# UnitIRCHstudyguide.pdf

RCH 8303, Quantitative Data Analysis 1

Course Learning Outcomes for Unit I Upon completion of this unit, students should be able to:

1. Perform statistical tests using software tools. 1.1 Choose appropriate Comprehensive R Archive Network (CRAN) locations for software

download. 1.2 Perform download and installation of the R software. 1.3 Perform download and installation of the R Commander library.

2. Explain results of statistical tests.

2.1 Describe the role of statistical analysis within the research process. 2.2 Discuss the differences between the population and a sample. 2.3 Elaborate on how central tendency variability is important in statistical analysis. 2.4 Describe how probability influences the distribution of data. 2.5 Contrast the differences between a normal distribution and a standard distribution. 2.6 Discuss how skewness and kurtosis influence the selection of some statistical tests.

Course/Unit Learning Outcomes

Learning Activity

1.1, 1.2, 1.3

Unit Lesson Chapter 1 Chapter 2 Tutorial: How to Guide: Installing R on Your Computer Website: The R Project for Statistical Computing Unit I Assignment 2

2.1, 2.2, 2.3, 2.4, 2.5, 2.6

Unit Lesson Tutorial: How to Guide: Setting up a CITI Login Unit I Assignment 1

Required Unit Resources Chapter 1: Introducing R and the R Commander Chapter 2: Installing R and the R Commander In order to access the following resources, please click the links below. Review the following webpage to learn about the software that will be used for computing data throughout this course. The R Foundation. (n.d.). The R project for statistical computing. https://www.r-project.org/ For instructions on how to install R, access the document How to Guide: Installing R on Your Computer. For instructions on how to set up a CITI account, access the document How to Guide: Setting up a CITI Login.

UNIT I STUDY GUIDE

Installation of R Software Package and CITI EOSA Course Requirements

RCH 8303, Quantitative Data Analysis 2

UNIT x STUDY GUIDE

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Unit Lesson

Introduction Welcome to Quantitative Data Analysis. In this course, you will utilize the statistical software programming language R with the graphical user interface R. By using R and R Commander (Cmdr), you will learn how to import, clean, and manipulate data. In addition, you will learn how to not only view data through a graphical lens via histograms and other plots, but you will perform statistical tests with data. This course will use the Using the R Commander: A Point-And-Click Interface for R textbook and software; however, if you are not comfortable utilizing R and R Commander you may use whatever statistical software program you choose. The answers you submit for your assignments must be correct regardless of the software you choose. Table 1 below provides a quick comparison guide of different statistics programs, also a summary of these programs follows the table. With the statistical software program R, you can use different types of statistical analysis such as t-tests, analysis of variance [ANOVA], correlation, and regression to interpret the results of your study. After analyzing the statistical test results, you will write up the results in an academic manner. You will apply the Publication Manual of the American Psychological Association (7th ed.) guidelines to report your results. In the research world, depending on whether you are doing quantitative research or qualitative research, you will have data to gather and analyze. Suppose you plan to conduct a quantitative type of study, the focus of this course and software for this type of data analysis. In that case, you will be using statistics to analyze and determine what your data is telling you. Table 1 Comparison Guide of Different Statistics Programs

R and Rcmdr R commander is a point and click interface for R

Free and no annual subscriptions, textbook supported. Free add-ons.

Install Rcmdr for point and click interface.

SPSS Point and click Many universities use this program. It is textbook supported.

6-month and 12-month license, pay for add-ons, and external fees may be required

PSPP

You can redistribute it and/or modify it under the terms of the GNU General Public License

Free software. PDF manual supported

Code-based support

STATA Point and click Video and textbook support

6-month and 12-month license and external fees may be required

Minitab Point and click Video Support 6 month and 12-month rentals

Excel Point and click Intuitive and Textbook supported

May not be able to complete all assumptions for statistical tests. Need to install Toolpak add on. Various costs.

RCH 8303, Quantitative Data Analysis 3

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SAS/STAT Point and click Free and low-cost Academic options

Free version appears to require code programming

RCH 8303, Quantitative Data Analysis 4

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point-and-click software, SPSS also has a command syntax language. PSPP is very similar to SPSS. It has the data and variable view tabs and has a layout that is almost identical to SPSS. SPSS does a better job of drawing the histograms for these variables. PSPP lists the variance as one of the statistics it will compute, but it does not compute and write out the variance. Excel Spreadsheet Software Excel software can be used for many of the basic statistical tests. Users may need to install the Analysis Toolpak to gain access to the statistical test menus. Running the assumption tests can be a challenge using Excel.

What Exactly is R? This course uses the free software program R, which is easily obtained and updated through the internet (refer to instructions in the syllabus). Two reasons more and more people are using R instead of other statistical software packages are cost and flexibility (Smart, 2014). R is free and, like many software packages, once you are shown how to use the program, the program can become a useful tool not only in your research journey but in your career. There is no need to pay annual renewal fees. You can simply download the latest edition years later if you need to do that. R also has many statistical tests that are not available in other packages. These tests are encapsulated in libraries; the libraries are maintained by statisticians and academic researchers. Thus, an R user is not constrained to the tests offered by a software company.

What is R Commander? The R Commander—the subject of the textbook in this course—is a point-and-click graphical user interface (GUI) for R, allowing you to use R statistical software through familiar menus and dialog boxes instead of by typing commands. The purpose of the assigned textbook book is to show you how to perform data analysis with the R Commander by employing common statistical methods.

What is the Essentials of Statistical Analysis? The Essentials of Statistical Analysis (EOSA), offered by Columbia Southern University through the Collaborative Institutional Training Initiative (CITI Program), explains various statistical methods and analyses used in quantitative research. Each module is approximately 30 minutes in duration and culminates with an exam. Once completed, the notice will be submitted for the unit. As we move from unit to unit, you will be required to complete other modules in the CITI program that align with the topic for that unit. The purpose of completing this training is to ensure you have the fundamental knowledge in statistics that align with the type of statistical tests performed.

Unit I Plan The Unit I assignment will be in two parts. Part 1 of your assignment requires you to complete six modules of the CITI Program EOSA that relate directly the readings in this unit. Each of the modules has a final quiz that must be completed and successfully passed with a 75% minimum score, which demonstrates your knowledge of basic statistics and the research process. The topics in the CITI EOSA course relating to Unit I are: Introduction to Statistics (ID 17609): This module explains the role of statistical analysis within the research process, describes the importance of planning before conducting a study, and describes examples of variables at different levels. This module is the foundation for learning quantitative data analysis.

RCH 8303, Quantitative Data Analysis 5

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Population and Sample (ID 17610): This module introduces the student to fundamental differences between the population and sample, helps the student understand inclusion and exclusion and its relationship to statistical concepts, and shows how population and sample fit in the broader research process. This module is vital for one’s understanding of the differences in terms and how they could affect a student’s proposed research. Central Tendency and Variability (ID 17611): This module will re-acquaint the student with measures of central tendency (e.g., mean, mode, medium) and how variability is essential in statistical analysis. This module is relevant because it lays the foundation of many, if not most, statistical tests. Distribution and Probability (ID 17613): This module explains the different types of distributions, the importance of plotting data to increase understanding, and introduces aspects of probability. This module is important since plotting data assists a researcher in understanding the distribution of variables under study. Normal Distribution and Z-Scores (ID 17615): This module is a continuation of module ID 17613, expands on aspects of the normal distribution, and introduces students to a standard distribution. This module is essential because this is a foundation of many, if not most, statistical analyses. Skewness and Kurtosis (ID 17616): This module explains skewness and kurtosis, and introduces students to data transformation. This module is very important because researchers often have to transform data to approximate a normal distribution to perform a parametric test. If data cannot be transformed, then a lesser strength nonparametric test would have to be used. For Part 2, you will need to install the free software program R. Instructions to download and install R are provided under your required resources for this unit. Once you have installed the R and R Commander, you will need to take a screenshot of your screen (as you are logged into the R program), and submit that in the portal in Blackboard.

Reference Smart, F. (2014, March 27). Why use R? Five reasons. R-Bloggers. https://www.r-bloggers.com/why-use-r-

five-reasons/

Learning Activities (Nongraded) Nongraded Learning Activities are provided to aid students in their course of study. You do not have to submit them. If you have questions, contact your instructor for further guidance and information. When studying APA formatting, pay particular attention to the sections that pertain to formatting for research and statistics. These pages, Reporting Standards for Quantitative Research, are 77–93 in the Publication Manual of the American Psychological Association (APA).

• Course Learning Outcomes for Unit I
• Required Unit Resources
• Unit Lesson
• Introduction
• Table 1
• What is Minitab?
• What are SPSS Statistics GradPack and Faculty Packs?
• What is SAS?
• What is STATA?
• What is PSPP?
• Excel Spreadsheet Software
• What Exactly is R?
• What is R Commander?
• What is the Essentials of Statistical Analysis?
• Unit I Plan
• Reference
• Learning Activities (Nongraded)

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