This document provides training on using SPSS for basic drug abuse data management and analysis. It outlines how to open SPSS, define variables in Variable View, and enter data in Data View. Key aspects of variable definition include the name, type, width, decimals, label, values, missing values, columns, align, and measure of a variable. The document demonstrates defining variables for identification number and age, and entering sample data. It emphasizes that the SPSS file must always be saved to preserve work.
SPSS for beginners, a short course about how novices can use SPSS to analyze their research findings. With this tutorial anyone becomes able to use SPSS for basic statistical analysis. No need to be a professional to use SPSS.
SPSS for beginners, a short course about how novices can use SPSS to analyze their research findings. With this tutorial anyone becomes able to use SPSS for basic statistical analysis. No need to be a professional to use SPSS.
SPSS is widely used program for statistical analysis in social sciences, particularly in education and research. However, because of its potential, it is also widely used by market researchers, health-care researchers, survey organizations, governments and, most notably, data miners and big data professionals.
The power point presentation is about SPSS Software. It shows how to enter the data and to upload the data from external sources into SPSS. The presntation also shows how to save the files in excel form and in .sav form.
This presentation demonstrated the fundamental of SPSS for beginner to learn what is SPSS and how to create variables and define their definition.
Thank you for your interest.
Please contact for more detail.
SPSS is widely used program for statistical analysis in social sciences, particularly in education and research. However, because of its potential, it is also widely used by market researchers, health-care researchers, survey organizations, governments and, most notably, data miners and big data professionals.
The power point presentation is about SPSS Software. It shows how to enter the data and to upload the data from external sources into SPSS. The presntation also shows how to save the files in excel form and in .sav form.
This presentation demonstrated the fundamental of SPSS for beginner to learn what is SPSS and how to create variables and define their definition.
Thank you for your interest.
Please contact for more detail.
Adjusting primitives for graph : SHORT REPORT / NOTESSubhajit Sahu
Graph algorithms, like PageRank Compressed Sparse Row (CSR) is an adjacency-list based graph representation that is
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Data Centers - Striving Within A Narrow Range - Research Report - MCG - May 2...pchutichetpong
M Capital Group (“MCG”) expects to see demand and the changing evolution of supply, facilitated through institutional investment rotation out of offices and into work from home (“WFH”), while the ever-expanding need for data storage as global internet usage expands, with experts predicting 5.3 billion users by 2023. These market factors will be underpinned by technological changes, such as progressing cloud services and edge sites, allowing the industry to see strong expected annual growth of 13% over the next 4 years.
Whilst competitive headwinds remain, represented through the recent second bankruptcy filing of Sungard, which blames “COVID-19 and other macroeconomic trends including delayed customer spending decisions, insourcing and reductions in IT spending, energy inflation and reduction in demand for certain services”, the industry has seen key adjustments, where MCG believes that engineering cost management and technological innovation will be paramount to success.
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According to M Capital Group: “Specifically, the long-term cost-saving opportunities available from the rise of remote managing will likely aid value growth for the industry. Through margin optimization and further availability of capital for reinvestment, strong players will maintain their competitive foothold, while weaker players exit the market to balance supply and demand.”
Quantitative Data AnalysisReliability Analysis (Cronbach Alpha) Common Method...2023240532
Quantitative data Analysis
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Common Method Bias (Harman Single Factor Test)
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Descriptive Analysis
1. SPSS data entry
Training session 3
GAP Toolkit 5
Training in basic drug abuse data management
and analysis
2. Objectives
• To describe opening and closing SPSS
• To introduce the look and structure of SPSS
• To introduce the data entry windows: Data View and
Variable View
• To outline the components necessary to define a
variable
• To introduce the SPSS online tutorial
6. Opening SPSS
• Double click the SPSS icon on the desktop
OR
• Start/Programs/SPSS for Windows/SPSS**
• The following introductory screen should appear:
7.
8. The Data View window
View tabs
Status bar/boxes
Cell edit field
Cell information
9. Data View
• Rows represent cases or observations, that is, the
objects on which data have been collected:
– For example, rows represent the contents of a single
treatment data collection form, the information on an
individual
• Columns represent variables or characteristics of the
object of interest:
– For example, each column contains the answers to the
questions on the treatment data collection form: age, gender,
primary drug of use, etc.
10. Data Editor
• Data Editor comprises two screens:
– Data View: the previous screen
– Variable View: used to define the variables
• To move between the two:
– Use the View tab at the bottom of the screen
OR
– Ctrl + T
OR
– View/Variables from the Data View window
– View/Data from the Variable View window
12. • Define your variables in Variable View
• Enter the data, the values of the variables, in Data View
The data entry process
13. Definition of variables
10 characteristics are used to define a variable:
Name Values
Type Missing
Width Column
Decimals Align
Label Measure
14. Name
• Each variable must have a unique name of not more
than 8 characters and starting with a letter
• Try to give meaningful variable names:
– Describing the characteristic: for example, age
– Linking to the questionnaire: for example, A1Q3
• Keep the names consistent across files
15. Type
• Internal formats:
– Numeric
– String (alphanumeric)
– Date
• Output formats:
– Comma
– Dot
– Scientific notation
– Dollar
– Custom currency
17. String (alphanumeric)
• String variables contain words or characters; strings can
include numbers but, taken here as characters,
mathematical operations cannot be applied to them
• The maximum size of a string variable is 255 characters
18. Date
• The input format for date variables must be defined,
such as DD/MM/YYYY, MM/DD/YYYY or MM/DD/YY
• Computers store dates as numbers from a base date; in
SPSS, dates are stored as the number of seconds from
14 October 1582
19. Example
• Create two variables:
– ID: the unique identifier, which will be alphanumeric with a
maximum of 8 characters
– Age: the age of the respondent measured in years, a
discrete variable ranging between 10 and 100
28. Missing
• Defines missing values
• The values are excluded from some analysis
• Options:
– Up to 3 discrete missing values
– A range of missing values plus one discrete missing value
29. Click in the Missing Values column to obtain the dialogue box below. Enter the value 999 for Age.
31. Columns and Align
• Columns sets the amount of space reserved to display
the contents of the variable in Data View; generally the
default value is adequate
• Align sets whether the contents of the variable appear
on the left, centre or right of the cell in Data View
• Numeric variables are right-hand justified by default and
string variables left-hand justified by default; the
defaults are generally adequate
32. Measure
• Levels of measurement:
– Nominal
– Ordinal
– Interval
– Ratio
• In SPSS, interval and ratio are designated together as
Scale
• The default for string variables is Nominal
• The default for numeric variables is Scale
33. Returning to Data View, the first two column headings will reflect the two variables created: ID and
Age. Here the first six observations have been entered.
35. Saving the file
• The file must always be saved in order to save the work
that has been done to date:
– File/Save
– Move to the target directory
– Enter a file name
– Save
36.
37. Summary
• Data Editor
– Data View
– Variable View
• File/Save
• Variable definition
– Name
– Type
– Width
– Decimals
– Label
– Values
– Missing
– Columns
– Align
– Measure