Lecture # 1

SPSS for Professionals, Researchers & Students

Lecture # 1Brief knowledge in SPSS

Introduction to Statistics

Definition of Statistics:

It is difficult to define to define statistics in a few words, since its dimension, scope; function; use and importance are constantly changing over changing over time. Facts and figures of phenomenon or events are called statistics.

Statistics is a field of study concerned with (1) the collection, organization, summarization and analysis of data and (2) the drawing of inferences about a body of data is observed.

Scope and Use of Statistics: Statistics has been useful in researches of almost all disciplines. A few fields are : Planning, Population, Health, Family planning, Biology, Business and commerce, Agriculture, physical science, socio-economic study, Environment, Medicine, Psychology and education, Production industry, Astronomy etc.

Variable and its type:A variable is characteristic whose value varies from person to person, object or from phenomenon to phenomenon, Example: Age, income, hair color, family size, profession etc.

Quantitative variable: A quantitative is one for which the resulting observations a re numeric and thus possesses a natural ordering. Example: Age, height family size etc.

Qualitative Variable: A qualitative variable is one for which numerical measurement is not possible, such as, hair color, religion, profession etc.

Quantitative variables may be further classified as or continuous. When a variable can assume only the isolated values within a given range, the variable is called discrete variable such as family size, class size etc. when a variable can theoretically assume any value within a given range the variable is said to be continuous variable. Thus age, height, temperature etc. are continuous variables.

Population: An aggregate of all individuals or items (actual or possible) of interest in any particular study defined on some common characteristics is called a population.Sample: a representative Part of the population is called a sample. The number of individuals in the sample is called sample size.

Types of population:

(1) Finite population: A population consisting of a finite number of individuals or items is called a finite population.

(2) Infinite population consisting of a Infinite number of individuals or items is called a infinite population.

Parameter: Population characteristic, about which inferences are to be made, is called parameter. Population mean is a parameter.

Statistic: Sample characteristic. The sample mean (x) is a statistic.

Estimator: An estimator is a statistics

Which is a unction of sample observation

This is used to investigate the value of the unknown parameter of the population.

Example: X = is an estimation of population parameter .

An estimator is a random variable which takes different values from sample to sample.Estimate: An estimate is a numerical value of the estimator obtained from a particular sample.

Data: Data is plural word and comprehend the idea of collection of pieces of information on some variables. Data are the raw, disorganized facts and figures collected from any field of inquiry.

Statistical data depending upon the sources are of two types

1. Primary data.

2. Secondary data.

1. Primary data: The data which are originally collected by an investigator or an agent for the first time for the purpose of statistical enquiry are known as primary data. The data is original in character.

2. Secondary data: The data which are originally collected but obtained from some published or unpublished sources are called secondary data. This type of data is not original in character. For example: the reports and publications made by Central Bureau of Statistics are primary for that organization but secondary for those who use it.

The data collected on quantitative variables is called quantitative data and the data collected on qualitative variables is called qualitative data.

Scale of Measurement:Measurement is a process of assigning number to some characteristics or variables or events according to scientific rules.

The variables in any study may be of different nature and they may represent some attributes, characteristics or key factors of interest. These variables can be measures under four levels per scales of measurement. The measurement scales are:

1. Nominal scale.

2. Ordinal scale.

3. Interval scale.

4. Ratio scale.

Nominal Scale: The measurement scale, in which numbers are assigned to the categories or variable values for identification only, is called a nominal scale. For example: sex, smoking status etc.

Ordinal Scale: The measurement scale in which numbers are assigned to the categories or variable values for identification as well as for ranking is called an ordinal scale. For example: consider the variable economic status which can be categorizes as rich (1) middle class and (2) poorInterval Scale: The measurement scale in which numbers are assigned to the variable values in such a way that the level of measurement is broken down on a scale of equal units and the zero value on the scale in not absolutely zero, is called an interval scale.

For example: the variable temperature can have values 00, 100, 200 etc.Ratio scale: The measurement scale in which numbers are assigned to the variable values in such a way that the level of measurement is broken down on a scale of equal units and the zero value on the scale is absolutely zero, is called a ration scale. For example: age, weight, pulse rate, parity etc.

Comparative Study of scales of measurement:

ScaleMathematical OperationsExample

NominalCountingSex, Religion

OrdinalCounting & RankingEconomic Status

IntervalCounting & Ranking, Addition & SubtractionTemperature, IQ

RatioCounting & Ranking, Addition, Subtract, multiple & DivisionAge, Family size

Classification of variable by scale of measurement:

Brief Knowledge in SPSS

Origin: The statistical package SPSS was first devised in 1996. Actually SPSS was developed as an analysis program for soc I al scientist.

The abbreviation SPSS stood for Statistical Package for the Social Sciences.

The SPSS Company gave the old abbreviation a new meaning (not very modest): Superior Performing Software System. One of the strong points of SPSS is that it can perform almost any statistical analysis.

Different versions of SPSS:

SPSS X is the SPSS version for minicomputers and mainframe computers. SPSS/PC + is the SPSS version for DOS based computers.

SPSS for Windows.

SPSS X can use up to 32,315 variables in comparison to the 500 that SPSS/PC+, SPSS for Windows can use more then 500 variables.

SPSS for Windows has been derived from the mainframe version and not from SPSS/PC+ version.The exchange of files between the different versions o f SPSS ( SPSS- X, SPSS/PC+, SPSS for Windows ) is handled by special SPSS files that are create and read with the IMPORT commands. Communication with other well-known PC packages is also possible.

Well stick to SPSS for windows. SPSS for Windows is an advanced statistical package designed to run interactively on PC and other computers in a graphical environment, using descriptive menus and simple dialog boxes to do most of the work. Most tasks can be accomplished simply by pointing and clicking the mouse.

What can SPSS do? Data entry

Manipulate and manage data

Produce reports and tables

Perform simple and complex statistical analyses

Produce graphical output

SPSS for Windows: Getting startedYou can start SPSS either by Using Start menu or by using Shortcut icon.

Using Start menu: Click on Start menu at the bottom-left corner of your screen. Point the cursor to Programs, point the cursor to SPSS for Windows and then click on SPSS 10.0 for Windows.Using Shortcut icon: Double click on Shortcut icon of SPSS 10.0 for windows on the desktop.

There are two icons for SPSS (if you open it from start button)

SPSS for Windows (This will be of our interest)SPSS production Facility

If we start SPSS for Windows, the following will be open. If a dialog box appears, click on Cancel or press the Esc key from key board. The dialog box will disappear low existing Windows is Data Editor Window.

Different types of important Window in SPSSData Editor: This is the first window that will appear when you start an SPSS session. You will see the Menu bar, the tool bar and other important contents of a data file.

Viewer Window: The viewer window is where we see the statistics and graphics the output form the work in SPSS. The viewer window is also called Output window is split into two parts or panes:

The Outline Pane (Left side of the viewer window)

The Display Pane (Right side of the viewer window)

Pivot table: Most of SPSSs tabular and statistical outputs appear in the viewer in the form of pivot tables. Double clicking a pivot table lets edit it.Chart editor: Double clicking a chart in the viewer will open the chart editor. Now we can modify the chart and even the chart type.

Syntax Editor: A syntax window is a window into which into which we can paste and/or write SPSS command. Then running the syntax on a data file we can get the desired output. To create a new syntax file, follow the steps:Click on File menu from the data window, Point the cursor to New and then click on syntax. (A Syntax Window will appear).

We can save the syntax Windows as well as output Window at our desire location simply by pressing Ctrl + S.

Various Types of Files in SPSS

SPSS reads, creates and writes different types of floes. Conventions for naming, printing, deleting or saving files and for submitting command files for processing differ from one computer to another or from one operating system to another. The following are some common files available in SPSS. Each file is used to store a particular type of information.

Types of fileExtensionPurpose

SPSS for data File or SPSS type fileSAVStores data along with the descriptive information of each variables and their values

SPSS syntax file or Command fileSPSContains various commands and instruction to perform various tasks. Sometimes it contains inline data.

Output fileSPOContains output/ results generated after executing commands through menu or syntax.

CREATING A DATA File in SPSSA data set is the organized or structured form of information obtained from experiments, surveys or other sources. Before starting data analysis in SPSS, it is important to be clear about how the variables are recorded for each case/individual.Note that in the organized or SPSS each column will represent a variable and each row

Will stand for a case/respondent/individual.

Naming a Variable:

The name of a variables should be short and mnemonic. A void using more than eight characters in naming a variable.

Give a label for the variable so that you can get a portrayal of the variable in the output.

Now well learn how to input data in SPSS. Lets do create a data file in SPSS using the information given bellow:IDNameReligionSexRegionHeightEducationMonthly

Income(TK)

1Pintu MuslimMaleDhaka67Higher120000

2JhonChristianMaleChittagong70Secondary8000

3MeenaMuslimFemale Barisal62Secondary9000

4RonjonHinduMaleKhulna71Illisterate3000

5HelalMuslimMaleRajshahi65Primary6000

6NancyChristianFemaleDhaka59Higher11000

7RadhaHinduFemaleChittagong64Secondary7000

8MintuMuslimMaleRajshahi57Illetarate4000

9RomeoChristianMaleKhulna68Primary5500

10TituMuslimMaleSylhet69Secondary10000

Sex: Male=1,Female=2Education: Illiterate=0,Primary=1,Secondary=2,Higher=3

Now explore GSS data File Gussset. Say Variables

Qualitative Economic status, religion

Nominal ID, Religion

Quantitative Age, family size

Ordinal Economic status

Interval IQ, marks

Ratio Age, Income

Md. Nurul Huda.

Mobile: 01822346868, 01673314980

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