0
1
1
0
1
o
2
2
0
2
0
1
0
0
100
020
0
0
o
1
1
(i) Estimate the total number of refereed publications by faculty members in the college and give
the standard error.
(ii) Estimate the proportion of faculty with no refereed publications and give the standard error.
Question 4 [20 marks, 4+4+4+2+2+2+2]
(a) A letter in the December 1995 issue of Dell Champion Variety Puzzles stated: "I've noticed over
the last several issues there have been no winners from the South in your contests. You always say
that winners are picked at random, so does this mean you're getting fewer entries from the South?"
In response, the editors took a random sample of 1000 entries from the last few contests and found
that 175 of those came from the South.
(i) Find a 95% CI for the percentage of entries that come from the South.
(ii) According to Statistical Abstract of the United States, 30.9% of the U. S. population live in
states that the editors considered to be in the South. Is there evidence from your confidence
interval that the percentage of entries from the South differs from the percentage of persons
living in the South?
(b) A city council of a small city wants to know the proportion of eligible voters who oppose having
an incinerator built for burning Phoenix garbage, just outside city limits. They randomly select 100
residential numbers from the city's telephone book that contains 3000 such numbers. Each selected
residence is then called and asked for (a) the total number of eligible voters and (b) the number of
voters opposed to the incinerator. A total of 157 voters are surveyed; of these, 23 refuse to answer
the question. Of the remaining 134 voters, 112 oppose the incinerator, so the council estimates the
proportion by
p=
with 112 = 0.83582 134 V(P) = 0.83582(~~ 0.83582) = 0.00102. Are these estimates valid? Why. or why not? For each of the following situations, indicate how you
might use ratio or regression estimation.
(i) Estimate the proportion of time devoted to sports in television news broadcasts in your city.
(ii) Estimate the average number of fish caught per hour by anglers visiting a lake in August.
4
(iii) Estimate the average amount that undergraduate students spent on textbooks at your univer­
sity in the fall semester.
(iv) Estimate the total weight of usable meat (discarding bones, fat, and skin) in a shipment of
chickens.
[20 marks, 4+4+6+6]
Question 5 Suppose a city has 90,000 dwelling units, of which 35,000 are houses, 45,000 are apartments, and 10,000
are condominiums. You believe that the mean electricity usage is about twice as much for houses as for
apartments or condominiums and that the standard deviation is proportional to the mean.
(a) How would you allocate a sample of 900 observations if you want to estimate the mean electricity
consumption for all households in the city?
(b) Now suppose that you want to estimate the overall proportion of households in which energy
conservation is practiced. You have strong reason to believe that about 45% of house dwellers use
some sort of energy conservation and that the corresponding percentages are 25% for apartment
dwellers and 3% for condominium residents. What gain would proportional allocation offer over
simple random sampling?
(c) Someone else has taken a small survey. using an SRS, of energy usage in houses. On the basis of
the survey, each house is categorized as having electric heating or some other kind of heating. The
January electricity consumption in kilowatt-hours for each house is recorded (Yi) and the results are
given below:
Type of
Heating
Electric
Nonelectric
Total
Number of Sample
Houses
Mean
24
972
463
36
60
Sample
Variance
202,396
96,721
From other records, it is known that 16,450 of the 35,000 houses have electric heating, and 18,550
have nonelectric heating.
(i) Using the sample, give an estimate and its standard error of the proportion of houses with
electric heating. Does your 95% (I include the true proportion?
(ii) Give an estimate and its standard error of the average number of kilowatt-hours used by houses
in the city. What type of estimator did you use, and why did you choose that estimator?
5
Useful formulas
L:~l (Yi - y)2
n 1
= fj
Mara
•
n
~
Pars
~
Thh
"Yi
= {;;;t n
1 ~Yi
L...J ­
n i=l Pi
=-
~
Thh
j.£hh = ­
N
Mr
= rj.£x
h =
Nj.£L
L
~
" Nh _
= L...J N
j.£str
Yh
h=l
Tstr
~
Pstr
=
N Mstr
L
" Nh ~
= L...J N
Ph
h=l
L
Mpstr
=
L
W hiA
h=l
6
M
fel
n
N
L
i=l j=l
{i,el
n
"n
L...i=l
82
u
= Nfl
i=l
L
fI
L
fel
M
-=­
3'=1
y.l -_ icl.
N
8
where
n
I:I:
Yij
.
= -nL.
~=1
1n
n
-- I:Yi
i=l j=l
1
where Y-
N
L
n
I:I:Yij = --n I:I: Yij
nL
=-
2
A(A ) _ N(N - n)
N(N - n).2!
n
2
= 2:'-1n-l
(lIi-jj) .
{i,1
V
fel
= fI
~el
V({i,l
N
-
M2
8!
-­
n
N-n8 2
_ _ .2!
N n
The formulas for systematic sampling are the same as those used for one-stage cluster sampling. Change
the subscript cI to sys to denote the fact that data were collected under systematic sampling.
To estimate T, multiply {i,c(.) by M. To get the estimated variances, mUltiply V({i,cO) by M2. If M is not
known, substitute M with Nm/n. m= 2::=1 Mi/n.
n for
~
SRS
n for
T
SRS
n for p SRS
1)(dl/z2) + 0-2
N0-2
(N -1)(dl/z2N2) + 0-2
n = (N
n
=
Np(l- p)
1)(dl/z2) + p(l - p)
N0-2
n = --:-::-:-:----:-c~-;--;:;----:::(N -1)(dl/z2) + 0-2
N0- 2
n = (N -1)(dl/z2N2) + 0-2
n
= (N
n for
~
SYS
n for
T
SYS
n for
~
STR
n=
n for
T
STR
n
'E~=1 N~(o-VWh)
N2(dl/z 2) + 'ELI Nho-~
'E~=1 Nl(o-VWh)
N2(dl/z2N2) + 'E~=1 Nho-~
7
where
Wh
=~. Allocations for STR p,: (c - eo)
n
•
=
(E~=l NkC1kVck) (E~=l Nk(JkVck)
N2(d2/z2) + L:~=l Nk(JI
N2(d2/Z2) + 11 E~=l Nk(JI
(E~=l Nk(Jk) 2
n
Allocations for STR r: Allocations for STR p: 8
STATISTICAL TABLES
1
TABLEA.1 Cumulative Standardizeci Normal Distribution A(z) is the integral ofthe standardized normal
distribution from - 00 to z (in other words, the
area under the curve to the left of z). It gives the
probability of a normal random variable not
being more than z standard deviations above its
mean. Values ofz of particular importance:
-4
-3
·2
·1
0
1 Z
2
z
A(z}
1.645
1.960
2.326
2.576
3.090
3.291
0.9500
0.9750
0.9900
0.9950
0.9990
0.9995
Lower limit of right 5% tail
Lower limit of right 2.5% tail
Lower limit ofright 1% tail
Lower limit of right 0.5% tail
Lower limit ofrigbtO.l% tail
Lower limit of right 0.05% tail
4
3
z
0.00
0.01
0.02
0.03
0.04
0.05
0.06
0.07
0.08
0.09
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0,7
0.8
0,9
1,0
J.l
1.2
1.3
1.4
1.5
1.6
1.7
1.8
1.9
2.0
2.1
2,2
2.3
2.4
2.5
2.6
2.7
2.8
2.9
3.0
3.1
3.2
3.3
3.4
3.5
3.6
0.5000
0.5398
0.5793
0.6179
0.6554
0.6915
0.7257
0.7580
0.7881
0,8159
0,8413
0.8643
0.8849
0.9032
0.9192
0.9332
0.9452
0.9554
0.9641
0,9713
0.9772
0.9821
0.9861
0.9893
0.9918
0.9938
0.9953
0.9965
0.9974
0.9981
0.9987
0.9990
0.9993
0.9995
0.9997
0.9998
0.9998
0.5040
0.5438
0.5832
0.6217
0.6591
0.6950
0.7291
0.7611
0.7910
0.8186
0,8438
0,8665
0.8869
0.9049
0.9207
0.9345
0.9463
0,9564
0.9649
0.9719
0.9778
0.9826
0.9864
0.9896
0.9920
0.9940
0.9955
0.9966
0.9975
0.9982
0.9987
0.9991
0.9993
0.9995
0.9997
0.9998
0.9998
0.5080
0.5478
0.5871
0.6255
0.6628
0.6985
0.7324
0.7642
0.7939
0.8212
0,8461
0.8686
0.8888
0.9066
0.9222
0.9357
0.9474
0.9573
0.9656
0,9726
0,9783
0.9830
0.9868
0.9898
0,9922
0.9941
0.9956
0.9967
0.9976
0.9982
0.9987
0.9991
0.9994
0.9995
0.9997
0.9998
0.9999
0.5120
0.5517
0.5910
0.6293
0.6664
0.7019
0.7357
0,7673
0.7967
0.8238
0.8485
0.8708
0.8907
0.9082
0.9236
0.9370
0.9484
0.9582
0.9664
0.9732
0.9788
0.9834
0.9871
0.9901
0.9925
0.9943
0.9957
0.9968
0.9977
0.9983
0.9988
0.9991
0.9994
0.9996
0.9997
0.9998
0.5160
0.5557
0.5948
0.6331
0.6700
0.7054
0.7389
0.7704
0.7995
0.8264
0,8508
0.8729
0.8925
0.9099
0.9251
0.9382
0.9495
0.9591
0.9671
0,9738
0.9793
0.9838
0.9875
0.9904
0.9927
0.9945
0.9959
0.9969
0.9977
0.9984
0.9988
0.9992
0.9994
0.9996
0.9997
0.9998
0.5199
0.5596
0.5987
0.6368
0.6736
0.7088
0.7422
0.7734
0.8023
0.8289
0.8531
0,8749
0.8944
0.9115
0.9265
0.9394
0.9505
0.9599
0.9678
0.9744
0.9798
0.9842
0.9878
0.9906
0.9929
0.9946
0.9960
0.9970
0.9978
0.9984
0.9989
0.9992
0.9994
0.9996
0.9997
0.9998
0.5239
0.5636
0.6026
0.6406
0.6772
0.7123
0.7454
0.7764
0.8051
0,8315
0.8554
0.8770
0.8962
0.9131
0.9279
0.9406
0.9515
0.9608
0.9686
0.9750
0.9803
0.9846
0.9881
0.9909
0.9931
0.9948
0.9961
0.9971
0.9979
0.9985
0.9989
0.9992
0.9994
0.9996
0.9997
0.9998
0.5279
0.5675
0.6064
0.6443
0.6808
0.7157
0.7486
0.7794
0.8078
0,8340
0.8577
0.8790
0.8980
0.9147
0.9292
0.9418
0.9525
0.9616
0.9693
0.9756
0.9808
0.9850
0.9884
0.9911
0.9932
0.9949
0.9962
0.9972
0.9979
0.9985
0.9989
0.9992
0.9995
0.9996
0.9997
0.9998
0.5319
0.5714
0.6103
0.6480
0.6844
0.7190
0.7517
0.7823
0.8106
0.8365
0.8599
0.8810
0.8997
0.9162
0.9306
0.9429
0.9535
0.9625
0.9699
0.9761
0.9812
0.9854
0.9887
0.9913
0.9934
0.9951
0.9963
0.9973
0.9980
0.9986
0.9990
0.9993
0.9995
0.9996
0.9997
0.9998
0.5359
0.5753
0.6141
0.6517
0.6879
0.7224
0.7549
0.7852
0.8133
0,8389
0.8621
0.8830
0.9015
0.9177
0.9319
0.9441
0.9545
0.9633
0.9706
0.9767
0.9817
0.9857
0.9890
0.9916
0.9936
0.9952
0.9964
0.9974
0.9981
0.9986
0.9990
0.9993
0.9995
0.9997
0.9998
0.9998
9
STATISTICAL TABLES
2
TABLEA.2
t Distribution: Critical Values of t
Significance level
Degrees 0/
freedom
Two-tailed test:
One-tailed test:
10"A.
5%
5%
2.5%
6.314
2.920
2.353
2.132
2.015
12.706
4.303
3.182
2.776
2.571
1.943
1%
0.5%
0.2%
0.1%
0.1%
0.05%
31.821
6.965
4.541
3.747
3.365
63.657
9.925
5.841
4.604
4.032
318.309
22.327
10.215
7.173
5.893
636.619
31.599
12.924
8.610
6.869
1.860
1.833
1.812
2.447
2.365
2.306
2.262
2.228
3.143
2.998
2.896
2.821
2.764
3.707
3.499
3.355
3.250
3.169
5.208
4.785
4.501
4.297
4.144
5.959
5.408
5.041
4.781
4.587
1.796
1.782
1.771
1.761
1.753
2.201
2.179
2.160
2.145
2.131
2.718
2.681
2.650
2.624
2.602
3.106
3.055
3.012
2.977
2.947
4.025
3.930
3.852
3.787
3.733
4.437
4.318
4.221
4.140
4.073
20
1.746
1.740
1.734
1.729
1.725
2.120
2.110
2.101
2.093
2.086
2.583
2.567
2.552
2.539
2.528
2.921
2.898
2.878
2.861
2.845
3.686
3.646
3.610
3.579
3.552
4.015
3.965
3.922
3.883
3.850
21
22
23
24
25
1.721
1.717
1.714
1.711
1.708
2.080
2.074
2.069
2.064
2.060
2.518
2.508
2.500
2.492
2.485
2.831
2.819
2.807
2.797
2.787
3.527
3.505
3.485
3.467
3.450
3.819
3.792
3.768
3.745
3.725
26
29
30
1.706
1.703
1.701
1.699
1.697
2.056
2.052
2.048
2.045
2.042
2.479
2.473
2.467
2.462
2.457
2.779
2.771
2.763
2.756
2.750
3.435
3.421
3.408
3.396
3.385
3.707
3.690
3.674
3.659
3.646
32
34
36
38
40
1.694
1.691
1.688
1.686
1.684
2.037
2.032
2.028
2.024
2.021
2.449
2.441
2.434
2.429
2.423
2.738
2.728
2.719
2.712
2.704
3.365
3.348
3.333
3.319
3.307
3.622
3.601
3.582
3.566
3.551
42
44
46
50
1.682
1.680
1.679
1.677
1.676
2.018
2.015
2.013
2.011
2.009
2.418
2.414
2.410
2.407
2.403
2.698
2.692
2.687
2.682
2.678
3.296
3.286
3.277
3.269
3.261
3.538
3.526
3.515
3.505
3.496
60
70
80
90
100
1.671
1.667
1.664
1.662
1.660
2.000
1.994
1.990
1.987
1.984
2.390
2.381
2.374
2.368
2.364
2.660
2.648
2.639
2.632
2.626
3.232
3.211
3.195
3.183
3.174
3.460
3.435
3.416
3.402
3.390
120
150
200
300
400
1.658
1.655
1.653
1.650
1.649
1.980
1.976
1.972
1.968
1.966
2.358
2.351
2.345
2.339
2.336
2.617
2.609
2.601
2.592
2.588
3.160
3.145
3.131
3.118
3.m
3.373
3.357
3.340
3.323
3.315
500
600
1.648
1.647
1.965
1.964
2.334
2.333
2.586
2.584
3.107
3.104
3.310
3.307
co
1.645
1.960
2.326
2.576
3.090
3.291
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
27
28
48
1.894
10 2%
1%
```