Exploring the project/product initiation, success and failure and how it affect organization

Activity 1: Exploring the Logic of Experimental Design

This Activity asks you to demonstrate your understanding of fundamental concepts related to research design and apply them to creating designs and analyzing research.

Read:
Jackson, S. (2012): Chapters 8 and 9

Trochim W. M. K., & Donnelly, J. P. (2008): Chapter 7 & Pages 186-191

Brown, J. Scott. “Variable.” Encyclopedia of Research Design. 2010. SAGE Publications.

Pole, Jason D., and Susan J. Bondy. “Control Variables.” Encyclopedia of Research Design. 2010. SAGE Publications.

Kovera, Margaret Bull. “Confounding.” Encyclopedia of Research Design. 2010. SAGE Publications. 13 Aug. 2010.

Salkind, Neil J. “Dependent Variable.” Encyclopedia of Research Design. 2010. SAGE Publications.

Fan, Shihe. “Independent Variable.” Encyclopedia of Research Design. 2010. SAGE

Exploring the Logic of Experimental Design

Answer the following questions:
1. Jackson (2012) even-numbered Chapter Exercises (p. 244).
2. What is the purpose of conducting an experiment? How does an experimental design accomplish its purpose?
3. What are the advantages and disadvantages of an experimental design in an educational study?
4. What is more important in an experimental study, designing the study in order to make strong internal validity claims or strong external validity claims? Why?
5. In an experiment, what is a control? What is the purpose of a control group? Of single or multiple comparison groups?
6. What are confounds? Give an example of a design that has three confounds. Describe three ways to alter the design to address these confounds and explain the advantages and disadvantages of each.
7. What does ?cause? mean and why is it an important concept in research? How are correlation and causation related?
8. You are a researcher interested in addressing the question: does smiling cause mood to rise (i.e., become more positive)? Sketch between-participants, within-participants, and matched-participants designs that address this question and discuss the advantages and disadvantages of each to yielding data that help you answer the question. Describe and discuss each design in 4-5 sentences.

Your paper should demonstrate thoughtful consideration of the ideas and concepts that are presented in the course and provide new thoughts and insights relating directly to this topic. Your response should reflect scholarly writing and current APA standards.
Learning Outcomes: 1, 2

Evaluate the purpose of quantitative designs.
Critique quantitative designs.
Section 2: Inferential Statistics
Designs yield data, which in most cases (but not all) only have meaning once they are subjected to statistical analysis. Good sense (not to mention the necessity of doing an a priori power analysis to determine sample size, which requires you to specify your method of data analysis?see Activity 7) dictates that you plan your design and data analysis together in order to ensure that the data you worked so hard to gather will be able to answer your research questions and address your research problem.

Specific statistical tests are tied to specific designs and alterations in designs can require changes in analyses. Keep this in mind while you are writing your proposal: as you tweak your design, check that your analytical strategy is still appropriate. Knowledge of how a statistical test works can suggest changes to a design that will make the design more powerful (again, see Activity 9). The results of a pilot study, problems in implementing a design, or belated bright ideas may lead you to change or supplement your analysis, but you want to begin with an integrated design/analysis plan.

Indeed, to speak only of the interconnectedness of design and analysis is misleading: design, analysis, research questions, hypotheses, assumptions about or knowledge of sample characteristics, interpretations of findings, and even assumptions about the nature of causation and reality are interwoven! Your design should be an integrated whole in which all the parts make sense in relationship to each other, and you should understand all of the key assumptions you make in doing your study.

Important note:
While pilot studies can be extremely valuable, they must be conducted under the guidance of a faculty mentor. If human participants are involved, an approved Institutional Review Board (IRB) application must be on file before pilot data is collected. It is NEVER appropriate to conduct a pilot (or other) study without IRB approval.
Required Reading:
Trochim W. M. K., & Donnelly, J. P. (2008): Pages 293-308

Jackson, S. (2012): Chapters 8, 10

Schmidt, F. (2010). Detecting and Correcting the Lies That Data Tell. Perspectives on Psychological Science 5(3) 233-242. Retrieved from http://pps.sagepub.com.proxy1.ncu.edu/content/5/3/233.full.pdf+html [click ?Full Text (PDF) Free to you link? for PDF version]

Carver, R. P. (1978, August). The case against statistical significance testing. Harvard Educational Review, 48(3), 378-399.
Retrieved from http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.120.780&rep=rep1&type=pdf

CHAPTER 5 – The Importance of Effect Magnitude. In Blackwell Handbook of Research Methods in Experimental Psychology.
Retrieved from http://www.credoreference.com.proxy1.ncu.edu/entry/bkhrmep/chapter_5_the_importance_of_effect_magnitu

Activity 2: Exploring Inferential Statistics and Their Discontents
Exploring Inferential Statistics and Their Discontents

Part I
Part I of this Activity checks your understanding of key concepts from Jackson and Trochim & Donnelly.

Read:
Trochim W. M. K., & Donnelly, J. P. (2008): Pages 293-308

Jackson, S. (2012): Chapters 8, 10

Answer the following questions:
1. Jackson even-numbered Chapter exercises (pp. 220-221; 273-275)
2. What are degrees of freedom? How are the calculated?
3. What do inferential statistics allow you to infer?
4. What is the General Linear Model (GLM)? Why does it matter?
5. Compare and contrast parametric and nonparametric statistics. Why and in what types of cases would you use one over the other?
6. Why is it important to pay attention to the assumptions of the statistical test? What are your options if your dependent variable scores are not normally distributed?

Part II
Part II of this Activity introduces you to a debate in the field of education between those who support Null Hypothesis Significance Testing (NHST) and those who argue that NHST is poorly suited to most of the questions educators are interested in. Jackson (2012) and Trochim and Donnelly (2006) pretty much follow this model. Northcentral follows it. But, as the authors of the readings for Part II argue, using statistical analyses based on this model may yield very misleading results. You may or may not propose a study that uses alternative models of data analysis and presentation of findings (e.g., confidence intervals and effect sizes) or supplements NHST with another model. In any case, by learning about alternatives to NHST, you will better understand it and the culture of the field of education.

Read:
Schmidt, F. (2010). Detecting and correcting the lies that data tell. Perspectives on Psychological Science, 5(3) 233-242.

Carver, R. P. (1978, August). The case against statistical significance testing. Harvard Educational Review, 48(3), 378-399.

CHAPTER 5 – The Importance of Effect Magnitude. (2003). In Blackwell Handbook of Research Methods in Experimental Psychology.

Answer the following questions:
1. What does p = .05 mean? What are some misconceptions about the meaning of p =.05? Why are they wrong? Should all research adhere to the p = .05 standard for significance? Why or why not?
2. Compare and contrast the concepts of effect size and statistical significance.
3. What is the difference between a statistically significant result and a clinically or ?real world? significant result? Give examples of both.
4. What is NHST? Describe the assumptions of the model.
5. Describe and explain three criticisms of NHST.
6. Describe and explain two alternatives to NHST. What do their proponents consider to be their advantages?
7. Which type of analysis would best answer the research question you stated in Activity 1? Justify your answer.

Length:7 pages

Submit your document in the Course Work area below the Activity screen.

Learning Outcome: 3

Analyze the advantages, disadvantages, and alternatives to null hypothesis significance testing.
Section 3: Quantitative Designs
de Vaus (2001) identified two broad types of quantitative research designs?descriptive and explanatory. Research that contributes to theory, as your dissertation must, will almost definitely be explanatory. It will seek to address a why question. It will test hypotheses that will add to our understanding of how the world works. It will yield findings that cast light on a causal relationship?e.g., does a causal relationship exist between two phenomena? What are the mechanisms through which the cause achieves its effect? Your study will be, in the broad sense of the word, an experiment.

The most common type of quantitative designs are those addressed in this section: (true) experimental designs and quasi-experimental (including cross-sectional) designs. You can read about other types of experimental designs such as non-experimental (see Trochim?s socialresearchmethods.net) and longitudinal (which in some category schemes are types of experimental or quasi-experimental designs, but aren?t discussed here) on your own.

Required Reading:
Jackson, S. (2012): Chapters 11, 12

Trochim W. M. K., & Donnelly, J. P. (2008): Pp. 191- 207

CHAPTER 6 – Design and Analysis of Experimental and Quasi-Experimental Investigations. (2003). In Blackwell Handbook of Research Methods in Clinical Psychology.
http://www.credoreference.com.proxy1.ncu.edu/entry.do?id=5062770

Wiley, R. (2009). Trade-offs in the design of experiments. Journal of Comparative Psychology, 123(4), 447?449. Retrieved from http://www.unc.edu/home/rhwiley/pdfs/Wiley2009_tradeoffs.pdf

Goldberg, N. (1990). A quasi-experiment assessing the effectiveness of TV advertising directed to children. Journal of Marketing Research, 27, 445-454.
Retrieved from http://proquest.umi.com.proxy1.ncu.edu/pqdweb?did=585499&Fmt=6&clientId=52110&RQT=309&VName=PQ
Activity 3: Experimental Designs I
Experimental Designs I
Previous Activities introduced you to the logic of experiments and to simple experimental designs. This Activity and the next take you deeper into experimental designs. You will explore experimental designs with multiple levels of an independent variable and associated statistical analyses.

Read:
Jackson, S. (2012): Chapter 11

Trochim W. M. K., & Donnelly, J. P. (2008): Pages 185 – 191

Answer the following questions:
1. Jackson, even-numbered Chapter Exercises, pp. 308-310.
2. What is an F-ratio? Define all the technical terms in your answer.
3. What is error variance and how is it calculated?
4. Why would anyone ever want more than two (2) levels of an independent variable?
5. If you were doing a study to see if a treatment causes a significant effect, what would it mean if within groups variance was higher than between groups variance? If between groups variance was higher than within groups variance? Explain your answer
6. What is the purpose of a post-hoc test with analysis of variance?
7. What is probabilistic equivalence? Why is it important?

Include 3-5 peer-reviewed journal articles to support your responses.

Length:7 pages

Learning Outcome: 4

Develop experimental designs with multiple levels of an independent variable and associated statistical analyses.
Activity 4: Experimental Designs II
Experimental Designs II
Almost everything in research involves trade-offs between practical considerations and the likelihood of obtaining convincing results and trade-offs between competing design goals. Good research designs thread a course between avoiding Type I errors?(thinking you?ve found a difference or relationship that is not there) because you didn?t identify and control for confounds, used measures of the wrong constructs, or made one of dozens of other errors, oversights or miscalculations, and avoiding Type II errors?(not finding a relationship or difference that is there) because you didn?t have a design of sufficient sensitivity or didn?t identify a moderating variable in your sample, or made one of dozens of other errors, oversights or miscalculations!

True experiments are considered by many to be the gold standard of research designs. Their use of random assignment to conditions removes a great source of error and threats to validity. But even experiments involve calculations of costs and benefits, i.e., trade-offs in design, and are not always the best way to answer a research question. You should realize by now that all designs are made to order; none are off the rack! You must individually tailor a design to address your research questions, given your available time and resources. In addition, you must justify all of your decisions!

Read:
Jackson, S. (2012): Chapter 12

Trochim W. M. K., & Donnelly, J. P. (2008): Pages 191- 207

CHAPTER 6 – Design and Analysis of Experimental and Quasi-Experimental Investigations. (2003). In Blackwell Handbook of Research Methods in Clinical Psychology.

Wiley, R. (2009). Trade-offs in the design of experiments. Journal of Comparative Psychology, 123(4), 447?449.

Answer the following questions:
1. Jackson, even-numbered Chapter Exercises, pp. 335-337.
2. Explain the difference between multiple independent variables and multiple levels of independent variables. Which is better?
3. What is blocking and how does it reduce ?noise?? What is a disadvantage of blocking?
4. What is a factor? How can the use of factors benefit a design?
5. Explain main effects and interaction effects.
6. How does a covariate reduce noise?
7. Describe and explain three trade-offs present in experiments.

Include 3-5 peer-reviewed journal articles to support your responses.

Length:7 pages

Learning Outcomes: 5, 6

Compare and contrast aspects of experimental designs.
Evaluate experimental designs with multiple independent variables and associated statistical analyses.
Activity 5: Quasi-Experimental Designs (10 Points)
For reasons that will be clear after you?ve completed the readings for this Activity, if you do an experimental study for your dissertation, it will probably be a quasi-experiment. There are very good reasons why quasi-experimental designs are popular and a large literature on how they can be done well.

Part I
Read:

Jackson, S. (2012): Chapter 13

Trochim W. M. K., & Donnelly, J. P. (2008): Chapters 7, 10, and Pages 308-330

Answer the following questions:
1. Jackson (2012), even-numbered chapter exercises, p 360.
2. Describe the advantages and disadvantages of quasi-experiments? What is the fundamental weakness of a quasi-experimental design? Why is it a weakness? Does its weakness always matter?
3. If you randomly assign participants to groups, can you assume the groups are equivalent at the beginning of the study? At the end? Why or why not? If you cannot assume equivalence at either end, what can you do? Please explain.
4. Explain and give examples of how the particular outcomes of a study can suggest if a particular threat is likely to have been present.
5. Describe each of the following types of designs, explain its logic, and why the design does or does not address the selection threats discussed in Chapter 7 of Trochim and Donnelly (2006):
a. Non-equivalent control group pretest only
b. Non-equivalent control group pretest/posttest
c. Cross-sectional
d. Regression-Discontinuity
6. Why are quasi-experimental designs used more often than experimental designs?
7. One conclusion you might reach (hint) after completing the readings for this assignment is that there are no bad designs, only bad design choices (and implementations). State a research question for which a single-group post-test only design can yield relatively unambiguous findings.

Part II
Read:

Goldberg, N. (1990). A quasi-experiment assessing the effectiveness of TV advertising directed to children. Journal of Marketing Research, 27, 445-54.

Answer the following question:
1. What research question(s) does the study address?
2. What is Goldberg?s rationale for the study? Was the study designed to contribute to theory? Do the results of the study contribute to theory? For both questions: If so, how? If not, why not?
3. What constructs does the study address? How are they operationalized?
4. What are the independent and dependent variables in the study?
5. Name the type of design the researchers used.
6. What internal and external validity threats did the researchers address in their design? How did they address them? Are there threats they did not address? If so how does the failure to address the threats affect the researchers? interpretations of their findings? Are Goldberg?s conclusions convincing? Why or why not?

Include 3-5 peer-reviewed journal articles to support your responses to Part I.

Length:7 pages