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Mathematics in the modern world

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Medical Technology (BSMT1)

431 Documents
Students shared 431 documents in this course
Academic year: 2023/2024
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Emilio Aguinaldo College

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MATHMATICS IN THE MODERN

WORLD LESSON 1: CLASSIFICATION

AND ORGANIZATION OF DATA

DATA MANAGEMENT

  • It is development, execution, and supervision of plans, policies, programs, and practices that control, protect, deliver, and enhance the value of data and information assets.
  • A administrative process by which the required data is acquired, validated and stored which is to ensure to satisfy the needs of the data users. STATISTICS
  • “STATUS” meaning “state”
  • It deals with the collection, classification, analysis, and interpretation of numerical facts or data. GENERAL PURPOSE OF STATISTICS
  1. Used to organize and summarize information
  2. Determining what general conclusions are justified based on the specific results METHODS OF DATA GATHERING
  3. DIRECT OR INTERVIEW METHOD
  • Person to person gathering of information
  1. INDIRECT OR QUESTIONNAIRE METHOD
  • Questionnaire are used to gather information
  1. REGISTRATION
  • Obtains data from the records of government agency authorized by LAW
  • Example: registration of birth, marriage and death
  1. OBSERVATION
  • Pertaining to the behaviors of individuals or group
  1. EXPERIMENTAL
  • Data are gathered form the results of experiments/experimental variables.
  • Independent Variable (IV) (the cause) – systematically manipulated by the investigator
  • Dependent Variable (DV) (the effect) - investigator measures to determine the effect of the independent variable SCIENTIFIC METHOD
  • Data from the experiment force a conclusion consonant with reality. DESCRIPTIVE STATISTICS
  • Involves collection and classification of data
  • Average and percentage

INFERENTIAL STASTICS

  • Analysis and interpretation of data
  • Estimate and prediction POPULATION
  • Set of measurements corresponding to the entire collection of units. It is group of objects/subjects. SAMPLE
  • Set of individuals selected from a population. DATA
  • Collection of measurements or observations.
  • DATUM a single measurement, commonly called a score or raw score TYPES OF DATA
  1. QUALITATIVE DATA
  • categories or attributes of event or individual
  1. QUANTITATIVE DATA
  • Can be measured or counted in numerical values
  • Discrete – data obtained by counting (number of students)
  • Continuous data – data obtained my measuring (height, weight, volume) PARAMETER
  • A value, usually a numerical value that describes a population. STATISTICC
  • A value, usually a numerical value that describes a sample SAMPLING ERROR
  • Naturally occurring discrepancy or error that exists between statistic and parameter VARIABLE
  • Any property or characteristic of some event, object or person LEVELS OF MEASUREMENT
  • Nominal, ordinal, interval or ratio (interval or ratio are called continuous or scale) HIERARCHY OF LEVELS
  1. Ratio – a true zero
  • Ex. Speed, height and weight
  1. Interval – numerical data that has order. Do not have a true zero
  • Numbers tell the distances between measurements
  • Ex. temperature
  1. Ordinal – ranks qualitative data according to its degree
  • The numbers indicates an order
  1. Nominal(weakest) – mutually exclusive categories
  • The number in the variables are used only to classify the data.

LESSON 2:

1. MEAN

  • “Average” or “Arithmetic mean”
  • Sum of all values in a data set
  1. MEDIAN
  • Middle most score
  • Middle value of a distribution
  1. MODE
  • Most frequent number in a data set OUTLIER
  • A value that lies outside
  • Use IQR method MEASURES OF RELATIVE DISPERSION
  • Used when one wishes to compare the scatter of one distribution with another distribution. STANDARD SCORE
  • It measures how many standard deviation is above or below the mean. SYMMETRIC DISTRIBUTION
  • Property of a distribution that has the mean as the center, acting as a mirror image of the two sides of the distribution.
  • The mean is equal to the median. ASYMMETRIC DISTRIBUTION
  • Lack of symmetry
  • Can be right-skewed distribution or left- skewed distribution EX. Right-skewed distribution
  • The scores of students who did not study for a major examination
  • The number of people buying Christmas presents during December. SKEWNESS Skewness is a measure or a criterion on how asymmetric the distribution of data is from the mean. PEARSON COEFFICIENT OF SKEWNESS
  • a method developed by Karl Pearson to find skewness in a sample using descriptive statistics like the mean and mode. SYMMETRICAL DISTRIBUTION Symmetrical distribution and mode occur occurs when the values of variables occur at regular frequencies and the mean, median at the same point. Positively SKEWED
  • a positively skewed (or right-skewed) distribution is a type of distribution in which most values are clustered around the left tail of the distribution while the right tail of the distribution is longer.

NEGATIVELY SKEWED

  • is a type of distribution in which more values are concentrated on the right side (tail) of the distribution graph while the left tail of the distribution graph is longer. KURTOSIS
    • measure of whether the data are heavy-tailed or light-tailed relative to a normal distribution
    • data sets with high kurtosis tend to have heavy tails, or outliers. Data sets with low kurtosis tend to have light tails, or lack of outliers. LEPTOKURTIC
  • Leptokurtic indicates a positive excess kurtosis. MESOKURTIC
  • equal PLATYKURTIC
  • A platykurtic distribution shows a negative excess kurtosis.
  • The kurtosis reveals a distribution with flat tails The characteristic of a frequency distribution that ascertains its symmetry about the mean is called skewness. On the other hand, Kurtosis means the relative pointedness of the standard bell curve, defined by the frequency distribution.
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Mathematics in the modern world

Course: Medical Technology (BSMT1)

431 Documents
Students shared 431 documents in this course

University: Emilio Aguinaldo College

Was this document helpful?
MATHMATICS IN THE MODERN
WORLD LESSON 1: CLASSIFICATION
AND ORGANIZATION OF DATA
DATA MANAGEMENT
-It is development, execution, and
supervision of plans, policies,
programs, and practices that control,
protect, deliver, and enhance the
value of data and information assets.
-A administrative process by which the
required data is acquired, validated
and stored which is to ensure to
satisfy the needs of the data users.
STATISTICS
-“STATUS” meaning “state”
-It deals with the collection,
classification, analysis, and
interpretation of numerical facts or
data. GENERAL PURPOSE OF
STATISTICS
1. Used to organize and
summarize information
2. Determining what general
conclusions are justified based
on the specific results
METHODS OF DATA GATHERING
1. DIRECT OR INTERVIEW METHOD
-Person to person gathering
of information
2. INDIRECT OR
QUESTIONNAIRE METHOD
-Questionnaire are used to
gather information
3. REGISTRATION
-Obtains data from the records of
government agency authorized by
LAW
-Example: registration of birth,
marriage and death
4. OBSERVATION
-Pertaining to the behaviors
of individuals or group
5. EXPERIMENTAL
-Data are gathered form the results
of experiments/experimental
variables.
-Independent Variable (IV) (the
cause) – systematically manipulated
by the investigator
-Dependent Variable (DV) (the
effect) - investigator measures to
determine the effect of the
independent variable
SCIENTIFIC METHOD
-Data from the experiment force a
conclusion consonant with
reality.
DESCRIPTIVE STATISTICS
-Involves collection and classification
of data
-Average and percentage
INFERENTIAL STASTICS
-Analysis and interpretation of data
-Estimate and prediction
POPULATION
-Set of measurements corresponding
to the entire collection of units. It is
group of objects/subjects.
SAMPLE
-Set of individuals selected from
a population.
DATA
-Collection of measurements
or observations.
-DATUM a single measurement,
commonly called a score or raw
score
TYPES OF DATA
1. QUALITATIVE DATA
-categories or attributes of event
or individual
2. QUANTITATIVE DATA
-Can be measured or counted
in numerical values
-Discrete – data obtained by
counting (number of students)
-Continuous data – data obtained
my measuring (height, weight,
volume)
PARAMETER
-A value, usually a numerical value
that describes a population.
STATISTICC
-A value, usually a numerical value
that describes a sample
SAMPLING ERROR
-Naturally occurring discrepancy or
error that exists between statistic and
parameter
VARIABLE
-Any property or characteristic of
some event, object or person
LEVELS OF MEASUREMENT
-Nominal, ordinal, interval or ratio
(interval or ratio are called
continuous or scale)
HIERARCHY OF LEVELS
1. Ratio – a true zero
-Ex. Speed, height and weight
2. Interval – numerical data that
has order. Do not have a true
zero
-Numbers tell the distances
between measurements
-Ex. temperature
3. Ordinal – ranks qualitative
data according to its degree
-The numbers indicates an order
4. Nominal(weakest) –
mutually exclusive
categories
-The number in the variables are
used only to classify the data.

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