Statistical Terms and Scales of Measurement2

8/13/2019 Statistical Terms and Scales of Measurement2

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Majority of patients who died of lung cancerare males.

95% of the population has 66 inches height.

Wearing of seatbelts increases the chance ofsurvival in automobile accidents.

Carbon monoxide is one of the majorpollutants of smog.

Blood makes up 8% of the total body weight.


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At the age of 70, what is the

average amount of water that aman has consumed?


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12, 000 gallons


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For how many times does a normalheart beat in a day?


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100,000


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How long does it take for food inthe mouth to enter the stomach?


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7 seconds


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True or False:

The width of your armspanstretched out is the length of yourwhole body.


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True


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In average, how many dreams doesa man have in one night sleep?


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7 dreams


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You speak 4,800 words a day!


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any qualitative or quantitativeinformation.

could be found throughsurveys, experiments, records,etc.


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Basic Terms Used in Statistics


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BASIC TERMS IN STATISTIC


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refers to the totality of all the elements orpersons fro which one has an interest at aparticular time.

Example:

4thYear students of CMRICTHS in the year2013-2014

Filipino people in 2013



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It is part of a population determined bysaampling.

Example:

4thYear students of CMRICTHS in the year2013-2014 who are good at dancing

Selected Filipino people in 2013



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III. Parameter is any statistical information orattribute taken from a population. It is a true

value or actual statistics since its source is

the population itself.

IV. Statistic is any estimate of statistical

attributes taken from a sample.



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Is a specific factor, property, or characteristicof a population, or a sample whichdifferentiates a sample or group of samplesfrom another group.

Example:

Examination: Time, gender

AUFCAT score, high school graduated from



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I. NON-PROBABILITY SAMPLES

II.PROBABILITY SAMPLES


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I. NON-PROBABILITY SAMPLES

Samples are obtained haphazardly, selected

purposively or are taken as volunteers Probabilities of selection are unknown

May not be used for statistical inference

Results from the use of judgement sampling, accidentalsampling, purposively sampling, etc.


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II. Probability Samples

Samples are obtained using some objectivechance mechanism, thus involvingrandomization

Requires the use of a complete listing of theuniverse called the sampling frame Probabilities of selection are known Generally referred to as random samples Allows one to make valid generalizations about

the universe/population


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TYPES OF VARIABLES

1. Qualitative

2. Quantitative


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represent differences in quality, character, orkind but not in amount. They yield non-numeric values.

take on alpha-numeric possible values

Ex:

Gender, birth month, locations, eye color



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Refers to numerical information obtainedfrom counting or measuring that can bemanipulated by any fundamental operation

take on numeric possible values

Ex: age, speed, test scores, temperature

*Quantitative data are further classified aseither discrete or continuous.



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CLASSIFICATION OF QUANTITATIVE DATA

I. DISCREET VARIABLEII.CONTINUOUS VARIABLE


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A discrete variable is a variable whose valuescan be counted using integral values.

Examples:

Number of employees, number of students inclassroom, number of cars owned, number ofsiblings



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A continuous variable is a variable that canassume any numerical value over an intervalor intervals. It yields fractions or decimals.

Examples:

Height, weight, temperature, time



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relates to the rules used to assign scores andis an indicator of the kind of information thatthe scores provide


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Use numbers for the purpose ofidentifying name or membership in agroup or category. As the name

implies, it consists of namingobservations or classifying them intovarious categories.

Purely categoricalExample: Gender, Civil Status


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Religion umber of PersonsCatholic 1, 170

Protestants 45

Iglesia ni Cristo 62

El Shaddai 25

No religions 95

Not reported 13

Other examples: gender, politicalparty, names of schools attended


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connote ranking or inequalities. Onecategory is higher than the other. In thistype of data, numbers represent greaterthan or less than.

categorical with inherent ordering ofcategories

Examples:

Social class or incomes, grades (A,B,C)winners (1st, 2nd, 3rd)Educational attainment; Academic Rank


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The measurement where data are arranged insome order and the differences between data aremeaningful.

Data at this level may lack inherent zero

starting point.-quantitative with constant measures of magnitudeand arbitrary zero point

Examples: Aptitude test score, temperature, IQ

score


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This measurement is an interval levelmodified to include the inherent zero startingpoint.

Examples:

Election votes, ages of students, weights ofbeef

Weekly Allowance, Number of Cellphones Owned


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Determine whether the following areQualitative or Quantitative. If Quantitative,classify if continuous or discrete.

1. Blood types in the blood bank

2. number of patients for consultation in aday

3. gender of newborn babies in the hospital

4. height of a newborn baby5. number of plants in the school

d f h l l f h


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Identify what level of measurement are thefollowing, then an give example:

1. Blood pressure

2. degrees of burn3. height of students

4. favorite sports

5. rank in the class6. number of students who passed

7. temperature

8. marital status

9. nationality

10. score in a game


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REFERENCE:

Advanced Algebra, Trigonometry,and Statistics; Esparrago, et al.

(2004)


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Statistical Terms and Scales of Measurement2