Description
Assignment 2: Article Critique (Multiple Regression)
Many weeks in this course follow a similar pattern. You begin the week by studying a statistical test. Next, you complete Assignment 1, applying that test using datasets that are provided in the context of a research question that you pose. As you master the skills related to the test, including how to run the test in SPSS, you engage with your peers in the Collaboration Lab. The final activity in most weeks, including this week, is an Article Critique, in which you search the Walden Library for research that applies the test you studied that week.
The practice of quantitative research not only involves statistical calculations and formulas but also involves the understanding of statistical techniques related to real-world applications. You might not become a quantitative researcher nor use statistical methods in your profession but as a consumer, citizen, and scholar-practitioner, it will be important for you to become a critical consumer of research, which will empower you to read, interpret, and evaluate the strength of claims made in scholarly material and daily news.
To prepare for this Assignment
- Review this week’s Learning Resources and media program related to multiple regression.
By Day 7
For this Assignment, you will critically evaluate a scholarly article related to multiple regression.
You will note that the journal article critique assignment is similar to those you did in the Quantitative Reasoning and Analysis course in weeks 9 and 10. You should not turn in the paper you submitted in the earlier course. Please note that SafeAssign will match your assignment to your submission(s) from the earlier course and it is not permissible to reuse work from previous courses without specific permission from your instructor.
For this assignment you need to choose an article where the authors used multiple regression that you have not used before in a journal article critique assignment.
Use proper APA format, citations, and referencing for your analysis, research question, and display of output.
Explanation & Answer
please find completed work and I am here to carry any changes I will say bye but will be waiting for your feedback here is the work and let me know if you would like me to make any changes Bye but am here if you need further help
multiple regression
by HAL Lab
Submission date: 12-Jun-2020 10:37AM (UTC-0400)
Submission ID: 1342606162
File name: Multiple_regression_critique.docx (17.46K)
Word count: 680
Character count: 3769
multiple regression
ORIGINALITY REPORT
4
%
SIMILARITY INDEX
2%
2%
4%
INTERNET SOURCES
PUBLICATIONS
STUDENT PAPERS
PRIMARY SOURCES
1
Miyoung Jang, Youngho Song, Jae-Woo Chang.
"A parallel computation of skyline using multiple
regression analysis-based filtering on
MapReduce", Distributed and Parallel
Databases, 2017
2%
Publication
2
2%
www.flygility.co.uk
Internet Source
Exclude quotes
Off
Exclude bibliography
On
Exclude matches
Off
Report: Multiple regression critique
Multiple regression critique
by HAL
General metrics
4,519
689
34
2 min 45 sec
5 min 18 sec
characters
words
sentences
reading
time
speaking
time
Writing Issues
No issues found
Plagiarism
This text hasn’t been checked for plagiarism
Report was generated on Friday, Jun 12, 2020, 05:40 PM
Page 1 of 7
Report: Multiple regression critique
Writing Issues
1
Engagement
1
Word choice
Unique Words
35%
Measures vocabulary diversity by calculating the
percentage of words used only once in your
document
unique words
Rare Words
28%
Measures depth of vocabulary by identifying words
that are not among the 5,000 most common English
words.
rare words
Word Length
5.4
Measures average word length
characters per word
Sentence Length
20.3
Measures average sentence length
words per sentence
Report was generated on Friday, Jun 12, 2020, 05:40 PM
Page 2 of 7
Report: Multiple regression critique
Multiple regression critique
3
ARTICLE CRITIQUE
Running Head: ARTICLE CRITIQUE 1
Article Critique
Name
Course
Date
Multiple regression critique
Introduction
Different statistical approaches are used to assist in predicting the value of one
of several variables. The use of multiple regression is one of the well-known
methods that help statisticians in modelling the relationship that exists
between one scalar response and explanatory variabl...