Required Course Materials

Software:

All assignments must be submitted in Canvas.

Textbook:

Utts, J.M. (2014) Seeing Through Statistics, Duxbury Press, 4th Edition.

Textbook:

Lock, R. H., Frazer Lock, P., Lock Morgan, K., Lock, E. F., & Lock, D. F. (2017). Statistics: Unlocking the Power of Data (2nd Ed.). John Wiley & Sons. 

In addition to the textbook, students must have a WileyPLUS account to complete homework assignments and access to the statistical software Minitab Express.

ISBN: 9781119524052 includes access to the textbook online, WileyPlus, and a Minitab Express access code

A handheld calculator is required for the proctored exams (cell phones, tablets, and online calculators are not allowed). The TI30-XS Multiview is recommended, though any calculator with square root and memory functions is sufficient. Contact your instructor if you have any questions concerning calculators.

Software:

Students must have immediate access to a printer/scanner in order to scan hand written assignments into .pdf documents and upload them into Canvas.

Textbook:

Akritas, M., (2015). Probability & Statistics with R for Engineers and Scientists, 1st edition, Pearson, ISBN-13: 978-0321852991.

Software:

Students must have immediate access to a printer/scanner in order to scan hand written assignments into .pdf documents and upload them into Canvas.

Textbook:

Hogg, R.V., and Tanis, E.A. (2020). Probability and Statistical Inference, 10th Edition, Pearson. ISBN-978-0135189399(We will primarily cover chapters 1-5.)

Note: This is NOT the global edition.

*10th adopted for SU19

Updated for SU19
Software:

Students must have immediate access to a printer/scanner in order to scan hand written assignments into .pdf documents and upload them into Canvas.

Access to the Minitab 17 statistical software package. (Although you will actually be allowed to use any of the other mainstream statistical packages, such as SAS, SPSS, and R, the methods in the course will be demonstrated only using Minitab.) See the Statisitical Software page for more information.

Textbook:

Hogg, R.V., and Tanis, E.A. (2020). Probability and Statistical Inference, 10th Edition, Pearson. ISBN-978-0135189399: We will primarily cover chapters 6-10.

Note: This is NOT the global edition.

*10th adopted for SU19

Updated for SU19
Software:

This course will use the statistical software program SAS. See the Statistical Software page for more information.

Textbook:

A.Dean and D. Voss. (1999), Design and Analysis of Experiments. ISBN-13: 978-1475772920 (available for free download from the PSU Library website)

Applied Linear Statistical Models by Kutner, Nachtsheim, Neter, and Li, 5th Edition. (this text is recommended as a reference, but not required).

Software:

Students will use their choice of  statistical software programs R or Minitab in this course. See the Statistical Software page for more information.

Textbook:

Pardoe, I. (2012). Applied Regression Modeling, 2nd Edition, Wiley. ISBN: 978-1-118-09728-1 (or E-Text: 978-1-119-09428-9 or E-Book: 978-1-118-34504-7). See https://www.iainpardoe.com/arm2e/.

Software:

This course will use the statistical software program Minitab or R. See the Statistical Software page for more information.

Textbook:

Higgins, Jame V. (2003). Introduction to Modern Nonparametric Statistics. 1st Edition, Duxbury Press. ISBN-10: 0534387756.

Software:
  • Access to a Windows PC that has internet access, SAS, and Microsoft Word
  • Access to your own copy of SAS. SAS 9.1.3, SAS 9.2 or SAS 9.3. Please make sure that you visit Statistical Software page for the latest information about SAS.
Textbook:

Recommended Texts

Delwiche, Lora D. (2013), The Little SAS Book: Primer, Fifth Edition. Cary, NC: SAS Publishing. ISBN 13: 978-1-61290-343-9 ISBN 10: 1-61290-343-6

Cody, Ronald P. and Jeffrey K. Smith (2006), Applied Statistics and the SAS Programming Language, Fifth Edition, Upper Saddle River, NJ: Pearson Prentice Hall. ISBN 0-13-146532-5

SAS Institute Inc. (2011), SAS Certification Prep Guide: Base Programming for SAS 9, 3rd Edition, Cary, NC: SAS Institute, Inc. ISBN 978-1607649243 (w/ CD).

Software:
  • Access to a Windows PC that has internet access, SAS, and Microsoft Word
  • Access to your own copy of SAS. SAS 9.1.3, SAS 9.2 or SAS 9.3. Please make sure that you visit Statistical Software page for the latest information about SAS.
Textbook:

Recommended Texts

Delwiche, Lora D. (2013), The Little SAS Book: Primer, Fifth Edition. Cary, NC: SAS Publishing. ISBN 13: 978-1-61290-343-9 ISBN 10: 1-61290-343-6

Cody, Ronald P. and Jeffrey K. Smith (2006), Applied Statistics and the SAS Programming Language, Fifth Edition, Upper Saddle River, NJ: Pearson Prentice Hall. ISBN 0-13-146532-5

SAS Institute Inc. (2011), SAS Certification Prep Guide: Base Programming for SAS 9, 3rd Edition, Cary, NC: SAS Institute, Inc. ISBN 978-1607649243 (w/ CD).

Software:
  • Access to a Windows PC that has internet access, SAS, and Microsoft Word
  • Access to your own copy of SAS. SAS 9.1.3, SAS 9.2 or SAS 9.3. Please make sure that you visit Statistical Software page for the latest information about SAS.
Textbook:

Cody, Ronald P. and Jeffrey K. Smith (2006), Applied Statistics and the SAS Programming Language, Fifth Edition, Upper Saddle River, NJ: Pearson Prentice Hall. ISBN 0-13-146532-5

Software:
  • Access to your own copy of R. Please make sure that you visit Statistical Software page for the latest information about R.
  • RStudio is a very nice platform for using R that will run on Windows, Mac, and Linux. R studio adds many useful features to simplify using R. All the functions used in this class can be performed without RStudio, but I will be demonstrating their use within RStudio.
Textbook:

Text: We will make extensive use of Essential R – the course notes for this class. You should download it and will probably find it useful to print it. You may also want to download additional resources in the compressed folder Essential R.zip.

Other Books and Resources on R:

Statistics: An introduction using R. 2005. Michael J. Crawley. Wiley and Sons. (This was useful enough to me when I began learning R that I bought a copy.).

Using R for Introductory Statistics. 2004. John Verzani. Chapman & Hall/CRC. (An extension of SimpleR) https://www.crcpress.com. If I was going to require a text, this would be it.

Software:
  • Access to your own copy of R. Please make sure that you visit Statistical Software page for the latest information about R.
  • RStudio is a very nice platform for using R that will run on Windows, Mac, and Linux. R studio adds many useful features to simplify using R. All the functions used in this class can be performed without RStudio, but I will be demonstrating their use within RStudio.
Textbook:

Text: We will make extensive use of Essential R – the course notes for this class. You should download it and will probably find it useful to print it. You may also want to download additional resources in the compressed folder Essential R.zip.

Other Books and Resources on R:

Statistics: An introduction using R. 2005. Michael J. Crawley. Wiley and Sons. (This was useful enough to me when I began learning R that I bought a copy.).

Using R for Introductory Statistics. 2004. John Verzani. Chapman & Hall/CRC. (An extension of SimpleR) https://www.crcpress.com. If I was going to require a text, this would be it.

Software:

This course will use the statistical software program Minitab. See the Statisitical Software page for more information.

A graphing calculator is recommended for this course, especially for students enrolled or considering the MAS program. Otherwise, a basic calculator that includes factorials and combinations will suffice. Please note that for the final exam using a calculator on a device with internet capabilities (e.g. cell phone) will NOT be permitted.

Textbook:

Ott, R. L. and Longnecker, M. (2016).  An Introduction to Statistical Methods and Data Analysis, 7th Edition, Cengage Learning.

ISBN 13: 978-1-305-26947-7,  ISBN 10: 1-305-26947-0

Software:

This course uses Minitab statistical software. Students can use any software they wish for assignments, but most will find it easiest to use Minitab. Plus, examples for the course units will be demonstrated using Minitab. See the Statistical Software page for more information about obtaining a copy of Minitab.

Textbook:

The textbook is required, and either of the two editions below are acceptable.  Here are the two options for the required textbook for this course. Students may use either:

The larger Applied Linear Statistical Models by Kutner, Nachtsheim, and Neter (5th edition) OR the smaller Applied Linear Regression Models by the same authors, Kutner, Nachtsheim, and Neter (4th edition).

The first half of the larger Applied Linear Statistical Models contains sections on regression models, the second half on analysis of variance and experimental design. This first half of the 5th edition text is available published as Applied Linear Regression Models by Kutner, Nachtsheim, and Neter (4th edition).

Students may use either textbook listed as they are identical.

The larger Applied Linear Statistical Models also includes 16 chapters on analysis of variance and experimental design not covered in this course, however these topics are covered in STAT 502 where these chapters are required. Students may consider purchasing the larger text if they are taking both courses. Applied Linear Statistical Models is considered to be one of the "bibles" of applied statistics so it probably will have value to you beyond this course.

Software:

Students will use both SAS and Minitab. If you are taking additional upper level STAT courses we recommend that you purchase a permanent license for Minitab. See the Statisitical Software page for more information about accessing these applications.  PLEASE NOTE: The Minitab v. 14 Student Version does not have full statistical functionality and is not recommended for STAT courses.

Minitab and SAS will be supported. Sample programs will be supplied but students will be required to do some programing on their own. Students should already feel comfortable using either Minitab and SAS, or be a quick learner of software packages, or be able to figure out how to do the required analyses in another package of their choice. Due to different software versions and platforms there may be issues with running a code. Students should NOT wait to the point of frustration but must be proactive in seeking advice and help from appropriate sources including documentation resources, other students via the online discussion boards, the teaching assistant, instructor or helpdesk.

Students who have no experience with programming or are anxious about being able to manipulate software code are strongly encouraged to take the one-credit course in SAS in order to establish this foundation before taking STAT 502.

Textbook:

There are two options of textbooks for this course. Students may use either:

The larger Applied Linear Statistical Models by Kutner, Nachtsheim, and Neter (5th edition) OR the smaller Analysis of Variance, a custom printing of the second half of the larger text (ISBN-97811216693-76).

Students may use either textbook listed.

The first half of the larger Applied Linear Statistical Models contains sections on regression models, the second half on analysis of variance and experimental design. The first 12 chapters on regression models are not covered in STAT 502, however these topics are covered in STAT 501 where these chapters are required. Students may consider purchasing the larger text if they are taking both courses. Applied Linear Statistical Models is considered to be one of the "bibles" of applied statistics so it probably will have value to you beyond this course.

Software:

This course will use the statistical software program Minitab. See the Statistical Software page for more information.

For most assignments the Minitab GLM or SAS Proc GLM and Proc Mixed commands will satisfy the computing requirements. Minitab Design Of Experiments (DOE) commands are also utilized extensively.

Students should already feel comfortable using SAS at a basic level, be a quick learner of software packages, or able to figure out how to do the required analyses in another package of their choice. Students who have no experience with programming or are anxious about being able to manipulate software code are strongly encouraged to take the one-credit courses in SAS in order to establish this foundation before taking courses that rely on this software.

SAS will be supported and sample programs will be supplied but you will be required to do some programing on your own. Due to different software applications, software versions and platforms there may be issues with running code. Students must be proactive in seeking advice and help from appropriate sources including documentation resources, other students, the teaching assistant, instructor or helpdesk.

Textbook:

Montgomery, D. C. (2019). Design and Analysis of Experiments, 10th Edition, John Wiley & Sons.

Software:

SAS (https://www.sas.com/), and/or R (https://www.cran.rproject.org/) are used in this course. You do not need both. See the Statistical Software page  for more information about acquiring a copy of these applications.

SAS and R will be supported. Sample programs will be supplied but students will be required to do some programing on their own. Students should already feel comfortable using either SAS or R, or be a quick learner of software packages, or be able to figure out how to do the required analyses in another package of their choice. Due to different software versions and platforms there may be issues with running a code. Students should NOT wait to the point of frustration but must be proactive in seeking advice and help from appropriate sources including documentation resources, other students via the online discussion boards, the teaching assistant, instructor or helpdesk.  Students who have no experience with programming or are anxious about being able to manipulate software code are strongly encouraged to take the one-credit courses in either SAS or R in order to establish this foundation before taking STAT 504.

Textbook:

Agresti, A. (2013). Categorical Data Analysis, 3rd Edition, Wiley.

This is the new and improved text of Agresti (1996). It is less theoretical and therefore less technical than Agresti (2002). Students are free to purchase either 2007 or 2002 text for this course. References are provided in the lesson materials for both texts.

Software:

SAS is the recommended software and shall be used for all in-class demonstrations of statistical analyses, homework assignments, and exams. See the Statisitical Software page for more information.

SAS will be supported and sample programs will be supplied but you will be required to do some programing on your own. Due to different software applications, software versions and platforms there may be issues with running code. Students must be proactive in seeking advice and help from appropriate sources including documentation resources, other students, the teaching assistant, instructor or helpdesk.

Statistical software SAS involves programming.  Students should already feel comfortable using SAS at a basic level, be a quick learner of software packages, or able to figure out how to do the required analyses in another package of their choice. Students who have no experience with programming or are anxious about being able to manipulate software code are strongly encouraged to take the one-credit course in SAS in order to establish this foundation before taking STAT 505.

Textbook:

Johnson, R.A., and Wichern, D.W. (2007). Applied Multivariate Statistical Analysis. 6th ed. Prentice Hall, New York.

Software:

Students will need to use software to generate random numbers. This can be accomplished by using a statistical software package such as Minitab, SAS or R. See the Statistical Software page for details regarding these applications.

Textbook:

Required: Sampling, 3rd.ed., by Steven K. Thompson, John Wiley and Sons, 2012.

Optional: Elementary Survey Sampling, 6th.or 7th ed., by R. Scheaffer, W. Mendenhall III, R. L. Ott, Duxbury Press, 2005.

Software:

Students will need to use software to calculate basic epidemiologic measures. This can be accomplished using a statistical software package such as SAS, R, Epiinfo, or Minitab. See the Statistical Software page for information regarding these applications.

Textbook:

Recommended Texts

Readings from the literature will supplement the following texts:

Epidemiology: Study the occurrence of disease. (2002) by Thomas Koepsell and Noel Weiss. ISBN 0-19-515078-3, Oxford University Press, New York, New York.

Epidemiology: Study design and data analysis. (2005) by Mark Woodward. Published by Chapman and Hall/CRC.

Software:

The examples in the course use R and students will do weekly R Labs to apply statistical learning methods to real-world data. Extensive guidance in using R will be provided, but previous basic programming skills in R or exposure to a programming language such as MATLAB or Python will be useful.

R involves programming. Students should already feel comfortable using R at a basic level, be a quick learner of software packages, or able to figure out how to do the required analyses in another package of their choice. Students who have no experience with programming or are anxious about being able to manipulate software code are strongly encouraged to take the one-credit course in R in order to establish this foundation before taking this course. 

R will be supported and sample programs will be supplied but you will be required to do some programing on your own. Due to different software applications, software versions and platforms there may be issues with running code. Students must be proactive in seeking advice and help from appropriate sources including documentation resources, other students, the teaching assistant, instructor or helpdesk.

Textbook:

An Introduction to Statistical Learning: with Applications in R, By James, G., Witten, D., Hastie, T., Tibshirani, R.  Springer, 2013.

Software:

In order to take this course, you need:

  • access to a Windows PC that has internet access, SAS, and Microsoft Word
Textbook:

The required textbook for this course is:

Friedman, Lawrence M. (2010). Fundamentals of Clinical Trials. 5th Edition, Springer. ISBN: 9783319185385

Software:

This course makes extensive use of the R Statistical Software. This is open-source free software that can be downloaded from the R Project home page. For more information and links to download this software please see the Statistical Software page. MS Word is also required.

R involves programming. Students should already feel comfortable using R at a basic level, be a quick learner of software packages, or able to figure out how to do the required analyses in another package of their choice. Students who have no experience with programming or are anxious about being able to manipulate software code are strongly encouraged to take the one-credit course in R in order to establish this foundation before taking STAT 510. 

R will be supported and sample programs will be supplied but you will be required to do some programing on your own. Due to different software applications, software versions and platforms there may be issues with running code. Students must be proactive in seeking advice and help from appropriate sources including documentation resources, other students, the teaching assistant, instructor or helpdesk.

Textbook:

Shumway R.H., Stoffer, D.S. (2012). Time Series Analysis and Its Applications With R Examples, 4th Edition, Springer. ISBN-978-3-319-52451-1

(The text is required, though students do not have to purchase it because it is available electronically through the Penn State library.)

Software:

This course makes extensive use if the R statistical software. See the Department of Statistics' Statistical Software page for information about obtaining a copy of R.

Textbook:

There will be no required text-book. Online course materials will combine methodological background description and presentation of analyses and results from recent articles. References and notes will be posted.

Software:

In STAT 580 SAS is the software that shall be used for all in-class demonstrations of statistical analyses, assignments, and projects. You will need to have access to your own copy of SAS, (SAS 9.1.3, SAS 9.2 or SAS 9.3) Please make sure that you visit Statistical Software page for the latest information about SAS.

Textbook:

Cabrera, J. and McDougal, A. 2002. Statistical Consulting. Springer: New York. (Required for STAT 580)

Software:

In STAT 581 students may use the statistical software that they prefer.

Textbook:

Cabrera, J. and McDougal, A. 2002. Statistical Consulting. Springer: New York.

Software:

Either Minitab 14 Student Version or Minitab 15 and up. Mac users may use SPSS. See the Statistical Software page for more details about these applications. Students wishing to use SAS, R, JUMP, etc. will not have support available through the course.

Textbook:

(Starting SU18) Agresti, Franklin & Klingenberg. (2017). Statistics: The Art and Science of Learning From Data, 4thEdition, Pearson. ISBN-9780321997838