Introduction to Statistics
-
Upload
dieter-campbell -
Category
Documents
-
view
24 -
download
0
description
Transcript of Introduction to Statistics
Introduction to
STATISTICS
Objectives: Define terms Identify types and kinds
of data Infuse the relevance of
statistics
Statistics
Statistics
Statistics is a branch of mathematics concerned with the techniques by which information is collected, organized, analyzed, and interpreted.
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.
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.
Steps in Statistical Investigation
1. Collection of data2. Processing of data3. Presentation of data4. Analysis of data5. Interpretation of data
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
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.
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
Types of Data1. Primary data – information
gathered directly from an original source
ex: autobiographies, diaries, business entities and private and public agencies
Types of Data2. Secondary data –
information taken from existing records
ex: published books, newspapers, magazines, theses and dissertations
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
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)
Classification of Statistical Data3. Interval data – numbers represent
equal units between measurements
ex: temperature readings
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)
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
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
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
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
Two types of variables
2. Quantitative variable – includes variables that assume numerical values.
Ex. height, weight, length, monthly income