Fundamentals of Biostatistics 8th edition

Textbook Cover

Bernard Rosner
Publisher: Cengage Learning

enhanced content

Cengage Unlimited

Included in a Cengage Unlimited subscription. Learn More

eBook

eBook

Your students can pay an additional fee for access to an online version of the textbook that might contain additional interactive features.

lifetime of edition

Lifetime of Edition (LOE)

Your students are allowed unlimited access to WebAssign courses that use this edition of the textbook at no additional cost.

textbook resources

Textbook Resources

Additional instructional and learning resources are available with the textbook, and might include testbanks, slide presentations, online simulations, videos, and documents.


Access is contingent on use of this textbook in the instructor's classroom.

  • Chapter 1: General Overview
    • 1: Concept Explorations (2)

  • Chapter 2: Descriptive Statistics
    • 2: Concept Explorations (4)
    • 2.1: Introduction
    • 2.2: Measures of Location
    • 2.3: Some Properties of the Arithmetic Mean
    • 2.4: Measures of Spread
    • 2.5: Some Properties of the Variance and Standard Deviation
    • 2.6: The Coefficient of Variation
    • 2.7: Grouped Data
    • 2.8: Graphic Methods
    • 2.9: Case Study 1: Effects of Lead Exposure on Neurological and Psychological Function in Children
    • 2.10: Case Study 2: Effects of Tobacco Use on Bone-Mineral Density in Middle-Aged Women
    • 2.11: Obtaining Descriptive Statistics on the Computer
    • 2.12: Summary
    • 2: Problems (8)
    • 2: Labs (10)

  • Chapter 3: Probability
    • 3: Concept Explorations (4)
    • 3.1: Introduction
    • 3.2: Definition of Probability
    • 3.3: Some Useful Probabilistic Notation
    • 3.4: The Multiplication Law of Probability
    • 3.5: The Addition Law of Probability
    • 3.6: Conditional Probability
    • 3.7: Bayes' Rule and Screening Tests
    • 3.8: Bayesian Inference
    • 3.9: ROC Curves
    • 3.10: Prevalence and Incidence
    • 3.11: Summary
    • 3: Problems (14)

  • Chapter 4: Discrete Probability Distributions
    • 4: Concept Explorations (3)
    • 4.1: Introduction
    • 4.2: Random Variables
    • 4.3: The Probability-Mass Function for a Discrete Random Variable
    • 4.4: The Expected Value of a Discrete Random Variable
    • 4.5: The Variance of a Discrete Random Variable
    • 4.6: The Cumulative-Distribution Function of a Discrete Random Variable
    • 4.7: Permutations and Combinations
    • 4.8: The Binomial Distribution
    • 4.9: Expected Value and Variance of the Binomial Distribution
    • 4.10: The Poisson Distribution
    • 4.11: Computation of Poisson Probabilities
    • 4.12: Expected Value and Variance of the Poisson Distribution
    • 4.13: Poisson Approximation to the Binomial Distribution
    • 4.14: Summary
    • 4: Problems (21)
    • 4: Labs (5)

  • Chapter 5: Continuous Probability Distributions
    • 5: Concept Explorations (3)
    • 5.1: Introduction
    • 5.2: General Concepts
    • 5.3: The Normal Distribution
    • 5.4: Properties of the Standard Normal Distribution
    • 5.5: Conversion from an N(μ, σ2) Distribution to an N(0, 1) Distribution
    • 5.6: Linear Combinations of Random Variables
    • 5.7: Normal Approximation to the Binomial Distribution
    • 5.8: Normal Approximation to the Poisson Distribution
    • 5.9: Summary
    • 5: Problems (26)

  • Chapter 6: Estimation
    • 6: Concept Explorations (7)
    • 6.1: Introduction
    • 6.2: The Relationship Between Population and Sample
    • 6.3: Random-Number Tables
    • 6.4: Randomized Clinical Trials
    • 6.5: Estimation of the Mean of a Distribution
    • 6.6: Case Study: Effects of Tobacco Use on Bone-Mineral Density (BMD) in Middle-Aged Women
    • 6.7: Estimation of the Variance of a Distribution
    • 6.8: Estimation for the Binomial Distribution
    • 6.9: Estimation for the Poisson Distribution
    • 6.10: One-Sided Confidence Intervals
    • 6.11: The Bootstrap
    • 6.12: Summary
    • 6: Problems (21)
    • 6: Labs (34)

  • Chapter 7: Hypothesis Testing: One-Sample Inference
    • 7: Concept Explorations (5)
    • 7.1: Introduction
    • 7.2: General Concepts
    • 7.3: One-Sample Test for the Mean of a Normal Distribution: One-Sided Alternatives
    • 7.4: One-Sample Test for the Mean of a Normal Distribution: Two-Sided Alternatives
    • 7.5: The Relationship Between Hypothesis Testing and Confidence Intervals
    • 7.6: The Power of a Test
    • 7.7: Sample-Size Determination
    • 7.8: One-Sample Χ2 Test for the Variance of a Normal Distribution
    • 7.9: One-Sample Inference for the Binomial Distribution
    • 7.10: One-Sample Inference for the Poisson Distribution
    • 7.11: Case Study: Effects of Tobacco Use on Bone-Mineral Density in Middle-Aged Women
    • 7.12: Derivation of Selected Formulas
    • 7.13: Summary
    • 7: Problems (28)
    • 7: Labs (18)

  • Chapter 8: Hypothesis Testing: Two-Sample Inference
    • 8: Concept Explorations (5)
    • 8.1: Introduction
    • 8.2: The Paired t Test
    • 8.3: Interval Estimation for the Comparison of Means from Two Paired Samples
    • 8.4: Two-Sample t Test for Independent Samples with Equal Variances
    • 8.5: Interval Estimation for the Comparison of Means from Two Independent Samples (Equal Variance Case)
    • 8.6: Testing for the Equality of Two Variances
    • 8.7: Two-Sample t Test for Independent Samples with Unequal Variances
    • 8.8: Case Study: Effects of Lead Exposure on Neurologic and Psychological Function in Children
    • 8.9: Estimation of Sample Size and Power for Comparing Two Means
    • 8.10: The Treatment of Outliers
    • 8.11: Derivation of Equation 8.13
    • 8.12: Summary
    • 8: Problems (31)
    • 8: Labs (30)

  • Chapter 9: Nonparametric Methods
    • 9: Concept Explorations (3)
    • 9.1: Introduction
    • 9.2: The Sign Test
    • 9.3: The Wilcoxon Signed-Rank Test
    • 9.4: The Wilcoxon Rank-Sum Test
    • 9.5: Case Study: Effects of Lead Exposure on Neurological and Psychological Function in Children
    • 9.6: Permutation Tests
    • 9.7: Summary
    • 9: Problems (11)

  • Chapter 10: Hypothesis Testing: Categorical Data
    • 10: Concept Explorations (3)
    • 10.1: Introduction
    • 10.2: Two-Sample Test for Binomial Proportions
    • 10.3: Fisher's Exact Test
    • 10.4: Two-Sample Test for Binomial Proportions for Matched-Pair Data (McNemar's Test)
    • 10.5: Estimation of Sample Size and Power for Comparing Two Binomial Proportions
    • 10.6: R × C Contingency Tables
    • 10.7: Chi-Square Goodness-of-Fit Test
    • 10.8: The Kappa Statistic
    • 10.9: Derivation of Selected Formulas
    • 10.10: Summary
    • 10: Problems (24)
    • 10: Labs (6)

  • Chapter 11: Regression and Correlation Methods
    • 11: Concept Explorations (6)
    • 11.1: Introduction
    • 11.2: General Concepts
    • 11.3: Fitting Regression Lines—The Method of Least Squares
    • 11.4: Inferences About Parameters from Regression Lines
    • 11.5: Interval Estimation for Linear Regression
    • 11.6: Assessing the Goodness of Fit of Regression Lines
    • 11.7: The Correlation Coefficient
    • 11.8: Statistical Inference for Correlation Coefficients
    • 11.9: Multiple Regression
    • 11.10: Case Study: Effects of Lead Exposure on Neurologic and Psychological Function in Children
    • 11.11: Partial and Multiple Correlation
    • 11.12: Rank Correlation
    • 11.13: Interval Estimation for Rank-Correlation Coefficients
    • 11.14: Derivation of Equation 11.26
    • 11.15: Summary
    • 11: Problems (17)
    • 11: Labs (17)

  • Chapter 12: Multisample Inference
    • 12: Concept Explorations (3)
    • 12.1: Introduction to the One-Way Analysis of Variance
    • 12.2: One-Way ANOVA—Fixed-Effects Model
    • 12.3: Hypothesis Testing in One-Way ANOVA—Fixed-Effects Model
    • 12.4: Comparisons of Specific Groups in One-Way ANOVA
    • 12.5: Case Study: Effects of Lead Exposure on Neurologic and Psychological Function in Children
    • 12.6: Two-Way ANOVA
    • 12.7: The Kruskal-Wallis Test
    • 12.8: One-Way ANOVA—The Random-Effects Model
    • 12.9: The Intraclass Correlation Coefficient
    • 12.10: Mixed Models
    • 12.11: Derivation of Equation 12.30
    • 12.12: Summary
    • 12: Problems (19)
    • 12: Labs (9)

  • Chapter 13: Design and Analysis Techniques for Epidemiologic Studies
    • 13: Concept Explorations (3)
    • 13.1: Introduction
    • 13.2: Study Design
    • 13.3: Measures of Effect for Categorical Data
    • 13.4: Attributable Risk
    • 13.5: Confounding and Standardization
    • 13.6: Methods of Inference for Stratified Categorical Data—The Mantel-Haenszel Test
    • 13.7: Multiple Logistic Regression
    • 13.8: Extensions to Logistic Regression
    • 13.9: Sample Size Estimation for Logistic Regression
    • 13.10: Meta-Analysis
    • 13.11: Equivalence Studies
    • 13.12: The Cross-Over Design
    • 13.13: Clustered Binary Data
    • 13.14: Longitudinal Data Analysis
    • 13.15: Measurement-Error Methods
    • 13.16: Missing Data
    • 13.17: Derivation of 100% × (1 − α) CI for the Risk Difference
    • 13.18: Summary
    • 13: Problems (17)

  • Chapter 14: Hypothesis Testing: Person-Time Data
    • 14.1: Measure of Effect for Person-Time Data
    • 14.2: One-Sample Inference for Incidence-Rate Data
    • 14.3: Two-Sample Inference for Incidence-Rate Data
    • 14.4: Power and Sample-Size Estimation for Person-Time Data
    • 14.5: Inference for Stratified Person-Time Data
    • 14.6: Power and Sample-Size Estimation for Stratified Person-Time Data
    • 14.7: Testing for Trend: Incidence-Rate Data
    • 14.8: Introduction to Survival Analysis
    • 14.9: Estimation of Survival Curves: The Kaplan-Meier Estimator
    • 14.10: The Log-Rank Test
    • 14.11: The Proportional-Hazards Model
    • 14.12: Power and Sample-Size Estimation under the Proportional-Hazards Model
    • 14.13: Parametric Survival Analysis
    • 14.14: Parametric Regression Models for Survival Data
    • 14.15: Derivation of Selected Formulas
    • 14.16: Summary
    • 14: Problems (12)

  • Chapter PJT: Project
    • PJT.1: Project (4)


Bernard Rosner's Fundamentals of Biostatistics, Eighth edition, is a practical introduction to the methods, techniques, and computation of statistics with human subjects. It prepares students for their future courses and careers by introducing the statistical methods most often used in medical literature. Rosner minimizes the amount of mathematical formulation (algebra-based) while still giving complete explanations of all the important concepts. As in previous editions, a major strength of this book is that every new concept is developed systematically through completely worked out examples from current medical research problems. Most methods are illustrated with specific instructions as to implementation using software either from SAS, Stata, R, Excel or Minitab.

Coming Fall 2021!


Instructor Product Features

  • Instructor Resources include Concept Videos. These topic-specific videos provide explanations of key concepts, examples, and applications in a lecture-based format. Lecture PowerPoint slides and a full Instructor Solutions Manual are also available.

Student Learning Tools

  • Read It links under each question quickly jump to the corresponding section of a complete, interactive eBook that lets students highlight and take notes as they read.
  • Student Resources include Data Analysis Tool Instructions / Tech Guides for the below software. Can be used stand-alone or in conjunction with assessment items (Homework, Labs, or Project Milestones).
    • TI-83/84 and TI-Nspire Calculator
    • Excel
    • JMP
    • Minitab
    • SPSS
    • R

Questions to Help Students Gain Interest and Assess Conceptual Understanding

  • Stats in Practice Video Questions (SIP) show students how Statistics applies in the real world. Short and current news videos introduce each module. Each video is accompanied by multiple-choice and discussion questions, so that students can understand real-world context of what they're learning and stay engaged throughout the whole module.
  • Concept Video Questions (CV) provide students with a concept video along with two to three comprehension questions.
  • Select Your Scenario (SYS) problems provide students with 3 different contexts to choose from. They select the scenario most relevant to them, and then solve the problem. Regardless of which scenario the student chooses, they will be required to answer questions demonstrating knowledge of a learning objective, making them the perfect questions to assign toward the end of a chapter.

Tools to Explore Real Data with Technology

  • The Statistical Analysis and Learning Tool (SALT) is designed by statisticians, for statisticians, to help you get introductory students deeply engaged in data manipulation, analysis, and interpretation without getting bogged down in complex computations.
  • SALT Tutorial Questions (ST): Help your students understand how to use SALT in their WebAssign assignments. Students are provided with scaffolded instruction not only on the content, but how to use SALT to compute and analyze data.
  • Labs (Lab): Students can perform real statistical analysis in class or online with premade and module-specific Stats Labs. Require students to use the instructor-selected data analysis tool to analyze a real data set, pulling together knowledge learned from that module and previous material to facilitate whole-picture learning.
  • Project Milestones (PJT): Allow one place for students to ideate, collaborate, and submit a longer-term project. The four sequential milestones are:
    1. Research Design
    2. Gather Data
    3. Analyze Data
    4. Present Results


Questions Available within WebAssign

Most questions from this textbook are available in WebAssign. The online questions are identical to the textbook questions except for minor wording changes necessary for Web use. Whenever possible, variables, numbers, or words have been randomized so that each student receives a unique version of the question. This list is updated nightly.

Question Group Key
E - End of Chaper Exercise
SIP - Stats in Practice
CV - Concept Video
S - SALT
ST - SALT Tutorial
SYS - Select Your Scenario
Lab - Lab
PJT - Project Milestone


Question Availability Color Key
BLACK questions are available now
GRAY questions are under development


Group Quantity Questions
Chapter PJT: Project
PJT.1 4 001 002 003 004
Chapter 1: General Overview
1.CE 2 001.CV 001.SIP
Chapter 2: Descriptive Statistics
2.CE 4 001.CV 001.SIP 002.CV 003.CV
2.E 8 ST.001.S SYS.001.S 001-007.S 008-012 009 010 011 012 013-018.S 014 015 016 017 018 019-022 020 021 022 023-025.S 026-030 027 028 029 030 031-032.S 032 033-034 034 035-037.S 036 037 038-046 039 040 041 042 043 044 045 046 047-050 048 049 050
2.Lab 10 001.Excel 001.JMP 001.Minitab 001.R 001.SPSS 002.Excel 002.JMP 002.Minitab 002.R 002.SPSS
2.ST 2 001.S 002.S
Chapter 3: Probability
3.CE 4 001.CV 001.SIP 002.SIP 003.SIP
3.E 14 001-015 002 003 004 005 006 007 008 009 010 011 012 013 014 015 016-027 017 018 019 020 021 022 023 024 025 026 027 028-031 029 030 031 032-049 033 034 035 036 037 038 039 040 041 042 043 044 045 046 047 048 049 050-052 051 052 053-063 054 055 056 057 058 059 060 061 062 063 064-067 065 066 067 068-075 069 070 071 072 073 074 075 076-078 077 078 079-082 080 081 082 083-086 084 085 086 087-092 088 089 090 091 092 093-096 094 095 096 097-100 098 099 100 101-103 102 103 104-107 105 106 107 108-110 109 110 111-114 112 113 114 115-117 116 117 118-121 119 120 121 122-124 123 124 125-127 126 127 128-131 129 130 131 132-135 133 134 135 136-140 137 138 139 140 141-144 142 143 144
Chapter 4: Discrete Probability Distributions
4.CE 3 001.CV 001.SIP 002.SIP
4.E 21 001-004 002 003 004 005-006 006 007 008 009-010.S 010 011 012 013 014-022 015 016 017 018 019 020 021 022 023 024-029 025 026 027 028 029 030-032.S 031 032 033-037 034 035 036 037 038-041.S 039 040 041 042-047 043 044 045 046 047 048-050 049 050 051-052 052 053 054-058 055 056 057 058 059-063.S 060 061 062 063 064-066 065 066 067-070 068 069 070 071-073 072 073 074-079.S 075 076 077 078 079 080-082 081 082 083-085 084 085 086-088 087 088 089-091 090 091 092-095 093 094 095 096-098 097 098 099-100.S 100 101-103 102 103 104-106 105 106
4.Lab 5 001.Excel 001.JMP 001.Minitab 001.R 001.SPSS
4.ST 1 001.S
4.SYS 1 001.S
Chapter 5: Continuous Probability Distributions
5.CE 3 001.CV 001.SIP 002.CV
5.E 26 ST.001.S ST.002.S SYS.001.S SYS.002.S 001-005 002 003 004 005 006-009.S 007 008 009 010-011 011 012-013.S 013 014-016.S 017-020 018 019 020 021-024.S 022 023 024 025-030 026 027 028 029 030 031-035.S 032 033 034 035 036-041 037 038 039 040 041 042-044 043 044 045-046 046 047-049.S 048 049 050-052 051 052 053-057.S 054 055 056 057 058 059-061 060 061 062-064 063 064 065-067.S 066 067 068-070 069 070 071-074.S 072 073 074 075-077 076 077 078-079 079 080 081-085 082 083 084 085 086-088 087 088 089-091.S 090 091 092-094 093 094 095-098.S 096 097 098 099-101 100 101 102-105.S 103 104 105 106.S 107.S 108.S 109-112 110 111 112 113-116.S 114 115 116 117-119 118 119 120-122.S 121 122 123-125 124 125 126-130.S 127 128 129 130
5.ST 2 001.S 002.S
5.SYS 1 002.S
Chapter 6: Estimation
6.CE 7 001.CV 001.SIP 002.CV 002.SIP 003.CV 003.SIP 004.CV
6.E 21 ST.001.S SYS.001.S 001-004 005-010.S 011-017.S 018-022 023-024.S 025-026 027-029.S 030-032 033-035.S 036-039 040-046.S 047-051 052-055.S 056-058 059.S 060-063 064-066.S 067-069 070.S 071.S 072.S 073.S 074.S 075-076 077-080.S 081-083 084-085.S 086-087 088-096 097-101 102-103 104-107 108-109 110-116
6.Lab 34 001.Excel 001.JMP 001.Minitab 001.R 001.SPSS 001.TI 002.Excel 002.JMP 002.Minitab 002.R 002.SPSS 003.Excel 003.JMP 003.Minitab 003.R 003.SPSS 003.TI 004.Excel 004.JMP 004.Minitab 004.R 004.SPSS 005.Excel 005.JMP 005.Minitab 005.R 005.SPSS 005.TI 006.Excel 006.JMP 006.Minitab 006.R 006.SPSS 006.TI
Chapter 7: Hypothesis Testing: One-Sample Inference
7.CE 5 001.CV 001.SIP 002.CV 002.SIP 003.CV
7.E 28 ST.001.S ST.002.S ST.003.S SYS.001.S SYS.002.S SYS.003.S 001-005.S 006.S 007.S 008.S 009-011 012-016.S 017-020 021-022.S 023-024 025.S 026 027 028-029.S 030-034 035-042.S 043-047 048-051 052-055 056-059.S 060-064 065-066.S 067 068.S 069-071 072-074.S 075-078 079-080.S 081-085 086-089.S 090-092 093-095.S 096-097 098-100.S 101-104 105-107.S 108-109 110-113.S 114-118 119-121
7.Lab 18 001.Excel 001.JMP 001.Minitab 001.R 001.SPSS 001.TI 002.Excel 002.JMP 002.Minitab 002.R 002.SPSS 002.TI 003.Excel 003.JMP 003.Minitab 003.R 003.SPSS 003.TI
Chapter 8: Hypothesis Testing: Two-Sample Inference
8.CE 5 001.CV 001.SIP 002.CV 002.SIP 003.SIP
8.E 31 ST.001.S ST.002.S SYS.001.S SYS.002.S 001.S 002-018 019-022.S 023-024 025-027.S 028-030.S 031-038.S 039-043 044-047.S 048.S 049-052 053-055.S 056-061 062-065.S 066-069 070.S 071.S 072.S 073-074.S 075-076 077-080.S 081-084 085-087.S 088 089-093.S 094-098 099-102.S 103-105 106-109.S 110-114 115-116.S 117-120 121-124.S 125-128 129-133.S 134-135 136-138.S 139-141 142-145.S 146-149 150-153.S 154-157 158-160.S 161-163 164-167.S 168-172 173-176.S
8.Lab 30 001.Excel 001.JMP 001.Minitab 001.R 001.SPSS 001.TI 002.Excel 002.JMP 002.Minitab 002.R 002.SPSS 002.TI 003.Excel 003.JMP 003.Minitab 003.R 003.SPSS 003.TI 004.Excel 004.JMP 004.Minitab 004.R 004.SPSS 004.TI 005.Excel 005.JMP 005.Minitab 005.R 005.SPSS 005.TI
Chapter 9: Nonparametric Methods
9.CE 3 001.CV 001.SIP 002.CV
9.E 11 001-003.S 004-006.S 007-008 009-010.S 011-012 013-016.S 017-021 022-025.S 026-030 031.S 032-035 036-038.S 039-040 041.S 042-044 045-048.S 049-054 055-060.S 061-064 065-072.S 073-077
Chapter 10: Hypothesis Testing: Categorical Data
10.CE 3 001.CV 001.SIP 002.SIP
10.E 24 001-005.S 006-007 008-012 013.S 014 015.S 016 017-018.S 019-022.S 023-024.S 025-026 027-028.S 029-031 032-036.S 037-041 042-046.S 047-050 051-052.S 053-058 060-062 063-064.S 065-067 068-070.S 071-073 074-077.S 078-080 081-083.S 084-085 086-089.S 090-092 093-096.S 097-100 101-103.S 104-106 107-110.S 111-113 114-115.S 116-118 119-122.S 123-126 127-129.S 130-134 135-138.S 139-142 143-146.S 147-152
10.Lab 6 001.Excel 001.JMP 001.Minitab 001.R 001.SPSS 001.TI
10.ST 1 001.S
Chapter 11: Regression and Correlation Methods
11.CE 6 001.CV 001.SIP 002.CV 002.SIP 003.CV 003.SIP
11.E 17 001-007.S 008 009-012 013-018.S 019-024 025-030.S 031-033 034-035.S 036 037-038.S 039-043 044.S 045.S 046-048 049-053.S 054-059.S 060-063 064-071.S 072-076 077-078.S 079-084 085-088.S 089-091 092-095.S 096-099 100-102.S 103-106 107-111.S 112-113 114-117 118-121
11.Lab 17 001.Excel 001.JMP 001.Minitab 001.R 001.SPSS 001.TI 002.Excel 002.JMP 002.Minitab 002.R 002.SPSS 002.TI 003.Excel 003.JMP 003.Minitab 003.R 003.SPSS
Chapter 12: Multisample Inference
12.CE 3 001.CV 001.SIP 002.SIP
12.E 19 001-005.S 006-008.S 009-011.S 012-013.S 014-017 018-019.S 020-026 027.S 028.S 029.S 030.S 031-034 035-036.S 037-039 040-041.S 042-043 044-046.S 047-051 052-054.S 055 056-060.S 061 062 063 064-066.S 067-071 072-073 074-077 078-081.S 082-085 086-088.S
12.Lab 9 001.Excel 001.JMP 001.Minitab 001.R 001.SPSS 002.JMP 002.Minitab 002.R 002.SPSS
Chapter 13: Design and Analysis Techniques for Epidemiologic Studies
13.CE 3 001.SIP 002.SIP 003.SIP
13.E 17 001-007.S 008.S 009-014 015-018.S 019-023 024-025.S 026-028 030 032-033 034-035.S 036-038 039-042.S 043-046 047.S 049-054 055-061.S 062-064 065-067.S 068-072.S 073-076 077 080-084 085-087.S 088-092 093-098.S 099-100 101-105.S 106 107-108.S 109-110 111-114.S 115-117 118-121.S 122-125
Chapter 14: Hypothesis Testing: Person-Time Data
14.E 12 001-006.S 007-011 012 014 016-021.S 022-024 025-026.S 027-031 032-036.S 037-042 043-047.S 048-052 053-056.S 057-060.S 061-062.S 063-067 068-071.S 072-075 076-079.S 080-084
Total 441 (492)