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Saturday, April 30, 2016
Theory of spss
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SPSS OMS Tutorial – Creating Data from Output
SPSS OMS (short for Output Management System) can convert your output to SPSS datasets. As we'll demonstrate in a minute, this can save you huge amounts of time, effort and frustration.
We recommend you follow along by downloading and opening course_evaluation.sav, part of which is shown below.
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Today’s Challenge
Some client wants to see charts holding correlations of q2 through q6 with q1 for each study major (psychology, anthropology) separately as shown here. This request -not unusual in market research- typically makes novice SPSS users
panic,
run the correlations in SPSS,
copy/paste everything into Excel sheets and
generate the charts one by one.
Unknown to many SPSS users, there's a much -much- faster way for getting this job done. It's called OMS.
Step 1: Split File
We'd normally always start with a routine data inspection but that's been done for you in this case. Now, a fast way for just running the desired correlations is by using SPLIT FILE. The syntax below shows how to do so.
Step 2: OMS Control Panel
Right, we created our correlations but they're in our Output Viewer window. We can't create charts from tables in our output window so we need this correlation table in data view instead.
We'll do just that by navigating to Utilities SPSS Menu Arrow OMS Control Panel which is shown below.
We'll follow the steps in the screenshot: we select our correlation table in the left half of the dialog.
It's a best practice to always specify an ID here. In this case, “corid” is short for “correlation id”
We then select New Dataset in the right half of the dialog. “cords” is short for “correlation dataset”.
Clicking Paste triggers a popup dialog confirming our OMS request. Just ignore it.
Clicking Ok then generates the first block of the syntax below. We then (manually) added two lines to it.
SPSS OMS Syntax Example
SPSS OMS Syntax - How Does It Work?
The next figure explains how our syntax basically works. In a nutshell,
the OMS command has SPSS monitor selected output following it so
our correlation table is captured by the OMS.
OMSEND then stops SPSS from monitoring output and create our desired correlations dataset.
SPSS OMS - OMS Syntax Explained
Result
SPSS OMS -
We now have our correlation matrix in an SPSS dataset, which allows us to run charts on it. We'll prepare these data a tiny bit before doing so with the syntax below.
*1. Activate newly created correlations dataset.
dataset activate cords.
*2. Delete all rows that don't hold correlations.
select if char.index(var3,'Pearson') > 0.
execute.
*3. Split file by var1
smile emoticon
study major).
sort cases by var1 howdoyouratethiscourse.
split file by var1.
Step 3: Creating Our Charts
We'll now create our desired charts by following the figure below. Since we're using SPLIT FILE, we need only one single command for creating all charts at once.
SPSS OMS -
In the second dialog (below), choose a nice main title for your charts. We decided upon “Correlations with Course Rating”.
SPSS OMS -
Following these steps results in the syntax below. Running it generates all desired charts.
SPSS Bar Chart Syntax Example
*Create actual charts.
GRAPH /BAR(SIMPLE)=VALUE(Howdoyouratethiscourse) BY Var2/title 'Correlations with Course Rating'.
Step 4: Prettifying our Charts
We now have the charts we wanted. A nice trick to make them look great with little effort is creating a chart template for them.
We double click just one of our charts and transpose it as shown below.
SPSS OMS -
Next, we change the colors, fonts, layout, everything in our first chart until it looks nice. Then navigate to File SPSS Menu Arrow Save Chart Template as explained in SPSS chart templates.
SPSS - Creating Pretty Charts
Finally, we activate the chart template we just created (step 3 below, first set path to .sgt file correctly). We then rerun the GRAPH command we pasted and ran previously and - there you go - five pretty charts in a split second.
If you ever get a similar request for different data, you can now rerun your syntax on it and you'll be done in seconds. As a bonus, you can probably (edit and) reuse your chart template other bar charts too.
Final Syntax Using Chart Template
*1. Apply variable label (shows up in chart subtitle).
variable labels var1 "Study Major".
*2. Suppress excessive decimal places.
formats howdoyouratethiscourse (f1).
*3. Activate newly created chart template (set path appropriately).
set ctemplate 'my-project-folder\my-template.sgt'.
*4. Rerun all graphs at once with chart template.
GRAPH /BAR(SIMPLE)=VALUE(Howdoyouratethiscourse) BY Var2/title 'Correlations with Course Rating'.
*5. Switch off chart template for any future graphs.
set ctemplate none.
Final Result
SPSS OMS -
Final Notes
SPSS OMS can be a tremendous time saver. Today's tutorial redirected a single correlation table to an SPSS dataset but you can very easily create a single dataset holding output from 1,000 or more output tables. In fact, we did just that in the simulation studies we presented when explaining the basic idea behind ANOVA, regression and the chi-square test. In these studies we basically
used one OMS command for capturing all ANOVA tables,
ran ANOVA on 1,000 random samples from a population data file,
ran OMSEND for creating a dataset with 1,000 F-values and
created a histogram for visualizing our sampling distribution.
As we see, SPSS OMS opens up a lot of possibilities. We hope it'll help you save time and effort as well!
BASIC COURSE CONTENT OF SPSS
Basic SPSS
1. Introduction
- About SPSS
- Defining Variables: Qualitative and Quantitative Variables
- Brief Concept of Measurement of scale
- Entering Data in the SPSS Spreadsheet
- Importing and Exporting Data
- Coding the Data
2. Data Management
- Inserting and deleting cases and variables
- Sorting cases
- Select Cases with and without random sampling
- Data Transformation
- Computing New Variables
- Re-Coding
3. Data Processing and Tabulation
- Presentation and Tabulation of Data
- Summarizing Data
- Descriptive Statistics
4. Data Exploration
- Box and Whisker plot
- Histogram with Normality Plot
- Stem and Leaf Plot
5. Graphical Presentation
- Concept of Charts and diagrams
- Simple, sub-divided, Multiple diagrams
- Pie-Charts
- Scatter/Dot Plots
- Popularity Pyramid
6. Analysis I
- Cross Tabulation for
- Two Attributes
- Three Attributes
7. Analysis II
- Concept of Estimation and Hypothesis Testing
- T-test for single Mean
- Z-test for single Mean
- T-test for Difference of Two Means
- Z-test for Difference of Two Means
- Paired t-test for single Means
- One way ANOVA
- POST-HOCK tests
WHAT YOU REQUIRE:
Interested organizations/institutions/individuals are expected to have laptop(s) while attending the workshop, and individuals attending should be from any discipline. Please feel free to bring your own datasets for practice while performing the tasks demonstrated by the trainer. If you have SPSS already installed on your machine the better. However it is not a must because you will be provided with a temporary version for the training.
Further more details:
Friday, April 29, 2016
basic course content of SPSS
COURSE CONTENT:
The course is organized in modules and each module covers a reasonable content to enable participants connect and progress successively in the next modules.
Module 1: SPSS interface and features
Module 2: Data storage types, measures & data management in SPSS
Module 3: Creating & editing quantitative & categorical graphs/charts
Module 4: Advanced data tabulation
Module 5: Point estimation & hypotheses testing
Module 6: Inferential analysis
Module 7: Analysis I/II
Advance SPSS Course content
Advance SPSS Course
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Defining Variables
Measurement of scale
- Nominal
- Ordinal
- Interval
- Ratio
Explorative Data Analysis
- Histogram
- Box and whisker plot
Data management
- Sort Cases
- Merge Files
- Select Cases
- Weight Cases
- Split Files
- Identify Duplicate Cases
- Identify Unusual Cases
- Define Multiple Response Sets
- Transpose
Transformation
- Compute Variables
- Record into Same Variables
- Record into Different Variables
- Rank Cases
- Create Time Series
- Replace Missing Values
- Random Number Generator
Report and Descriptive Statistics
- Cases Summaries
- Crosstabs ( Simple Bi-Variate Frequency Analysis)
Cross Table (Advanced Classification Analysis)
- Chi-Square Tests for Independence of Attributes
- Degree of Association for Multi-variate Nominal Attributes
- Degree of Association for Multi-variate Ordinal Attributes
Cross Table II(Advanced Classification Analysis)
- Tests of agreement between two or more attributes [Kappa, Risk(Relative Risk)]
- Mo-Nemar’ Test (A non- parametric test for related sample)
- Association between nominal and interval type data (Measured by statistics: Eta)
- Cochran’s and Mantel-Haenszel Statistics
Regression Analysis I
- Simple Linear Regression
- Curve Estimation
Thursday, April 28, 2016
course details of spss
Course: Statistical Package for the Social Sciences (SPSS)
Duration: 20 hours
Time: 1 hour/day( Theory + Practical)
Introduction
SPSS COURSE Statistical Package for the Social Sciences (SPSS) is a comprehensive and flexible statistical analysis and data management solution produced by IBM and makes statistical data analysis straightforward. SPSS can take data from almost any type of file and use them to generate tabulated reports, charts, and plots of distributions and trends, descriptive statistics, and conduct complex statistical analyses spss training in lalitpur
WHY THIS SPSS COURSE?
SPSS is a widely used program for statistical analysis in social science. SPSS is a powerful suite of data analytics, reporting and modeling software. It is the data analytics software package of choice for people who need to analyze large amounts of quantitative data and is used as standard by a wide range of users who need to quickly and accurately carry out statistical analysis of that data such as market researchers, health researchers, survey companies, government, education researchers, marketing organizations and data miners. spss training in kathmandu
SPSS functionality ranges from simple plots and charts; through to much more sophisticated statistical tests. Although very broadly applicable, SPSS is very well-suited to analyzing survey data. It has a very broad range of applications from the relatively simple like calculating frequencies and creating lists and charts through to the far more advanced like variance analysis, multivariate statistical analysis and cluster analysis. It is also useful in building predictive models. spss training in nepal
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