Data and Statistics | Bài giảng số 1 chương 1 học phần Applied statistics | Trường Đại học Quốc tế, Đại học Quốc gia Thành phố Hồ Chí Minh

An error in data acquisition occurs whenever the data value obtained is not equal to the true or actual value that would be obtained with a correct procedure. Experienced data analysts take great care in collecting and recording data to ensure that errors are not made. Special procedures can be used to check for internal consistency of the data. -> Taking steps to acquire accurate data can help ensure reliable and valuable decision-making information. Tài liệu giúp bạn tham khảo, ôn tập và đạt kết quả cao. Mời bạn đón xem.

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Môn: Applied statistics (ENEE1006IU)

Trường: Trường Đại học Quốc tế, Đại học Quốc gia Thành phố Hồ Chí Minh

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Profile 0136_Trần Thảo Vy
APPLIED STATISTICS
COURSE CODE: ENEE1006IU
Lecture 1:
Chapter 1: Data and Stascs
(3 credits: 2 is for lecture, 1 is for lab-work)
Instructor: TRAN THANH TU
tu@hcmiu.edu.vn 2
Email: tu@hcmiu.edu.vn tu@hcmiu.edu.vn
1
1.1. DATA CLASSIFICATION
•Elements, Variables, and Observaons •Scales of Measurement
•Categorical and Quantave Data •Cross-Seconal and Time
Series Data
A. ELEMENTS, VARIABLES, AND OBSERVATIONS
•Data are the facts and gures collected, analyzed, and summarized for
presentaon and interpretaon.
Elements are the enes on which data are collected.
A variable is a characterisc of interest for the elements.
tu@hcmiu.edu.vn 3
The set of measurements obtained for a parcular element is called an
B. SCALES OF MEASUREMENT
•Scales of Measurement: nominal, ordinal, interval, or rao.
determines the amount of informaon contained in the data
tu@hcmiu.edu.vn 4
indicates the most appropriate data summarizaon and stascal analyses
tu@hcmiu.edu.vn 5
B. SCALES OF MEASUREMENT
•Scales of Measurement: nominal, ordinal, interval, or rao
tu@hcmiu.edu.vn 6
tu@hcmiu.edu.vn 7
B. SCALES OF MEASUREMENT
-Nominal scale: when the data for a variable consist of labels or names used to
idenfy an aribute of the element
a numerical code as well as a nonnumerical label may be used
-Ordinal scale: if the data exhibit the properes of nominal data and in addion, the
order or rank of the data is meaningful
-Interval scale: if the data have all the properes of ordinal data and the interval
between values is expressed in terms of a xed unit of measure
Interval data are always numerical
-Rao scale: if the data have all the properes of interval data and the rao of two
values is meaningful
tu@hcmiu.edu.vn 8
This scale requires that a zero value be included to indicate that nothing exists for
the variable at the zero point
B. SCALES OF MEASUREMENT
-Nominal scale: when the data for a variable consist of labels or names used to
idenfy an aribute of the element
tu@hcmiu.edu.vn 9
a numerical code as well as a nonnumerical label may be used
Example: genotype, blood type, zip code, gender, race, eye color, polical party, etc.
B. SCALES OF MEASUREMENT
-Ordinal scale: if the data exhibit the properes of nominal data and in addion, the
order or rank of the data is meaningful
tu@hcmiu.edu.vn 10
Example: socio economic status (“low income”,”middle income”,”high income”)
educaon level (“high school”,”BS”,”MS”,”PhD”) income level (“less than
50K”, “50K-100K”, “over 100K”)
sasfacon rang (“extremely dislike”, “dislike”, “neutral”, “like”, “extremely like”), etc.
tu@hcmiu.edu.vn 11
B. SCALES OF MEASUREMENT
-Interval scale: if the data have all the properes of ordinal data and the interval
between values is expressed in terms of a xed unit of measure
Interval data are always numerical (in which, zero sll has the meaning)
Example: temperature (Farenheit), temperature (Celcius),
pH, SAT score
(200-800), credit score (300-850), etc.
tu@hcmiu.edu.vn 12
B. SCALES OF MEASUREMENT
-Rao scale: if the data have all the properes of interval data and the rao of two
values is meaningful
This scale requires that a zero value be included to indicate that nothing exists for
the variable at the zero point
tu@hcmiu.edu.vn 13
Example: enzyme acvity, dose amount, reacon rate, ow rate,
concentraon, pulse, weight, length, temperature in Kelvin (0.0 Kelvin
really does mean “no heat”), survival me, etc.
Time is interval scale: 0 is 12:00 noon
Duraon is raon scale: 0 means no more me
B. SCALES OF MEASUREMENT
Summary of data types and scale measures:
tu@hcmiu.edu.vn 14
tu@hcmiu.edu.vn 15
C. CATEGORICAL AND QUANTITATIVE DATA
tu@hcmiu.edu.vn 16
tu@hcmiu.edu.vn 17
C. CATEGORICAL AND QUANTITATIVE DATA
•A categorical variable is a variable with categorical data, and a quantave
variable is a variable with quantave data.
•If the variable is categorical, the stascal analysis is limited
tu@hcmiu.edu.vn 18
(when the categorical data are
idened by a numerical code,
arithmec operaons such as addion,
subtracon,
mulplicaon, and division do not
provide meaningful results)
tu@hcmiu.edu.vn 19
C. CATEGORICAL AND QUANTITATIVE DATA
tu@hcmiu.edu.vn 20
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APPLIED STATISTICS COURSE CODE: ENEE1006IU Lecture 1:
Chapter 1: Data and Statistics
(3 credits: 2 is for lecture, 1 is for lab-work) Instructor: TRAN THANH TU Email: tttu@hcmiu.edu.vn tttu@hcmiu.edu.vn 1 1.1. DATA CLASSIFICATION
•Elements, Variables, and Observations •Scales of Measurement
•Categorical and Quantitative Data •Cross-Sectional and Time Series Data
A. ELEMENTS, VARIABLES, AND OBSERVATIONS
•Data are the facts and figures collected, analyzed, and summarized for
presentation and interpretation.
Elements are the entities on which data are collected.
A variable is a characteristic of interest for the elements. tttu@hcmiu.edu.vn 2
The set of measurements obtained for a particular element is called an B. SCALES OF MEASUREMENT
•Scales of Measurement: nominal, ordinal, interval, or ratio.
determines the amount of information contained in the data tttu@hcmiu.edu.vn 3
indicates the most appropriate data summarization and statistical analyses tttu@hcmiu.edu.vn 4 B. SCALES OF MEASUREMENT
•Scales of Measurement: nominal, ordinal, interval, or ratio tttu@hcmiu.edu.vn 5 tttu@hcmiu.edu.vn 6 B. SCALES OF MEASUREMENT
-Nominal scale: when the data for a variable consist of labels or names used to
identify an attribute of the element
a numerical code as well as a nonnumerical label may be used
-Ordinal scale: if the data exhibit the properties of nominal data and in addition, the
order or rank of the data is meaningful
-Interval scale: if the data have all the properties of ordinal data and the interval
between values is expressed in terms of a fixed unit of measure
Interval data are always numerical
-Ratio scale: if the data have all the properties of interval data and the ratio of two values is meaningful tttu@hcmiu.edu.vn 7
This scale requires that a zero value be included to indicate that nothing exists for
the variable at the zero point B. SCALES OF MEASUREMENT
-Nominal scale: when the data for a variable consist of labels or names used to
identify an attribute of the element tttu@hcmiu.edu.vn 8
a numerical code as well as a nonnumerical label may be used
Example: genotype, blood type, zip code, gender, race, eye color, political party, etc. B. SCALES OF MEASUREMENT
-Ordinal scale: if the data exhibit the properties of nominal data and in addition, the
order or rank of the data is meaningful tttu@hcmiu.edu.vn 9
Example: socio economic status (“low income”,”middle income”,”high income”)
education level (“high school”,”BS”,”MS”,”PhD”) income level (“less than
50K”, “50K-100K”, “over 100K”)
satisfaction rating (“extremely dislike”, “dislike”, “neutral”, “like”, “extremely like”), etc. tttu@hcmiu.edu.vn 10 B. SCALES OF MEASUREMENT
-Interval scale: if the data have all the properties of ordinal data and the interval
between values is expressed in terms of a fixed unit of measure
Interval data are always numerical (in which, zero still has the meaning)
Example: temperature (Farenheit), temperature (Celcius), pH, SAT score
(200-800), credit score (300-850), etc. tttu@hcmiu.edu.vn 11 B. SCALES OF MEASUREMENT
-Ratio scale: if the data have all the properties of interval data and the ratio of two values is meaningful
This scale requires that a zero value be included to indicate that nothing exists for
the variable at the zero point tttu@hcmiu.edu.vn 12
Example: enzyme activity, dose amount, reaction rate, flow rate,
concentration, pulse, weight, length, temperature in Kelvin (0.0 Kelvin
really does mean “no heat”), survival time, etc.
Time is interval scale: 0 is 12:00 noon
Duration is ration scale: 0 means no more time B. SCALES OF MEASUREMENT
Summary of data types and scale measures: tttu@hcmiu.edu.vn 13 tttu@hcmiu.edu.vn 14
C. CATEGORICAL AND QUANTITATIVE DATA tttu@hcmiu.edu.vn 15 tttu@hcmiu.edu.vn 16
C. CATEGORICAL AND QUANTITATIVE DATA
•A categorical variable is a variable with categorical data, and a quantitative
variable is a variable with quantitative data.
•If the variable is categorical, the statistical analysis is limited tttu@hcmiu.edu.vn 17
(when the categorical data are
identified by a numerical code,
arithmetic operations such as addition, subtraction,
multiplication, and division do not provide meaningful results) tttu@hcmiu.edu.vn 18
C. CATEGORICAL AND QUANTITATIVE DATA tttu@hcmiu.edu.vn 19 tttu@hcmiu.edu.vn 20