Statistic

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1. (6)

It has been suggested that the average Facebook user spends 6 hours a week on the site. If we

assume a normal distribution, with a population standard deviation of 3 hours…

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i.(3)

What p

ercentage of users spend more than 9 hours on Facebook?

ii.(3)

What p

ercentage of users spend between 2 and 4 hours on Facebook?

2. (6)

On final exams, Sarah scored 90 in Economics and Martha scored 85 in Geography. We can assume

that the students’ scores within each subject are approximately “normal” in distribution. The

mean scores

in Economics and Geography were both 72. The standard deviation in Economics was 12 points, while in

Geography it was 8.

Which of the two students has a better score, compared with his/her fellow students? Please show how you

arrived at your

conclusion.

3. (4)

What is the difference between random sampling, stratified random sampling, and cluster sampling? How

might random sampling of the entire population in the US help us understand the current spread of COVID

19,

rather than just testing

people who show symptoms?

4. A group of researchers at the University of Texas

Houston conducted a comprehensive study of

pregnant cocaine

dependent women (

Journal of Drug Issues

, Summer 1997). All the women in the study

used cocaine on a regular basis for

more than a year. One of the many variables measured was birth

weight (in grams) of the baby delivered. For a sample of 16 cocaine

dependent women, the mean birth

weight was 2,971 grams and the standard deviation was 410 grams. Test the hypothesis that th

e true

mean birth weight of babies delivered by cocaine

dependent women is less than 3,100 grams. Use alpha =

.05.

5. (3)

Confidence bands for population means are smaller if you (1) know the standard deviation of the

population, instead of estimating it

from the sample, or (2) if you decrease the level of confidence

required. In addition to these two possibilities, how else could you obtain a smaller confidence band?

6. (3)

We can calculate confidence bands for means by using z

values

from a normal dis

tribution table (or t

-values

from a t

distribution table), even if the population under study is not normally distributed. Briefly explain the

property of random samples that makes this possible.

1. (6)
It has been suggested that the average Facebook user spends 6 hours a week on the site. If we
assume a normal distribution, with a population standard deviation of 3 hours…

i.(3)
What percentage of users spend more than 9 hours on Facebook?

ii.(3)
What p
ercentage of users spend between 2 and 4 hours on Facebook?

2. (6)
On final exams, Sarah scored 90 in Economics and Martha scored 85 in Geography. We can assume
that the students’ scores within each subject are approximately “normal” in distribution. The

mean scores
in Economics and Geography were both 72. The standard deviation in Economics was 12 points, while in
Geography it was 8.

Which of the two students has a better score, compared with his/her fellow students? Please show how you
arrived at your
conclusion.

3. (4)
What is the difference between random sampling, stratified random sampling, and cluster sampling? How
might random sampling of the entire population in the US help us understand the current spread of COVID

19,
rather than just testing
people who show symptoms?

4. A group of researchers at the University of Texas

Houston conducted a comprehensive study of
pregnant cocaine

dependent women (
Journal of Drug Issues
, Summer 1997). All the women in the study
used cocaine on a regular basis for

more than a year. One of the many variables measured was birth
weight (in grams) of the baby delivered. For a sample of 16 cocaine

dependent women, the mean birth
weight was 2,971 grams and the standard deviation was 410 grams. Test the hypothesis that th
e true
mean birth weight of babies delivered by cocaine

dependent women is less than 3,100 grams. Use alpha =
.05.

5. (3)
Confidence bands for population means are smaller if you (1) know the standard deviation of the
population, instead of estimating it

from the sample, or (2) if you decrease the level of confidence
required. In addition to these two possibilities, how else could you obtain a smaller confidence band?

6. (3)
We can calculate confidence bands for means by using z

values from a normal dis
tribution table (or t

values
from a t

distribution table), even if the population under study is not normally distributed. Briefly explain the
property of random samples that makes this possible.

1. (6) It has been suggested that the average Facebook user spends 6 hours a week on the site. If we

assume a normal distribution, with a population standard deviation of 3 hours…

i.(3) What percentage of users spend more than 9 hours on Facebook?

ii.(3) What percentage of users spend between 2 and 4 hours on Facebook?

2. (6) On final exams, Sarah scored 90 in Economics and Martha scored 85 in Geography. We can assume

that the students’ scores within each subject are approximately “normal” in distribution. The mean scores

in Economics and Geography were both 72. The standard deviation in Economics was 12 points, while in

Geography it was 8.

Which of the two students has a better score, compared with his/her fellow students? Please show how you

arrived at your conclusion.

3. (4) What is the difference between random sampling, stratified random sampling, and cluster sampling? How

might random sampling of the entire population in the US help us understand the current spread of COVID-19,

rather than just testing people who show symptoms?

4. A group of researchers at the University of Texas-Houston conducted a comprehensive study of

pregnant cocaine-dependent women (Journal of Drug Issues, Summer 1997). All the women in the study

used cocaine on a regular basis for more than a year. One of the many variables measured was birth

weight (in grams) of the baby delivered. For a sample of 16 cocaine-dependent women, the mean birth

weight was 2,971 grams and the standard deviation was 410 grams. Test the hypothesis that the true

mean birth weight of babies delivered by cocaine-dependent women is less than 3,100 grams. Use alpha =

.05.

5. (3) Confidence bands for population means are smaller if you (1) know the standard deviation of the

population, instead of estimating it from the sample, or (2) if you decrease the level of confidence

required. In addition to these two possibilities, how else could you obtain a smaller confidence band?

6. (3) We can calculate confidence bands for means by using z-values from a normal distribution table (or t-values

from a t-distribution table), even if the population under study is not normally distributed. Briefly explain the

property of random samples that makes this possible.

2

>Q

3

1

99

97

98

99

97

96

98

98

99

91

95

91

98

99

94

95

94

98

93

97

98

98

97

90

93

93

98

100

99

94

93

91

95

94

94

98

94

98

100

92

93

96

97

95

96

100

96

98

97

95

Year Maximum August Temperature
2

0 1 7 9 5
20 6 97
20

15 9

8
201

4 91
20

13 99
20

12 98
20

11
20

10
2009
2008 104
2007
2006 96
2005
2004
2003
2002 100
2001 95
2000
19
1998
1997
1996
1995 101
19

94
19

93
19

92
1991
19

90
19

89
19

88
19

87
19

86
19

85
19

84
19

83
19

82
19

81
19

80
19

79
19

78
19

77
19

76
19

75
19

74
19

73
19

72
19

71
19

70
19

69
19

68
19

67
19

66
19

65
19

64
19

63
19

62
19

61
19

60
19

59
19

58

Q5

% export value

1

19

2

3

4

19

5

20

6

7

8

9

18

10

31

11

12

13

ia

84

15

62

17

18

16

19

13

20

41

20

70

18

14

Country Corruption Index

1

16

2

36

3

4

5

35

6

77

7

76

8

9

68

10

11

75

12

40

13

14

15

61

16

35

17

18

41

19

17

20

20

21

25

22

81

23

67

24

25

36

26

27

35

28

29

59

31

59

88

30

34

35

35

35

36

24

73

38

34

39

85

40

72

41

58

42

80

41

44

45

27

37

47

20

48

29

49

76

50

46

76

52

41

38

73

61

56

52

44

58

73

59

49

60

27

61

, South

57

62

29

63

29

64

58

65

28

66

41

67

32

68

59

69

81

70

, Republic of

37

71

25

72

32

73

47

74

32

75

54

76

51

77

28

78

33

79

37

80

43

81

23

82

29

83

53

84

31

85

82

86

ealand

87

87

25

88 Niger 34
89

33

90

37

91

28

92

29

93

35

94

36

95

60

96

64

97

47

98

28

99

56

100

45

101

39

30

85

104

50

60

10

43

58

38

43

85

85

63

25

36

36

43

41

26

32

80

71

70

23

33

35

22

Oil & Gas >

50 Corruption data – https://www.transparency.org/cpi20

18
Country Corruption Index
Angola
Azerbaijan 25
Bahrain 36
Chad
Congo, Democratic Republic of the
Ecuador 34
Gabon 31
Iran 28
Iraq
Kazakhstan
Kuwait 41
Libya 17
Niger 27
14 Norway
Oman 52
16 Qatar
Saudi Arabia 49
Sudan
Syria
Trinidad and Tobago
21 Turkmenistan
22 United Arab Emirates
23 Venezuela
24 Yemen
Oil & Gas <50% export value
Afghanistan
Albania
Algeria 35
Argentina 40
Armenia
Australia
Austria
Bangladesh 26
Barbados
Belarus 44
Belgium
Benin
Bolivia 29
Bosnia and Herzegovina 38
Botswana
Brazil
Bulgaria 42
Burkina Faso
Burundi
Cambodia
Cameroon
Canada
Chile
China 39
Colombia
Costa Rica 56
Côte d’Ivoire
Croatia 48
Cuba 47
30 Cyprus
Czech Republic
32 Denmark
33 Dominican Republic
Egypt
El Salvador
Eritrea
37 Estonia
Ethiopia
Finland
France
Georgia
Germany
43 Ghana
Greece 45
Guatemala
46 Guyana
Haiti
Honduras
Hong Kong
Hungary
51 Iceland
India
53 Indonesia
54 Ireland
55 Israel
Italy
57 Jamaica
Japan
Jordan
Kenya
Korea
Kyrgyzstan
Laos
Latvia
Lebanon
Lesotho
Liberia
Lithuania
Luxembourg
Macedonia
Madagascar
Malawi
Malaysia
Mali
Malta
Mauritius
Mexico
Moldova
Mongolia
Morocco
Mozambique
Myanmar
Namibia
Nepal
Netherlands
New

Z
Nicaragua
Pakistan
Panama
Papua New Guinea
Paraguay
Peru
Philippines
Poland
Portugal
Romania
Russia
Rwanda
Senegal
Serbia
102 Sierra Leone
103 Singapore
Slovakia
105 Slovenia
106 Somalia
107 South Africa
108 Spain
109 Sri Lanka
110 Suriname
111 Sweden
112 Switzerland
113 Taiwan
114 Tajikistan
115 Tanzania
116 Thailand
117 Tunisia
118 Turkey
119 Uganda
120 Ukraine
121 United Kingdom
122 United States
123 Uruguay
124 Uzbekistan
125 Vietnam
126 Zambia
127 Zimbabwe

Q12

Albania

016

2

Algeria

Argentina

Australia

Austria

Belgium

91

Brazil

Bulgaria

Canada

Chile

China

Colombia 425

Costa Rica

Croatia

Cyprus

Czech Republic 487

Denmark

Dominican Republic

Estonia

Finland

France 499

Georgia

Germany

Greece

Hong Kong 527

Hungary

Iceland

Indonesia

Ireland

Israel

Italy 485

Japan

Jordan

427

Korea

Latvia

Lebanon 347

Lithuania 472

Luxembourg

Macedonia

Malaysia

Malta

Mexico

Moldova

5.838

427

Netherlands 503

New Zealand 509

Norway

Peru

Poland

Portugal

Qatar

Romania

Russia

Singapore

Slovenia

Spain

Sweden 500 7.284
Switzerland

Taiwan

Thailand

Trinidad and Tobago 427

Tunisia

Turkey

00

434

498

United States 497

Uruguay

Vietnam 487

Reading Comprehension
Qingling Wu: Percentage of 13-year-old students who come from households with at least one computer, 2002
Happiness
Qingling Wu: This statistic is compiled from responses to the survey question: “Taking all things together, would you say you are: very happy, quite happy, not very happy, or not at all happy?”. The “Happiness (net)” statistic was obtained via the following formula: the percentage of people who rated themselves as either “quite happy” or “very happy” minus the percentage of people who rated themselves as either “not very happy” or “not at all happy”.
405 4.644 Reading Comprehension Data – http://www.businessinsider.com/pisa-worldwide-ranking-of-math-science-reading-skills

-2 -1
350 5.872 Happiness Index Data -http://worldhappiness.report/ed/2017/
425 6.599
503 7.284
485 7.006
499 6.8
407 6.635
432 4.714
527 7.316
459 6.652
494 5.273
6.357
427 7.079
487 5.293
443 5.621
6.609
500 7.522
358 5.230
519 5.611
526 7.469
6.442
401 4.286
509 6.951
467 5.227
5.

472
470 5.324
482 7.504
397 5.262
521 6.977
479 7.213
5.964
516 5.920
408 5.336
Kazahkstan 5.819
517 5.838
Kosovo 347 5.279
488 5.850
5.225
5.902
481 6.863
352 5.

175
431 6.084
447 6.527
423 6.578
416
Montenegro 5.237
7.377
7.314
513 7.537
398 5.715
506 5.973
498 5.195
402 6.375
434 5.825
495 5.963
535 6.572
Slovak Republic 453 6.098
505 5.758
496 6.403
492 7.494
497 6.422
409 6.424
6.168
361 4.805
428 5.5
UAE 6.648
United Kingdon 6.714
6.993
437 6.454
5.074

Q13

8

5

423

115

5.5

50

521

10 115

62

70

6.8

35 56

2

1

175

100

0.12 3

Pig

Body Weight (kg) Brain Weight (g)
Brachiosaurus 87000 154.5
Rat 0.2 1.9
Beaver 1.3 8.1
Cow 465
Grey Wolf 36.33 119.5
Goat 27.66
Guinea

Pig 1.04
Diplodocus 11700
Asian elephant 2547 4603
Donkey 187.1 419
Horse 655
Potar monkey
Cat 3.3 25.6
Giraffe 529 680
Gorilla 207 406
Human 1320
African elephant 6654 5712
Triceratops 9400
Rhesus monkey 179
Kangaroo
Hamster 0.1
Mouse 0.02 0.4
Rabbit 2.5 1

2.1
Sheep 55.5
Jaguar 157
Chimpanzee 52.16 440
Mole
192 180
Source: Jerison, H. J. Evolution of the Brain and Intelligence New York: Academic Press, 1973.

ztable

Z 0

0.02

0.0013 0.0013

0.0012

0.0011 0.0011

0.0010

0.0017

0.0016

0.0015

0.0014

0.0023

0.0021

0.0019

0.0026

9

-2

6

-1

78

085

0

0 0.5000

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

1.1

1.2

1.3

1.4

1.5

1.6

1.7

1.8

1.9

2

2.1

2.2

2.3

2.4

2.5

2.6

2.7

2.8 0.9974

0.9977

0.9979

2.9 0.9981

0.9983

0.9984

0.9985

0.9986

3

0.9987 0.9987

0.9988

0.9989 0.9989

0.9990

0.9990

0.9991 0.9991

0.9992 0.9992 0.9992

0.9993

0.9993 0.9993

0.9994 0.9994 0.9994 0.9994

0.9995 0.9995

3.3 0.9995 0.9995 0.9995

0.9996 0.9996 0.9996 0.9996 0.9996

0.9997 0.9997 0.9997 0.9997 0.9997 0.9997 0.9997 0.9997 0.9997

Standard Normal Distribution Table
Probability (x <= Z)
Mean = 0
Standard Deviation = 1
0.01 0.03 0.04 0.05 0.06 0.07 0.08 0.09
-3 0.0013 0.0012 0.0011 0.0010

2.9 0.0019 0.0018 0.0017 0.0016 0.0015 0.0014

2.8 0.0026 0.0025 0.0024 0.0023 0.0022 0.0021 0.0020

2.7 0.0035 0.0034 0.0033 0.0032 0.0031 0.0030 0.0029 0.0028 0.0027

2.6 0.0047 0.0045 0.0044 0.0043 0.0041 0.0040 0.0039 0.0038 0.0037 0.0036
-2.5 0.0062 0.0060 0.005 0.0057 0.0055 0.0054 0.0052 0.0051 0.0049 0.0048

2.4 0.0082 0.0080 0.0078 0.0075 0.0073 0.0071 0.0069 0.0068 0.0066 0.0064

2.3 0.0107 0.0104 0.0102 0.0099 0.0096 0.0094 0.0091 0.0089 0.0087 0.0084

2.2 0.0139 0.0136 0.0132 0.0129 0.0125 0.0122 0.0119 0.0116 0.0113 0.0110
-2.1 0.0179 0.0174 0.0170 0.0166 0.0162 0.0158 0.0154 0.0150 0.0146 0.0143
0.0227 0.0222 0.0217 0.0212 0.0207 0.0202 0.0197 0.0192 0.0188 0.0183
-1.9 0.0287 0.0281 0.0274 0.0268 0.0262 0.025 0.0250 0.0244 0.0239 0.0233

1.8 0.0359 0.0351 0.0344 0.0336 0.0329 0.0322 0.0314 0.0307 0.0301 0.0294

1.7 0.0446 0.0436 0.0427 0.0418 0.0409 0.0401 0.0392 0.0384 0.0375 0.0367

1.6 0.0548 0.0537 0.0526 0.0516 0.0505 0.0495 0.0485 0.0475 0.0465 0.0455

1.5 0.0668 0.0655 0.0643 0.0630 0.0618 0.0606 0.0594 0.0582 0.0571 0.0559

1.4 0.0808 0.0793 0.0778 0.0764 0.0749 0.0735 0.0721 0.0708 0.0694 0.0681
-1.3 0.0968 0.0951 0.0934 0.0918 0.0901 0.0885 0.0869 0.0853 0.0838 0.0823

1.2 0.1151 0.1131 0.1112 0.1093 0.1075 0.1056 0.1038 0.1020 0.1003 0.0985

1.1 0.1357 0.1335 0.1314 0.1292 0.1271 0.1251 0.1230 0.1210 0.1190 0.1170
0.1587 0.1562 0.1539 0.1515 0.1492 0.1469 0.1446 0.1423 0.1401 0.1379

0.9 0.1841 0.1814 0.1788 0.1762 0.1736 0.1711 0.1685 0.1660 0.1635 0.1611

0.8 0.2119 0.2090 0.2061 0.2033 0.2005 0.1977 0.1949 0.1922 0.1894 0.1867

0.7 0.2420 0.2389 0.2358 0.2327 0.2296 0.2266 0.2236 0.2206 0.2177 0.2148

0.6 0.2743 0.2709 0.2676 0.2643 0.2611 0.25 0.2546 0.2514 0.2483 0.2451

0.5 0.3 0.3050 0.3015 0.2981 0.2946 0.2912 0.2877 0.2843 0.2810 0.2776
-0.4 0.3446 0.3409 0.3372 0.3336 0.3300 0.3264 0.3228 0.3192 0.3156 0.3121
-0.3 0.3821 0.3783 0.3745 0.3707 0.3669 0.3632 0.3594 0.3557 0.3520 0.3483
-0.2 0.4207 0.4168 0.4129 0.4090 0.4052 0.4013 0.3974 0.3936 0.3897 0.3859
-0.1 0.4602 0.4562 0.4522 0.4483 0.4443 0.4404 0.4364 0.4325 0.4286 0.4247
0.5000 0.4960 0.4920 0.4880 0.4840 0.4801 0.4761 0.4721 0.4681 0.4641
0.5040 0.5080 0.5120 0.5160 0.5199 0.5239 0.5279 0.5319 0.5359
0.5398 0.5438 0.5478 0.5517 0.5557 0.5596 0.5636 0.5675 0.5714 0.5753
0.5793 0.5832 0.5871 0.5910 0.5948 0.5987 0.6026 0.6064 0.6103 0.6141
0.6179 0.6217 0.6255 0.6293 0.6331 0.6368 0.6406 0.6443 0.6480 0.6517
0.6554 0.6591 0.6628 0.6664 0.6700 0.6736 0.6772 0.6808 0.6844 0.6879
0.6915 0.6950 0.6985 0.7019 0.7054 0.7088 0.7123 0.7157 0.7190 0.7224
0.7257 0.7291 0.7324 0.7357 0.7389 0.7422 0.7454 0.7486 0.7517 0.7549
0.7580 0.7611 0.7642 0.7673 0.7704 0.7734 0.7764 0.7794 0.7823 0.7852
0.7881 0.7910 0.7939 0.7967 0.7995 0.8023 0.8051 0.8078 0.8106 0.8133
0.8159 0.8186 0.8212 0.8238 0.8264 0.8289 0.8315 0.8340 0.8365 0.8389
0.8413 0.8438 0.8461 0.8485 0.8508 0.8531 0.8554 0.8577 0.8599 0.8621
0.8643 0.8665 0.8686 0.8708 0.8729 0.8749 0.8770 0.8790 0.8810 0.8830
0.8849 0.8869 0.8888 0.8907 0.8925 0.8944 0.8962 0.8980 0.8997 0.9015
0.9032 0.9049 0.9066 0.9082 0.9099 0.9115 0.9131 0.9147 0.9162 0.9177
0.9192 0.9207 0.9222 0.9236 0.9251 0.9265 0.9279 0.9292 0.9306 0.9319
0.9332 0.9345 0.9357 0.9370 0.9382 0.9394 0.9406 0.9418 0.9429 0.9441
0.9452 0.9463 0.9474 0.9484 0.9495 0.9505 0.9515 0.9525 0.9535 0.9545
0.9554 0.9564 0.9573 0.9582 0.9591 0.9599 0.9608 0.9616 0.9625 0.9633
0.9641 0.9649 0.9656 0.9664 0.9671 0.9678 0.9686 0.9693 0.9699 0.9706
0.9713 0.9719 0.9726 0.9732 0.9738 0.9744 0.9750 0.9756 0.9761 0.9767
0.9773 0.9778 0.9783 0.9788 0.9793 0.9798 0.9803 0.9808 0.9812 0.9817
0.9821 0.9826 0.9830 0.9834 0.9838 0.9842 0.9846 0.9850 0.9854 0.9857
0.9861 0.9864 0.9868 0.9871 0.9875 0.9878 0.9881 0.9884 0.9887 0.9890
0.9893 0.9896 0.9898 0.9901 0.9904 0.9906 0.9909 0.9911 0.9913 0.9916
0.9918 0.9920 0.9922 0.9925 0.9927 0.9929 0.9931 0.9932 0.9934 0.9936
0.9938 0.9940 0.9941 0.9943 0.9945 0.9946 0.9948 0.9949 0.9951 0.9952
0.9953 0.9955 0.9956 0.9957 0.9959 0.9960 0.9961 0.9962 0.9963 0.9964
0.9965 0.9966 0.9967 0.9968 0.9969 0.9970 0.9971 0.9972 0.9973 0.9974
0.9975 0.9976 0.9977 0.9978 0.9979 0.9980 0.9981
0.9982 0.9983 0.9984 0.9985 0.9986
0.9987 0.9988 0.9989 0.9990
3.1 0.9991 0.9992 0.9993
3.2 0.9994 0.9995
0.9996 0.9997
3.4 0.9998

ttable

The Shape of the Student’s t distribution is determined by the degrees of freedom. As shown in the animation above, its shape changes as the degrees of freedom increases. For more

inf

ormation on how this distribution is used in hypothesis testing, see t-test for independent samples and t-test for dependent samples in the chapter on Basic Statistics and Tables. See also, Student’s t Distribution. As indicated by the chart below, the areas given at the top of this table are the right tail areas for the t-value inside the table. To determine the 0.05 critical value from the t-distribution with 6 degrees of freedom, look in the 0.05 column at the 6 row: t(.05,6) =

1.94318

0. t table with right tail probabilities df\p

0.4 0.25 0.1 0.05 0.025 0.01 0.005

0.0005 1

0.32492

1

3.077684 6.313752 12.7062 31.82052 63.65674 636.6192 2

0.288675 0.816497 1.885618 2.919986 4.30265 6.96456 9.92484 31.5991 3

0.276671 0.764892 1.637744 2.353363 3.18245 4.5407 5.84091 12.924 4

0.270722 0.740697 1.533206 2.131847 2.77645 3.74695 4.60409 8.6103 5

0.267181 0.726687 1.475884 2.015048 2.57058 3.36493 4.03214 6.8688 6

0.264835 0.717558 1.439756

1.94318

2.44691 3.14267 3.70743 5.9588 7

0.263167 0.711142 1.414924 1.894579 2.36462 2.99795 3.49948 5.4079 8

0.261921 0.706387 1.396815 1.859548 2.306 2.89646 3.35539 5.0413 9

0.260955 0.702722 1.383029 1.833113 2.26216 2.82144 3.24984 4.7809 10

0.260185 0.699812 1.372184 1.812461 2.22814 2.76377 3.16927 4.5869 11

0.259556 0.697445 1.36343 1.795885 2.20099 2.71808 3.10581 4.437 12

0.259033 0.695483 1.356217 1.782288 2.17881 2.681 3.05454 4.3178 13

0.258591 0.693829 1.350171 1.770933 2.16037 2.65031 3.01228 4.2208 14

0.258213 0.692417 1.34503 1.76131 2.14479 2.62449 2.97684 4.1405 15

0.257885 0.691197 1.340606 1.75305 2.13145 2.60248 2.94671 4.0728 16

0.257599 0.690132 1.336757 1.745884 2.11991 2.58349 2.92078 4.015 17

0.257347 0.689195 1.333379 1.739607 2.10982 2.56693 2.89823 3.9651 18

0.257123 0.688364 1.330391 1.734064 2.10092 2.55238 2.87844 3.9216 19

0.256923 0.687621 1.327728 1.729133 2.09302 2.53948 2.86093 3.8834 20

0.256743 0.686954 1.325341 1.724718 2.08596 2.52798 2.84534 3.8495 21

0.25658 0.686352 1.323188 1.720743 2.07961 2.51765 2.83136 3.8193 22

0.256432 0.685805 1.321237 1.717144 2.07387 2.50832 2.81876 3.7921 23

0.256297 0.685306 1.31946 1.713872 2.06866 2.49987 2.80734 3.7676 24

0.256173 0.68485 1.317836 1.710882 2.0639 2.49216 2.79694 3.7454 25

0.25606 0.68443 1.316345 1.708141 2.05954 2.48511 2.78744 3.7251 26

0.255955 0.684043 1.314972 1.705618 2.05553 2.47863 2.77871 3.7066 27

0.255858 0.683685 1.313703 1.703288 2.05183 2.47266 2.77068 3.6896 28

0.255768 0.683353 1.312527 1.701131 2.04841 2.46714 2.76326 3.6739 29

0.255684 0.683044 1.311434 1.699127 2.04523 2.46202 2.75

639 3.6594 30

0.255605 0.682756 1.310415 1.697261 2.04227 2.45726

2.75

3.646 inf

0.253347 0.67449 1.281552 1.644854 1.95996 2.32635 2.57583 3.2905 Calculator for p values given a t score. One and two tailed tests

http://faculty.vassar.edu/lowry/tabs.html

#t

http://faculty.vassar.edu/lowry/tabs.html

1.

The “Q3” tab in the midterm excel data sheet contains data on the maximum Augu

st

temperatures for Denver

between 1958 and

2

017

. Calculate the

means

and the

standard deviations

for the

entire sample

, and then

separately for 1958

1987 and 1988

-2017

. Give the equations used to calculate the values.

2.

Transparency International compiles an index of corruption f

or over 150 world nations. The data for

these nations for 2018 is provided in the midterm excel file. The 24 nations for whom oil and gas make up

more than 50% of export revenues are separated from the other 127 nations. Note that higher values in

the inde

x indicate lower levels of corruption.

i.(4)

Find the means and variances of the corruption index for each of the two groups of countries.

ii.(8)

Construct a 95% confidence interval for the true mean difference between the two groups.

iii.(8)

Using t

-st

at, determine whether the difference in mean corruption between the two groups of countries is

statistically significant at the 95% confidence level. Give your answer in the form of a classical hypothesis test.

3.

A “Happiness” statistic of different countries was compiled by the World Value Surve

y. The

“Happiness (net)” statistic was calculated by the percentage of people who rated themselves as either

“quite happy” or “very happy” minus the percentage of people who rated themselves as either “not very

happy” or “not at all happy”. Now we want to

know if reading comprehension affects happiness. Conduct

a regression analysis for predicting “Happiness” from “Reading Comprehension” by answering the

following questions.

You can use the regression tool in the data analysis toolpak, rather than

performin

g regression manually in the spreadsheet.

i. (2)

State the dependent and independent variables and explain your selection.

ii. (2)

Make a scatterplot of the variables and comment on the relationship between X and Y evident from

the scatterplot.

iii. (5)

Perform a linear regression on the dataset. What is the regression equation

? What

is the r

2? What

does the r

2

mean?

i

v. (2)

Add a regression line to the scatter

v. (2)

Provide a .05 level of significance test for slope being 0

vi. (5)

Show and comment

on the residual plot. Are there any apparent violations of regression

assumptions or outliers?

vii. (2)

Calculate the expected net happiness of Hungary, which has a reading comprehension index of

470.

13. (20)

In the worksheet, Q12 lists a data set that

you want to investigate for the relationship between

body weight and brain weight of some animals.

Show and comment on the scatterplot, discussing the apparent relationship between the two variables.

Conduct a regression analysis (in data analysis toolpa

k) for the two variables and report the results. In

particular, comment on the strength of the relationship (i.e., coefficient of determination), the regression

coefficients, their significance, and analyze the residual plot for violations of regression as

sumptions and

outliers.

Try try to improve your initial regression by performing log transformations and/or eliminating outlier(s). After

each change, perform a new regression analysis and report the results, making sure to discuss all of the points

raise

d above. Pay particular attention to changes in the coefficient of determination and in the residual plot. After

performing 2 regression analyses with transformed variables and/or removed outliers, compare your results and

determine the best regression equ

ation. Explain why you chose that particular result.

1.

The “Q3” tab in the midterm excel data sheet contains data on the maximum August temperatures for Denver
between 1958 and 2017. Calculate the
means
and the
standard deviations
for the
entire sample
, and then
separately for 1958

1987 and 1988

2017
. Give the equations used to calculate the values.

2.
Transparency International compiles an index of corruption f
or over 150 world nations. The data for
these nations for 2018 is provided in the midterm excel file. The 24 nations for whom oil and gas make up
more than 50% of export revenues are separated from the other 127 nations. Note that higher values in
the inde
x indicate lower levels of corruption.

i.(4)
Find the means and variances of the corruption index for each of the two groups of countries.

ii.(8)
Construct a 95% confidence interval for the true mean difference between the two groups.

iii.(8)
Using t

st
at, determine whether the difference in mean corruption between the two groups of countries is
statistically significant at the 95% confidence level. Give your answer in the form of a classical hypothesis test.

3.
A “Happiness” statistic of different countries was compiled by the World Value Surve
y. The
“Happiness (net)” statistic was calculated by the percentage of people who rated themselves as either
“quite happy” or “very happy” minus the percentage of people who rated themselves as either “not very
happy” or “not at all happy”. Now we want to
know if reading comprehension affects happiness. Conduct
a regression analysis for predicting “Happiness” from “Reading Comprehension” by answering the
following questions.
You can use the regression tool in the data analysis toolpak, rather than
performin
g regression manually in the spreadsheet.

i. (2)
State the dependent and independent variables and explain your selection.

ii. (2)
Make a scatterplot of the variables and comment on the relationship between X and Y evident from
the scatterplot.

iii. (5)

Perform a linear regression on the dataset. What is the regression equation? What is the r
2
? What
does the r
2
mean?

iv. (2)
Add a regression line to the scatter

v. (2)
Provide a .05 level of significance test for slope being 0

vi. (5)
Show and comment
on the residual plot. Are there any apparent violations of regression
assumptions or outliers?

vii. (2)
Calculate the expected net happiness of Hungary, which has a reading comprehension index of
470.

13. (20)
In the worksheet, Q12 lists a data set that
you want to investigate for the relationship between
body weight and brain weight of some animals.

Show and comment on the scatterplot, discussing the apparent relationship between the two variables.

Conduct a regression analysis (in data analysis toolpa
k) for the two variables and report the results. In
particular, comment on the strength of the relationship (i.e., coefficient of determination), the regression
coefficients, their significance, and analyze the residual plot for violations of regression as
sumptions and
outliers.

Try try to improve your initial regression by performing log transformations and/or eliminating outlier(s). After
each change, perform a new regression analysis and report the results, making sure to discuss all of the points
raise
d above. Pay particular attention to changes in the coefficient of determination and in the residual plot. After
performing 2 regression analyses with transformed variables and/or removed outliers, compare your results and
determine the best regression equ
ation. Explain why you chose that particular result.

1. The “Q3” tab in the midterm excel data sheet contains data on the maximum August temperatures for Denver

between 1958 and 2017. Calculate the means and the standard deviations for the entire sample, and then

separately for 1958-1987 and 1988-2017. Give the equations used to calculate the values.

2.Transparency International compiles an index of corruption for over 150 world nations. The data for

these nations for 2018 is provided in the midterm excel file. The 24 nations for whom oil and gas make up
more than 50% of export revenues are separated from the other 127 nations. Note that higher values in

the index indicate lower levels of corruption.

i.(4) Find the means and variances of the corruption index for each of the two groups of countries.

ii.(8) Construct a 95% confidence interval for the true mean difference between the two groups.

iii.(8) Using t-stat, determine whether the difference in mean corruption between the two groups of countries is

statistically significant at the 95% confidence level. Give your answer in the form of a classical hypothesis test.

3.A “Happiness” statistic of different countries was compiled by the World Value Survey. The

“Happiness (net)” statistic was calculated by the percentage of people who rated themselves as either
“quite happy” or “very happy” minus the percentage of people who rated themselves as either “not very

happy” or “not at all happy”. Now we want to know if reading comprehension affects happiness. Conduct

a regression analysis for predicting “Happiness” from “Reading Comprehension” by answering the

following questions. You can use the regression tool in the data analysis toolpak, rather than

performing regression manually in the spreadsheet.

i. (2) State the dependent and independent variables and explain your selection.

ii. (2) Make a scatterplot of the variables and comment on the relationship between X and Y evident from

the scatterplot.

iii. (5) Perform a linear regression on the dataset. What is the regression equation? What is the r2? What

does the r2 mean?

iv. (2) Add a regression line to the scatter

v. (2) Provide a .05 level of significance test for slope being 0

vi. (5) Show and comment on the residual plot. Are there any apparent violations of regression

assumptions or outliers?

vii. (2) Calculate the expected net happiness of Hungary, which has a reading comprehension index of

470.

13. (20) In the worksheet, Q12 lists a data set that you want to investigate for the relationship between

body weight and brain weight of some animals.

Show and comment on the scatterplot, discussing the apparent relationship between the two variables.

Conduct a regression analysis (in data analysis toolpak) for the two variables and report the results. In

particular, comment on the strength of the relationship (i.e., coefficient of determination), the regression

coefficients, their significance, and analyze the residual plot for violations of regression assumptions and

outliers.

Try try to improve your initial regression by performing log transformations and/or eliminating outlier(s). After
each change, perform a new regression analysis and report the results, making sure to discuss all of the points

raised above. Pay particular attention to changes in the coefficient of determination and in the residual plot. After

performing 2 regression analyses with transformed variables and/or removed outliers, compare your results and

determine the best regression equation. Explain why you chose that particular result.

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