As a scholar-practitioner, it is important for you to understand that just because a hypothesis test indicates a relationship exists between an intervention and an outcome, there is a difference between groups, or there is a correlation between two constructs, it does not always provide a default measure for its importance. Although relationships are significant, they can be very minute relationships, very small differences, or very weak correlations. In the end, we need to ask whether the relationships or differences observed are large enough that we should make some practical change in policy or practice.

For this Discussion, you will explore statistical significance and meaningfulness.

To prepare for this Discussion:

• Review the Learning Resources related to hypothesis testing,      meaningfulness, and statistical significance.
• Review Magnusson’s web blog found in the Learning Resources to      further your visualization and understanding of statistical power and      significance testing.
• Review the American Statistical Association’s press release and      consider the misconceptions and misuse of p-values.2

   

   

   

   

   

   

  8210 Week 5 Discussion:

  Statistical Significance and Meaningfulness

  Once you start to understand how exciting the world of statistics can be, it is tempting to fall into the trap of chasing statistical significance. That is, you may be tempted always to look for relationships that are statistically significant and believe they are valuable solely because of their significance. Although statistical hypothesis testing does help you evaluate claims, it is important to understand the limitations of statistical significance and to interpret the results within the context of the research and its pragmatic, “real world” application.

  As a scholar-practitioner, it is important for you to understand that just because a hypothesis test indicates a relationship exists between an intervention and an outcome, there is a difference between groups, or there is a correlation between two constructs, it does not always provide a default measure for its importance. Although relationships are significant, they can be very minute relationships, very small differences, or very weak correlations. In the end, we need to ask whether the relationships or differences observed are large enough that we should make some practical change in policy or practice.

   

  For this Discussion, you will explore statistical significance and meaningfulness.

   

  To prepare for this Discussion:

  · Review the Learning Resources related to hypothesis testing, meaningfulness, and statistical significance.

  · Review Magnusson’s web blog found in the Learning Resources to further your visualization and understanding of statistical power and significance testing.

  · Review the American Statistical Association’s press release and consider the misconceptions and misuse of p-values.

  · Consider the scenario:

  · A research paper claims a meaningful contribution to the literature based on finding statistically significant relationships between predictor and response variables. In the footnotes, you see the following statement, “given this research was exploratory in nature, traditional levels of significance to reject the null hypotheses were relaxed to the .10 level.”

  Assignment Task Part 1

   

  Post your response to the scenario in 200 words in which you critically evaluate this footnote. As a reader/reviewer, what response would you provide to the authors about this footnote?

   

  Assignment Task 2

  Respond to one of your colleagues’ posts in 125 words and explain the benefits and consequences of the “relaxed” level of significance.

   

   

   

   

   

   

   

   

   

   

   

   

   

   

   

   

   

   

   

   

   

   

  Learning Resources

  Required Readings

  Frankfort-Nachmias, C., Leon-Guerrero, A., & Davis, G. (2020). Social statistics for a diverse society (9th ed.). Thousand Oaks, CA: Sage Publications.

  · Chapter 8, “Testing Hypothesis: Assumptions of Statistical Hypothesis Testing” (pp. 241-242)

  Wagner, III, W. E. (2020). Using IBM® SPSS® statistics for research methods and social science statistics (7th ed.). Thousand Oaks, CA: Sage Publications.

  · Chapter 6, “Testing Hypotheses Using Means and Cross-Tabulation”

   

  Warner, R. M. (2012). Applied statistics from bivariate through multivariate techniques (2nd ed.). Thousand Oaks, CA: Sage Publications.

  Applied Statistics From Bivariate Through Multivariate Techniques, 2nd Edition by Warner, R.M. Copyright 2012 by Sage College. Reprinted by permission of Sage College via the Copyright Clearance Center.

  · Chapter 3, “Statistical Significance Testing” (pp. 81–124)

   

  Applied Statistics From Bivariate Through Multivariate Techniques, 2nd Edition by Warner, R.M. Copyright 2012 by Sage College. Reprinted by permission of Sage College via the Copyright Clearance Center.

   

  Magnusson, K. (n.d.). Welcome to Kristoffer Magnusson’s blog about R, Statistics, Psychology, Open Science, Data Visualization [blog]. Retrieved from http://rpsychologist.com/index.html

  As you review this web blog, select [Updated] Statistical Power and Significance Testing Visualization link, once you select the link, follow the instructions to view the interactive for statistical power. This interactive website will help you to visualize and understand statistical power and significance testing.

  Note: This is Kristoffer Magnusson’s personal blog and his views may not necessarily reflect the views of Walden University faculty.

   

  American Statistical Association (2016). American Statistical Association Releases Statement on Statistical Significance and P-Values. Retrieved from http://www.amstat.org/newsroom/pressreleases/P-ValueStatement.pdf

  As you review this press release, consider the misconceptions and the misuse of p-values in quantitative research.

   

  Document: Week 5 Scenarios (PDF)

  Use these scenarios to complete this week’s Assignment.

   

  Datasets

  Your instructor will post the datasets for the course in the Doc Sharing section and in an Announcement. Your instructor may also recommend using a different dataset from the ones provided here.

  Required Media

  Walden University, LLC. (Producer). (2016f). Meaningfulness vs. statistical significance [Video file]. Baltimore, MD: Author.

   

  Note: The approximate length of this media piece is 4 minutes.

   

  In this media program, Dr. Matt Jones discusses the differences in meaningfulness and statistical significance. Focus on how this information will inform your Discussion and Assignment for this week.

   

  Accessible player

  Walden University, LLC. (Producer). (2016n). Halfway point [Video file]. Baltimore, MD: Author.

   

  Note: The approximate length of this media piece is 2 minutes.

   

  In this media program, Dr. Annie Pezalla, Associate Director of Curriculum and Assessment with the Office of Research and Doctoral Studies at Walden University, discusses what you have learned so far in the course. She also discusses what you have to look forward to as well as things to look out for in the remainder of the course.

   

  Accessible player

  Optional Resources

  Skill Builders:

  · Evaluating P Values

  · Statistical Power

  To access these Skill Builders, navigate back to your Blackboard Course Home page, and locate “Skill Builders” in the left navigation pane. From there, click on the relevant Skill Builder link for this week.

  You are encouraged to click through these and all Skill Builders to gain additional practice with these concepts. Doing so will bolster your knowledge of the concepts you’re learning this week and throughout the course.

The following tables form part of a database held in a relational DBMS :

Hotel (hotelNo, hotelName, city) Room (roomNo, hotelNo, type, price) Booking

(hotelNo, guestNo, dateFrom, dateTo, roomNo) Guest (guestNo, guestName,

guestAddress)

where Hotel contains hotel details and hotelNo is the primary key ; Room contains

room details for each hotel and (roomNo, hoteINo) forms the primary key ; Booking

contains details of bookings and (hoteINo, guestNo, datFrom) forms the primary key;

Guest contains guest details and guestNo is the primary key

a. Identify the foreign keys in this schema. Explain how the entity and referential

integrity rules apply to these relations.

b. Produce some sample tables for these relations that observe the relational

integrity rules. Suggest some general constraints that would be appropriate for

this schema.

c. Analyze the RDBMSs that you are currently using. Determine the support the

system provides for primary keys, alternate keys, foreign keys, relational

integrity, and views.

d. Implement the above schema in one of the RDBMSs you currently use.

Generate two user-views that are accessible and updatable as well as two

other user-views that cannot be updated.

Exercise 2 :

Assume you have been contracted to develop a database system for a university

library. You are required to use a systems development lifecycle approach. Discuss

how you are going to approach the project. Describe user groups that will be involved

during the requirement analysis. What are the key issues that need to be answered

during fact finding?

Exercise 3 :

Create an ER model for each of the following descriptions:

a. A large organization has several parking lots, which are used by staff.

b. Each parking lot has a unique name, location, capacity, and number of floors

(where appropriate).

c. Each parking lot has parking spaces, which are uniquely identified using a

space number.

d. Members of staff can request the sole use of a single parking space. Each

member of staff has a unique number, name, telephone extension number,

and vehicle license number.

e. Represent all the ER models described in parts (a), (b), (c), and (d) as a single

ER model. Provide any assumptions necessary to support your mode.