ideas and concepts

Introduction to R and others

1. Downloading and Installing R
   1. the_r_project_for_statistical_computing
   2. r, getting started
2. Starting R
3. Entering Commands
4. Exiting from R
5. Interrupting R
6. Viewing the Supplied Documentation
7. Getting Help on a Function
8. Searching the Supplied Documentation
9. Getting Help on a Package
10. Searching the Web for Help
11. Finding Relevant Functions and Packages
12. Searching the Mailing Lists
13. Submitting Questions to the Mailing Lists

using theories and making hypotheses

Installing R

Assignment

Concepts and ideas

Some basics

1. Introduction
2. Printing Something
3. Setting Variables
4. Listing Variables
5. Deleting Variables
6. Creating a Vector
7. Computing Basic Statistics
8. Creating Sequences
9. Comparing Vectors
10. Selecting Vector Elements
11. Performing Vector Arithmetic
12. Getting Operator Precedence Right
13. Defining a Function
14. Typing Less and Accomplishing More
15. Avoiding Some Common Mistakes

using theories and making hypotheses

• Theories
  • to build science
  • to guide as a frame (what to look, how to think, and how to look at)
  • to explain phenomena
  • to predict phenomena (to provide a context for predictions)
  • Empirically relevant (testing) and always tentative (deductive cycle)
    • via research (hypothesis testing)
    • hence, not fixed
  • generalized statement regarding a connection between A and B (idea, concept, construct, phenomena, etc)
  • Levels ?
    • Micro . . . frustration and aggression
    • Meso . . . online communities and disinhibition
    • Macro . . . ethnicity (or socio-econ class) and family bond
  • role of T
    • 
• Research Questions (or Problems)
  • Two ideas guided by theories
  • Questions on their relationships
  • Conceptualization

• Hypothesis
  • Educated guess (via theories)
  • Difference
  • Association
  • Variables (vs. ideas, concepts, and constructs)
    • Operationalization
    • Types of Variable
      • IV
      • DV
      • Control variable
      • Mediating (Intervening) variable

Assignment

In class

small <- c(0.6739635, 1.5524619, 0.3250562, 1.2143595, 1.3107692, 2.1739663, 1.6187899, 0.8872657, 1.9170283, 0.7767406)
medium <- c(10.526448, 9.205156, 11.427756, 8.53318, 9.763317, 9.806662, 9.150245, 10.058465, 9.18233, 7.949692)
big <- c(99.83624, 100.70852, 99.73202, 98.53608, 100.74444, 98.58961, 100.46707, 99.88068, 100.46724, 100.49814)

dframe <- data.frame(small, medium, big)

fib <- c(0,1,1,2,3,5,8,13,21,34)

a1 <- c(1,1,2,3,5,8,13,21)
a2 <- c(2,4,5,3,6,9,18,25)

1. select all elements that exceeds +-2 sd from the mean of the column, medium in dframe.
2. choose only odd numbers from the variable fib.
3. combine a1 and a2 into a data frame, dframe2
4. name a1 and a2 to x and y in dfram2

Concepts and ideas

Navigating software

1. Introduction
2. Getting and Setting the Working Directory
3. Saving Your Workspace
4. Viewing Your Command History
5. Saving the Result of the Previous Command
6. Displaying the Search Path
7. Accessing the Functions in a Package
8. Accessing Built-in Datasets
9. Viewing the List of Installed Packages
10. Installing Packages from CRAN
11. Setting a Default CRAN Mirror
12. Suppressing the Startup Message
13. Running a Script
14. Running a Batch Script
15. Getting and Setting Environment Variables
16. Locating the R Home Directory
17. Customizing R

Assignment

Class Activity

• 가설 만들어 보기
  • No need to read theories
    • the third person effect
    • Spiral of Silence
    • cognitive dissonance
  • Read hypothesis
  • how to write hypothesis at behavioral science writing.
  • One sample hypothesis Hypothesis at www.socialresearchmethods.net

Concepts and ideas

Input and output

1. Introduction
2. Entering Data from the Keyboard
3. Printing Fewer Digits (or More Digits)
4. Redirecting Output to a File
5. Listing Files
6. Dealing with “Cannot Open File” in Windows
7. Reading Fixed-Width Records
8. Reading Tabular Data Files
9. Reading from CSV Files
10. Writing to CSV Files
11. Reading Tabular or CSV Data from the Web
12. Reading Data from HTML Tables
13. Reading Files with a Complex Structure
14. Reading from MySQL Databases
15. Saving and Transporting Objects

Assignment

• 가설 연습 in ajoubb
• w04_assignment

Oct 5: Chooseok Holiday
Oct 3, 4, 5, 6, 7, 8

Concepts and ideas

Data Structures

1. Introduction
2. Appending Data to a Vector
3. Inserting Data into a Vector
4. Understanding the Recycling Rule
5. Creating a Factor (Categorical Variable)
6. Combining Multiple Vectors into One Vector and a Factor
7. Creating a List
8. Selecting List Elements by Position
9. Selecting List Elements by Name
10. Building a Name/Value Association List
11. Removing an Element from a List
12. Flatten a List into a Vector
13. Removing NULL Elements from a List
14. Removing List Elements Using a Condition
15. Initializing a Matrix
16. Performing Matrix Operations
17. Giving Descriptive Names to the Rows and Columns of a Matrix
18. Selecting One Row or Column from a Matrix
19. Initializing a Data Frame from Column Data
20. Initializing a Data Frame from Row Data
21. Appending Rows to a Data Frame
22. Preallocating a Data Frame
23. Selecting Data Frame Columns by Position
24. Selecting Data Frame Columns by Name
25. Selecting Rows and Columns More Easily
26. Changing the Names of Data Frame Columns
27. Editing a Data Frame
28. Removing NAs from a Data Frame
29. Excluding Columns by Name
30. Combining Two Data Frames
31. Merging Data Frames by Common Column
32. Accessing Data Frame Contents More Easily
33. Converting One Atomic Value into Another
34. Converting One Structured Data Type into Another

Assignment

• 자신의 관심사와 어울리는 참고문헌 수집하기
  1. 자신의 관심사를 정리하는 2 문단 작성
  2. 이에 해당하는 키워드 추출 (3-5)
  3. 키워드를 이용하여 관련된 논문 찾기 (영어논문 1개, 국내논문 3개)
     • Science Direct
     • Sage online pub
     • DBpia
     • 논문은 empirical study를 지향하는 것 (연구문제 혹은 가설을 포함하는 사회과학 논문)이어야 합니다.
  4. 각 논문을 APA style의 참고문헌목록 형식으로 소개하고
     • APA 형식은 언론관련학술지논문작성지침.hwp 참조
     • 각 논문이 왜 자신의 논문과 관련이 있는지 자신의 글로 정리하여 기록
     • 가설 혹은 연구문제가 있다면 무엇이었는지 정리 후 기록
• 이를 토대로 자신의 가설을 만들어 보기 (3)
• Ajou BB journal에서 수행: assignment-w05: building hypotheses

w05_assignment

Oct 9: Hangul Day

Concepts and ideas

Data Transformations

1. Introduction
2. Splitting a Vector into Groups
3. Applying a Function to Each List Element
4. Applying a Function to Every Row
5. Applying a Function to Every Column
6. Applying a Function to Groups of Data
7. Applying a Function to Groups of Rows
8. Applying a Function to Parallel Vectors or Lists

Strings and Dates

Matrix Calculation
Social Network Analysis

Announcement

• First quiz
  • The quiz will be held during the mid term schedule.
  • 1st quiz + Week 07 materials.
  • Two sets:
    • without materials
    • with materials (textbook + r help)
    • No internet connection

Assignment

Concepts and ideas

Probability

1. Introduction
2. Counting the Number of Combinations
3. Generating Combinations
4. Generating Random Numbers
5. Generating Reproducible Random Numbers
6. Generating a Random Sample
7. Generating Random Sequences
8. Randomly Permuting a Vector
9. Calculating Probabilities for Discrete Distributions
10. Calculating Probabilities for Continuous Distributions
11. Converting Probabilities to Quantiles
12. Plotting a Density Function

Assignment

개인과제

교재를 읽고

1. Chi-square test를 할 수 있는 가설과
2. One sample t-test를 할 수 있는 가설
3. Two sample t-test를 할 수 있는 가설을 만들어 오시오.

Concepts and ideas

General Statistics
t-test 참조
ANOVA 참조
Factorial ANOVA 참조

1. Introduction
2. Summarizing Your Data
3. Calculating Relative Frequencies
4. Tabulating Factors and Creating Contingency Tables
5. Testing Categorical Variables for Independence
6. Calculating Quantiles (and Quartiles) of a Dataset
7. Inverting a Quantile
8. Converting Data to Z-Scores
9. Testing the Mean of a Sample (t Test)
10. Forming a Confidence Interval for a Mean
11. Forming a Confidence Interval for a Median
12. Testing a Sample Proportion
13. Forming a Confidence Interval for a Proportion
14. Testing for Normality
15. Testing for Runs
16. Comparing the Means of Two Samples
17. Comparing the Locations of Two Samples Nonparametrically
18. Testing a Correlation for Significance
19. Testing Groups for Equal Proportions
20. Performing Pairwise Comparisons Between Group Means
21. Testing Two Samples for the Same Distribution

Assignment

Assignment-Week09

Concepts and ideas

General Statistics
Oneway ANOVA
Twoway ANOVA

Assignment

Concepts and ideas

Graphics

1. Introduction
2. Creating a Scatter Plot
3. Adding a Title and Labels
4. Adding a Grid
5. Creating a Scatter Plot of Multiple Groups
6. Adding a Legend
7. Plotting the Regression Line of a Scatter Plot
8. Plotting All Variables Against All Other Variables
9. Creating One Scatter Plot for Each Factor Level
10. Creating a Bar Chart
11. Adding Confidence Intervals to a Bar Chart
12. Coloring a Bar Chart
13. Plotting a Line from x and y Points
14. Changing the Type, Width, or Color of a Line
15. Plotting Multiple Datasets
16. Adding Vertical or Horizontal Lines
17. Creating a Box Plot
18. Creating One Box Plot for Each Factor Level
19. Creating a Histogram
20. Adding a Density Estimate to a Histogram
21. Creating a Discrete Histogram
22. Creating a Normal Quantile-Quantile (Q-Q) Plot
23. Creating Other Quantile-Quantile Plots
24. Plotting a Variable in Multiple Colors
25. Graphing a Function
26. Pausing Between Plots
27. Displaying Several Figures on One Page
28. Opening Additional Graphics Windows
29. Writing Your Plot to a File
30. Changing Graphical Parameters

Assignment

Announcement

Quiz 03: 다음 주 수요일
범위: input and output ~ twoway ANOVA
방법: 필기(20분) 및 실기 (50분)

Concepts and ideas

Graphics

Assignment

Concepts and ideas

Regression Multiple Regression
Linear Regression and ANOVA

1. Introduction
2. Performing Simple Linear Regression
3. Performing Multiple Linear Regression
4. Getting Regression Statistics
5. Understanding the Regression Summary
6. Performing Linear Regression Without an Intercept
7. Performing Linear Regression with Interaction Terms
8. Selecting the Best Regression Variables
9. Regressing on a Subset of Your Data
10. Using an Expression Inside a Regression Formula
11. Regressing on a Polynomial
12. Regressing on Transformed Data
13. Finding the Best Power Transformation (Box?Cox Procedure)
14. Forming Confidence Intervals for Regression Coefficients
15. Plotting Regression Residuals
16. Diagnosing a Linear Regression
17. Identifying Influential Observations
18. Testing Residuals for Autocorrelation (Durbin?Watson Test)
19. Predicting New Values
20. Forming Prediction Intervals
21. Performing One-Way ANOVA
22. Creating an Interaction Plot
23. Finding Differences Between Means of Groups
24. Performing Robust ANOVA (Kruskal?Wallis Test)
25. Comparing Models by Using ANOVA

Assignment

1. Do Ex 1 part in linear regression

Concepts and ideas

Linear Regression and ANOVA
http://commres.net/wiki/text_mining_example_with_korean_songs

Assignment

1. 자신의 전공과 관심사에 맞는 아래의 테스트를 수행하기 위한 가설을 작성하시오.
   1. T-test
   2. F-test
   3. factorial f-test
   4. Simple regression
   5. Multiple regression
2. 각 가설의 독립변인과 종속변인을 밝히고 이를 측정하는 방법에 대해서 논하시오.
3. 가설과 관련이 있는 논문을 찾아서 (적어도 하나 이상씩) 관련 논문이 밝힌 것을 설명하고 자신의 가설과의 연관성을 논하시오.
4. 각 가설에 필요한 데이터를 구한 후, 적절한 테스를 하시오 (r의 인풋과 아웃풋 필요).
5. 테스트 결과를 논하시오.