Science 480: Research Methods in Science

Course Orientation

Course Objectives

SCIE 480: Research Methods in Science is intended to introduce undergraduate students to the practice of scientific research in the 21st century and the theories underlying it. To that end, the course opens with a broad‑based, cross‑disciplinary discussion of current designs and methods used by researchers in various fields of endeavour. While scientific thinking has been perceived by some as rigorous and undaunted by the vagaries of opinion, you will learn that science is self‑correcting and open‑ended in its very nature.

The course covers a wide range of conceptual and technical aspects of research methods:

  • the logic and the nature of the scientific method.
  • the art and the science of sampling and data collection.
  • a review of research designs.
  • details of quantitative and qualitative approaches to presentation of data and hypothesis testing.
  • the importance of mathematical modelling in scientific research.
  • the meaning of reliability and validity in scientific circles.
  • research ethics.
  • the importance of health and safety in the lab and in the field.
  • the how of scientific communication and research dissemination.

Key concepts of statistical analysis and mathematical modelling will be introduced, including an examination of how these concepts relate to the scientific method and are used in a surprising number of research processes.

Moreover, by taking this course you will gain first‑hand experience with the design and writing of a research proposal, a literature search and a review, as well as the collection, display, and analysis of scientific data.

The Structure of Your Course

SCIE 480 is divided into four units, which discuss various empirical research designs and experiments for both qualitative and quantitative data.

Unit 1:  The Nature of Science

This unit covers scientific reasoning and introduces students to the scientific method. Unit 1 describes the unique approach that science takes to understand the universe.

Unit 2:  Statistics

This unit is a natural follow‑up to the discussions in Unit 1 on the hypothesis testing involved in certain research experimental designs. Unit 2 focuses on the role of statistical methods used for the analysis of both qualitative and quantitative data collected in these kinds of experiments.

The expectation is that students already have a relatively solid background in introductory descriptive and inferential statistical methods.

Unit 3:  Mathematical Modelling

This unit provides a brief introduction to mathematical modelling, with particular emphasis on simple deterministic models derived with the use of difference equations and differential equations. The mathematical background needed for this unit is simple Algebra and basic knowledge of Calculus.

Unit 4:  Writing a Research Proposal and Presenting Your Results

This unit discusses the design, the structure, and the necessary ingredients of a good research proposal—one of the first formal processes any scientist should articulate before embarking on the research itself. How this report is presented can mean the difference between receiving, or not receiving, funding for your project or experiment. Moreover, Unit 4 provides the opportunity for a scientist to take a birds‑eye view of the entire research process with provisions for gathering, analyzing, and presenting the data pertinent to the writing of the final scientific paper.

Learning Outcomes

Upon successful completion of this course, you will be able to

  • demonstrate understanding of the different types of research and the ethical principles that must be followed if human or animals are involved.
  • carry out a literature review on a specific scientific topic by using library and online resources to look for relevant scientific papers ranging from popular scientific journals to more technical specialist journals.
  • differentiate between a null hypothesis and a research or alternative hypothesis, between random and systematic errors, and between accuracy and precision.
  • provide reasons for including statistical methods, both descriptive and inferential, in data-driven research, and explain the importance of measurements, their accuracy and their significance.
  • explain the relevance of mathematical modelling in science and demonstrate understanding of the description and prediction aspects of a mathematical model.
  • apply linear regression and basic nonlinear discrete and differential equation models to sets of experimental data using Excel.
  • describe the general structure of scientific articles and use this knowledge to write a research proposal.

Course Materials

The course is taught using a digital textbook (eBook), other online materials, and academic support.

Textbook: Marder, M. P. (2011.) Research Methods for Science. New York, NY: Cambridge University Press.

Online Course Materials: this Course Orientation, the Study Guide and access to the following scientific research papers:

Norvig, P. (n.d.). Warning Signs in Experimental Design and Interpretation. (Unit 1)

Busquets, J. et al. (2007). Liver Transplantation Across Rh Blood Group Barriers Increases the Risk of Biliary Complications. Journal of Gastrointestinal Surgery. (Unit 2)

Snider, S.B. & Brimlow, J.N. (2013). An Introduction to Population Growth. Nature Education Knowledge 4(4):3. (Unit 3)

Vandermeer, J. (2010). How Populations Grow: The Exponential and Logistic Equations. Nature Education Knowledge 3(10):15. (Unit 3)

Online Maple TA Study Session

Unit 2 includes an Online Maple TA Study Sessions for your self‑assessments. These self‑assessments are designed to provide a review of introductory statistical concepts, terminology, and some methods of data analysis, both descriptive and inferential. Each session may be studied an unlimited number of times. The results of each attempt are NOT recorded.

Note: The Unit 2 online quiz (Assignment 2, part III) is based on a selection of questions from the Maple TA Study Session site throughout unit 2.

How to access Maple TA Study Session site

The Maple TA Study Session site needs separate credentials for access. To be registered in this third party tool, please contact Julie Peschke (juliep@athabascau.ca) and request access to the SCIE 480 self‑assessment study sessions by supplying a) your first and last names, b) your AU student ID number and c) the name of the course.

Technology

Students enrolled in SCIE 480 must have access to Microsoft Excel spreadsheet software.

In Unit 2: Statistics, you have the option to work with Microsoft Excel as a data analysis tool.

In Unit 3: Mathematical Modelling, you will be expected to use Microsoft Excel to do linear regression analysis and carry out a nonlinear fitting of the solutions of linear and logistic differential equations on a set of experimental data.

Suggested Study Schedule

SCIE 480 is a three‑credit (one‑semester) course designed to be completed in about 25 weeks. Students are permitted to take up to six months, but we recommend following the 25‑week schedule suggested below, thereby keeping some time in reserve for unexpected delays or emergencies.

If you decide to follow the suggested study schedule, you should have no difficulty completing the course within your six‑month contract. If you find yourself falling behind, contact your academic expert to discuss the situation. You may also extend your course contract. However, there is a fee for this and you are required to apply for such extensions at least one month before your course end date. You may, of course, proceed more quickly than this schedule is suggests.

Note: Students receiving financial assistance may face more rigorous time constraints. Please check your course registration for any restrictions on the length of registration, and be prepared to adjust your schedule accordingly.

Week Activity

1

Read the Student Manual and this Course Orientation carefully and look over the other course materials.

Contact your academic expert to introduce yourself.

Set up your study plan.

In the Study Guide, read the introductory section of Unit 1, “The Nature of Science.”

2

Read Unit Section 1.1 Types of research and 1.2 How to find literature resources.

Familiarize yourself with AU library resources.

Participate in the A1‑I discussion forum (part I of Assignment1) for credit.

3

Read Unit Section 1.3 How to read scientific papers and 1.4 Research hypothesis and null hypothesis, Type I and II errors.

4

Read Unit Section 1.5 Random and systematic errors, accuracy and precision, bias and 1.6 Research involving humans and animals.

Final deadline for the Discussion Forum.

Submit the other two parts of Assignment 1 using the respective assignment dropbox on the course homepage.

5

Read and study Unit Sections 2.1: Motivations for Statistics. and 2.2: Reducing many numbers to few.

Prepare a draft version for the Assignment 2‑I Discussion.

Work through the Online Maple TA Study Sessions ‑‑ Using Statistical Analysis in Research, Organizing and Graphing Data and Numerical Descriptive Measures: statistical number crunching.

6

Read and study Unit Sections 2.3: Probability distributions and 2.4: Connecting data and probability distributions.

Finalize and post your answer in the Assignment 2‑I Discussion Forum on the course homepage.

Work through the Online TA Study Sessions:
Calculating Probabilities: Basic Definitions and Rules,
Probability Distributions of Discrete Random Variables,
Discrete Probability Distributions: The binomial distribution and
Probability Distributions of Continuous Random Variables.

7

Read and study Unit Section 2.5: What happens to sample averages as the sample size (N) increases.

Work through the Online Maple TA Study Session:
Sampling Distributions: On the road to hypothesis testing.

8

Read and study Unit Section 2.6: The Central Limit Theorem.

Work through the Online Maple TA Study Session:
Hypothesis Testing for ONE population.

9

Read and study Unit Sections 2.7 Comparing many samples.

Work through the Online Maple TA Study Session:
Hypothesis Testing for TWO Populations.

10

Read and study Unit Section 2.8: Data with categorical variables and 2.9: Other statistical tests.

Work through the Online Maple TA Study Session:
The Chi‑squared Tests: for categorical data, and
REVIEW: Choosing the Right Statistical Test

11

Work through Assignment 2‑II: Statistical Analysis of a Research Paper. If you have completed the Online Maple TA Study Sessions, you should have an understanding of the statistical terminology and processes this written exercise requires. It must be submitted before your course end date.

When you are ready, complete the Unit 2 ONLINE QUIZ (Assignment 2‑III). It too must be submitted before your course end date. However, it is probably easier to do when the material is fresh in your memory.

12

Study the introduction to Unit 3 and Sections 3.1: Basic mathematical ingredients for modelling.

13

Study Sections 3.2: Linear Regression.

14

Study the first part of Sections 3.3: Difference Equations (iterative maps) (up to The Discrete Linear and Logistic Models: An application).

Start studying the second part of Sections 3.3: The Discrete Linear and Logistic Models: An application.

15

Finish studying the second part of Sections 3.3: The Discrete Linear and Logistic Models: An application.

16

Study the first part of Sections 3.4: Differential Equations (up to The Discrete Linear and Logistic Models: An application).

Start studying the second part of Sections 3.4: The Continuous Linear Model: An application.

17

Finish studying the second part of Sections 3.4: The Continuous Linear Model: An application.

Start working on Assignment 3.

18

Finish working on Assignment 3 and submit it.

19

Read and study Unit Section 4.1 Writing Scientific papers.

If you haven’t already done so, begin Assignment 4 by selecting a topic for your research proposal in close consultation with your academic expert.

Read and study section 4.4 Designing and writing a research proposal.

Start writing a draft of your research proposal.

20

Study Unit Section 4.2 Producing scientific figures.

Continue working on your research proposal draft.

21

Study Unit Section 4.3 Giving scientific presentations. Continue working on your research proposal draft.

22

If you haven’t already done so, submit your research proposal.

23

Using the feedback that you received for your proposal draft, write the final research proposal.

24

Continue writing the final research proposal.

25

Submit Assignment 4.

Student Evaluation

To receive credit for SCIE 480, you must achieve a mark of at least 50 per cent on the assignments for Units 1, 2, and 3 as a collective composite grade and a grade of at least 50% on the assignment for Unit 4.

Assignment 1:

Part‑I: Discussion
Part‑II: Short Answer Questions
Part‑III: Summary

Total: 25% of final grade

Assignment 2:

Part‑I: Discussion
Part‑II: Written Exercise
Part‑III: Online Quiz

Total: 25% of final grade

Assignment 3:

Part‑I: Problem Solving
Part‑II: Summary

Total: 25% of final grade

Assignment 4:

Part‑I: Draft Research Proposal
Part‑II: Final Research Proposal

Total: 25% of final grade

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