introduction to statistics
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Introduction to Statistics. Objectives:. Define terms Identify types and kinds of data Infuse the relevance of statistics. mathematics. interpreted. information. collected. Statistics. organized. techniques. analyzed. mathematics. interpreted. information. collected. Statistics. - PowerPoint PPT PresentationTRANSCRIPT
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Introduction to
STATISTICS
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Objectives: Define terms Identify types and kinds
of data Infuse the relevance of
statistics
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Statistics
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Statistics
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Statistics is a branch of mathematics concerned with the techniques by which information is collected, organized, analyzed, and interpreted.
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Two Major Divisions of Statistics1. Descriptive Statistics – is concerned with the collection, classification, and presentation of data to be able to summarize and describe the group characteristics of the data.
Ex: measures of central tendency, measures of variability, skewness, etc.
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2. Inferential Statistics – refers to the drawing of conclusion or judgment about the population based on a representative sample taken from the same population
Ex: hypothesis testing using z-test, t-test, analysis of variance, etc.
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Steps in Statistical Investigation
1. Collection of data2. Processing of data3. Presentation of data4. Analysis of data5. Interpretation of data
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Steps in Statistical Investigation1. Collection of data – process of
obtaining or gathering numerical data
2. Processing of data – organizing data to show significant characteristics
3. Presentation – in the form of tables, graphs, and charts
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4. Analysis of data – method of drawing from the given data relevant information from which numerical description can be formulated.
5. Interpretation of data – refers to the task of drawing conclusions from the analyzed data.
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Data or information are obtained through interview or surveys, researches, experiments, and a lot more. It is the measured variable from a set of experimental units, or a set of measurements
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Types of Data1. Primary data – information
gathered directly from an original source
ex: autobiographies, diaries, business entities and private and public agencies
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Types of Data2. Secondary data –
information taken from existing records
ex: published books, newspapers, magazines, theses and dissertations
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Classification of Statistical Data1. Nominal data – are numerical in
name only because they do not share the properties of numbers we deal with in ordinary arithmetic.
ex: designation of marital status as 1, 2, 3, or 4 for single, married, widowed or divorced
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Classification of Statistical Data2. Ordinal data – numbers indicate
rank order of measurements but they do not indicate the magnitude of interval between the measures.
ex: order of finish in races, grades for achievement, body frames (small, medium, large)
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Classification of Statistical Data3. Interval data – numbers represent
equal units between measurements
ex: temperature readings
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Classification of Statistical Data4. Ratio data – numbers represent
equal units between measurements and there is an absolute zero point. The easiest to find and they include all the usual measurements.
ex: income (measured in pesos, with zero equal to no income at all)
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Other Classification of Statistical Data
1. Discrete data – quantifiable expressed by a whole number, an end result of counting- can only assume a finite or countable number of values
ex: number of students, number of days
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Other Classification of Statistical Data
2. Continuous data – usually results of measurements- can assume infinitely many values that correspond to the points on a line or interval
ex: height, weight, winning time
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Variable is the characteristic that is being studied.Variable is observable characteristic that can be measured or classified.ex. height, grade of students, time, hair color
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Two types of variables1. Qualitative variable –
assumes values that can be categorized according to some distinct characteristics or attribute. - it has no numerical value
Ex: color, type of car
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Two types of variables
2. Quantitative variable – includes variables that assume numerical values.
Ex. height, weight, length, monthly income