Data Management: Collec/ng,
Presen/ng and Analyzing Research
Data
By: Ania) Murni & Zainal A. Hasibuan
ania/(zhasibua)@cs.ui.ac.id
Faculty of Computer Science University of Indonesia
Mo/va/on
• Can research without data?
• How can you resolve the problem without suppor/ng data?
• How do you convince other, that your data are sufficient to support the solu/on?
• Where do you go to find data?
• Can you have imaginary data in research?
Session Objec/ves
• To understand source of data and type of data
• To understand how to collect and present data
Source of Data
• Quan/ta/ve data are values on a numerical scale
Source of Data
Source of data
Continuous Discrete
Qualitative
(categorical)
Quantitative
(numerical)
Quan/ta/ve or Numerical Data
• Discrete Data
– Only certain values are possible (there are gaps between the possible values)
• Con/nuous Data
Types of Data
• Primary data: data observed and recorded or collected directly from respondents
Types of Data
Secondary
Data
Compilation
Observation
Experimentation
Print or Electronic
Survey
Primary
Data Collection
Categorical Data
Ratio Data
Interval Data
Ordinal Data
Nominal Data
Differences between measurements, true zero exists
Differences between measurements but no true zero
Ordered Categories (rankings, order, or scaling)
Categories (no ordering or direction)
Height, Age, Weekly Food Spending
Temperature in Fahrenheit, Standardized exam score
Service quality rating, Standard & Poor’s bond rating, Student letter grades
Marital status, Type of car owned
Collec/ng Quan/ta/ve Data
• Iden/fy your unit analysis
– Who can supply the informa/on that you will use to answer your quan/ta/ve research ques/ons or hypotheses?
• Specify the popula/on and sample
• Informa/on to collect
– Specify variable from research ques/ons and hypotheses
– Opera/onally define each variable
Criteria For Choosing Instrument To Collect Quan/ta/ve Data
• Have authors develop the instrument recently, and can you obtain the most recent version?
• Is the instrument widely cited by other authors?
• Are reviews available for the instrument?
• Is there informa/on about the reliability and validity of scores from past uses of the instrument?
• Does the procedure for recording data fit the research ques/ons/hypotheses in your study?
Collec/ng Qualita/ve Data
• What data/informa/on you want to collect?
• How do collect the data/informa/on
– Observa/ons
– Interviews and ques/onnaires
– Documents
Presen/ng Qualita/ve Data
Kategori Frekuensi Frekuensi
relative
Persen
A 35 35/400=0.09 9%
B 260 260/400=0.65 65%
C 93 93/400=0.23 23%
D 12 12/400=0.03 3%
Presen/ng Data as Graphs
Presen/ng Data as Graphs
Penyusunan Distribusi Frekuensi
Contoh : Data Tinggi Badan (Cm) Dari 50 Orang Dewasa
Distribusi Frekuensi Tinggi Badan
Interval kelas Frekuensi Jumlah
Measures of Loca/on
• Mean
• Median
Mean
• Another name for average.
• If describing a popula/on, denoted as µ, the greek leber “mu”.
• If describing a sample, denoted as , called “x‐bar”.
• Appropriate for describing measurement data.
Calcula/ng Sample Mean
Formula:
That is, add up all of the data points and divide by the number of data points.
Data (# of classes skipped): 2 8 3 4 1
Sample Mean = (2+8+3+4+1)/5 = 3.6
Median
• Another name for 50th percen/le.
• Appropriate for describing measurement data.
Calcula/ng Sample Median
Order data from smallest to largest.
If odd number of data points, the median is the middle value.
Data (# of classes skipped): 2 8 3 4 1
Ordered Data: 1 2 3 4 8
Calcula/ng Sample Median
Order data from smallest to largest
If even number of data points, the median is the average of the two middle values
Data (# of classes skipped): 2 8 3 4 1 8
Ordered Data: 1 2 3 4 8 8
Mode
• Mode is the most common number
• Put the numbers in order
• Choose the number that appears the most frequently.
Example Mode
• Class shoe sizes: 3, 5, 5, 6, 4, 3, 2, 1, 5, 6
• Put in order: 1, 2, 3, 3, 4, 5, 5, 5, 6, 6
Skewness
The skewness of a distribu/on is measured by comparing the rela/ve posi/ons of the mean, median and mode.
• Distribu/on is symmetrical
• Mean = Median = Mode
• Distribu/on skewed right
• Median lies between mode and mean, and mode is less than mean
• Distribu/on skewed le2
Negatively Skewed
Positively Skewed Symmetric
(Not Skewed)
S < 0 S = 0 S > 0
Steps in Data Analysis
Pengumpulan Data Verifikasi
Data Pengelompokan
Data Isi
Tabel2
Cek Konsistensi Data antar tabel
Analisa Masing2 Tabel
- Performance : lihat trend
- Profile : bandingkan dng standar
Analyze Quan/ta/ve Data
• Describe trends in the data to a single variable or ques/on on your instrument.
– e.g., What is the self esteem of middle school students?
Analyze Quan/ta/ve Data
• Compare two or more groups on the independent variable in terms of the dependent variable.
– e.g., How do boys and girls compare in their self esteem?
– We need inferen/al sta/s/cs in which we analyze data from a sample to draw conclusions about an unknown popula/on.
Analyze Quan/ta/ve Data
• Relate two or more variable.
– e.g., Does self esteem relate to an op/mis/c ajtude?
– To answer the ques/on, we need inferen/al sta/s/cs.
• Test hypotheses about the differences in the groups or the rela/onships of variables.
– e.g., Boys have higher self esteem than girls or self esteem predicts an op/mis/c ajtude among middle school children.
