1. ANALYZING QUANTITATIVE DATA WITH SPSS
© Susan Mowers
Spring 2016

2. Overview Working with quantitative data Introducing SPSS
Elements of your descriptive analysis
Before SPSS, check your data literacy:
Who do the data cover? When/where was it gathered? Was it a sample, of whom?
What do the data mean?
Or in other words, the background story to your analysis, and the write-up of your methodology
Descriptive statistics 101
Archive your work
Weights
Selected options for presenting data
ICPSR data research materials for students…
Quantitative analysis has two aspects: Descriptive statistics (Description or summarization of or showing the data at hand), According to the data from the 2006 Census, women are twice as likely to be single parents if they live in Ontario, and three times as likely in ??) , and inferential statistics (prediction), single parent mothers … On the other hand,

3. Learning outcomes
Find out what files you need to do basic SPSS quantitative analysis
Learn how to capture your files and your work
Learn what elements you can use for a descriptive analysis of your quantitative data.
Learn what learning tools ICPSR has to offer for quantitative research
Capture your files and work
–for working effectively and being able to back up your research results

4. Working with quantitative data
You need to know the source and methods for your data
What is the basic information, Statistics Canada web site: [StatsCan Page for the CCHS]
What about the rest of the detail? See <odesi> for your data and documentation
Why do you need to gather various files before you get started in SPSS?
Understand what the data represent – Are they meaningful to your research question?
Be prepared to answer how you arrived at your results – Are your results replicable / valid?
Keep your work every day in one place! Double-check regularly: are your files backed up?
Make sure the data license allows you to share your data with the rest of your research team and supervisor
Describe your methodology: Cite your data!! Name your key variables / measurements. Are they different from the original data? Can you provide your SPSS code of your work to your professor or team-mates?

5. Introducing Spss Benefits of SPSS?
Easy to learn
All the benefits of the computing syntax code behind your GUI-driven statistics
Designed for social science data
SPSS supports labels, declared missing values and so on,(good data markup) e.g.,:
Label: Legal Marital Status for the variable DHHGMS,
Label: Married for the value 1, Common-law for the value 2, …. The labels will show up on your tables and graphs!
Missing value: 9 = Not stated, required so that SPSS will treat 9 as a « missing value, and not as a valid value
SPSS also supports weighting
Caution: labels and missing values should be declared by the data producer/provider, but they still need to be checked.
Non-SPSS file formats? Conversion! Make sure you retain
SPSS installed in:
Vanier labs,
3rd floor Morisset lab, and
FSS Library (FSS 2010).
SPSS = graphical – pull-down menus
+ syntax code to re-run … you and your supervisor or instructor or readers of your research articles can re-run your statistics
Research replication
Non-SPSS file formats ? Conversion options Can you import or transfer to SPSS .sav ?
SPSS supports some « codebook information »
Non-SPSS file formats? Conversion! Check to see if the original file has data labels?
Note that .sav is a standard SPSS data file. .por is a portable SPSS file
Labels are essential for your descriptive statistics which is partly about showing your statistics, either through statistical tables or in graphs!

6. DATA documentation
QUESTIONNAIRE
CODEBOOK

7. Must-have files for descriptive analysis using spss
User guide is prefered over Statistics Canada survey page. It answers:
SURVEY METHODOLOGY QUESTIONS:
Does the survey cover the right population and time period?
Who (target population, response rate) When data gathered/covered, Why, (e.g, health planning, policy and services) How (survey design/method)
This is the background to your research story!
Codebook, Questionnaire… They answer:
What is the size of the sample?
Does the survey cover the right concepts and measurements?
Will you need to do more work (and how) on the data before it is ready to analyse?
What is the weight variable?
SPSS data file (either the full dataset or a subset)
Note:
Main products for descriptive statistics (SPSS, Stata, SAS, even Excel – note collectica version)
Descriptive statistics describe, summarize and show the data – they don’t allow for predictions beyond the data

8. Analyzing quaNTITative data through descriptive statistics
Descriptive statistics describe, summarize and show the data
Do you know your types of data? Why does it matter?
Averages won’t work with data that reflect qualitative / categorical values, e.g., « Gender » or « Highest education level », but they will work with quantitative values, e.g., « Positive mental health continuous scale », « Years of education » or « Earnings income (in dollars) ».
Types of data?
Nominal Married, Common-Law, Divorced-separated, Single/Never married
Ordinal Less than high school, High school, Some post-secondary, Post-secondary grad.
Interval-ratio $15,000 - $29,000 (as one of 10 levels of income, in equal income ranges of $14.999)
Continuous : Positive mental health continuous scale,
Main products (SPSS, Stata, SAS, even Excel – note colectica version of Excel)
Descriptive statistics don’t allow for predictions beyond the data itself
Qualitiative variables: Numbers have no meaning, nominal groups are unordered, ordinal groups are ordered
Quantative variables: numbers have meaning, spaces between numbers are equal

9. Importing data sources
Documents (.pdf)
SPSS file (.sav)
Note, our SPSS file is a subset of the variables we are analysing
Syntax file (.sps)
Log/output file (.spv)
The full file has 1381 variables, ours has xx including two new variables I created to prepare the data for this workshop.

10. Hands-on Import files to your work area
Create a folder called spss on your computer desktop
Go to
Right click on files.zip. Save the file to the desktop: Save target as and select Desktop
Right click on files.zip and follow the instructions to Select a Destination and Extract the files.

11. Hands-on Open the data Under folder data
Double-click on the file cchs2012_spssgrad.sav

12. Descriptive statistics 101
What do the data have to say about our categorical values?
Use Frequencies for categorical values (e.g., maritial status, body mass index groups, education levels, …)
For nominal values and ordinal values
Distribution in raw numbers and percents (ratios),
Select statistics: mode for nominal values
Select statistics: median and mode for ordinal values
Frequencies for age groups and education level
The mode (most typical)
Descriptives for Positive mental health continuous scale
Cross-tabulation (percentages) two categorical variables
BMI nominal overweight, underweight, just about right (do you considder yourself)
Means
Compares the average (mean) between groups
Use when one variable is interval and the other is ordinal or nominal
E.g. Who is higher educated, married men or married women? (married men/women is a recoded/derived value that I created)

13. Hands-on
Let’s do a frequency table for a categorical value … chose from:
Marital status – (G)
DHHGMS
(nominal)
Body mass index
BMI class (18 +)
HWTGISW
(ordinal)
Highest education lev/ HH 4 levels
EDUDH04
Note, I have filtered out respondents aged years
Data file: ages 18 and over

14. Menu method for frequency + USING paste to syntax (best practise)
Click on Analyse
Click on Descriptive statistics
Click on Frequencies
Select your variable, using the right arrow
Click on Statistics
Select Mode, and if relevant, Median
Click Continue
Click Paste
Run your command in your Syntax editor (highlight and click on right arrow at top)
FREQUENCIES VARIABLES=HWTGISW
/STATISTICS=STDDEV MEDIAN MODE
/ORDER=ANALYSIS.

15. WHAT ARE Sample weights?
Unweighted Frequencies
Describe the distribution of your survey respondents’ legal marital status
Weighted Frequencies
Describe the distribution of your target population’s (Canadians) legal marital status

16. Hands-on Turn on the weight
Pull down menu: Data then
Scroll down and select Weight cases
Paste to your syntax editor
Re-run your frequencies, pasting again into your syntax editor
You now have population estimates for your data!
Weighted frequencies can be used as research results
We will keep the weight turned on for the rest of our descriptive statistics workshop.
Best practise: by pasting your code into your syntax editor, you can clearly see if your data is weighted or not

17. Descriptive statistics 101
What do the data have to say about our continuous variables?
Use a histogram for a continuous variable to show the distribution …
Continuous variables: Positive Mental Health Continuous Score and Body mass index scale
Note: Higher scores in the two categorical values above indicate
higher levels of positive mental health and
higher ratios of weight to height, so higher on the scale for overweight compared to underweight.
Frequencies for age groups and education level
The mode (most typical)
Descriptives for Positive mental health continuous scale
Cross-tabulation (percentages) two categorical variables
Means
Compares the average (mean) between groups
Use when one variable is interval and the other is ordinal or nominal
eg. Who has a more positive mental health score, men or women?
Underweight = <18.5 Normal weight = 18.5–24.9 Overweight = 25–29.9 Obesity = BMI of 30 or greater

18. Hands-on
Let’s do a histogram to show the distribution of positive mental health
Positive Mental Health Continuous Score
PMHDSCR
(continuous) OR
Body mass index scale
BMI / self-report - (D,G) HWTGBMI
Note, Respondents aged years have been removed from the data

19. Menu method for frequency + USING paste to syntax (best practise)
Click on Graphs
Click on Legacy dialogs
Chose Histogram
Click on your variable of interest and use the right arrow
Optional: If you want separate histograms for different groups, e.g., married and single, you can put an additional variable (e.g, Sex or Married respondents (not single)) in the Panel by: are. Chose rows if you would like the two graphs on top of each other, or Column if you want them side by side. Click on Statistics
Click Paste
Run your commands in your Syntax editor (highlight the commands and click on right arrow at top)
GRAPH
/HISTOGRAM=PMHDSCR
/PANEL ROWVAR=MARRIED ROWOP=CROSS.

20. Show your data (descriptive statistics), e.g., histogram

21. Descriptive statistics 101 ACCORDING TO OUR DATA … Continuous variables, part 2
Run basic Descriptive statistics for continous variables, e.g.
Click on Pull-down menu Analyse
Click on Descriptive statistics
Click on Descriptives
Click on the continuous variable(s) you want, like Postitive Mental Health Continuous Score and click on right arrow
Click on Options to the right. Select Minimum, Maximum, Mean (=average), and for more advanced users, Standard deviation
Note: your weight should still be turned on. If not, turn it back on.
Click on Paste, and then in Syntax editor, Run your syntax
Frequencies for age groups and education level
The mode (most typical)
Descriptives for Positive mental health continuous scale
Cross-tabulation (percentages) two categorical variables
Means
Compares the average (mean) between groups
Use when one variable is interval and the other is ordinal or nominal
eg. Who has worked longer at their job, men or women?

22. Descriptives
Weighted:

23. Quick note: Standard deviation
From Math is Fun:
“The Standard Deviation is a measure of how spread out numbers are” and “what is normal and more extreme”.
From data on the height of group of dogs …
Calculate the mean and variance
Calculate the variance (square of differences), then average of the sum of differences)

24. Descriptive statistics 101 ACCORDING TO OUR DATA …
Does marital status reflect gender differences in attractiveness (age, body mass index) and education level?
Bar graph - Show
Cross-tabulation - Summarize
Frequencies for age groups and education level
The mode (most typical)
Descriptives for Positive mental health continuous scale
Cross-tabulation (percentages) two categorical variables
Means
Compares the average (mean) between groups
Use when one variable is interval and the other is ordinal or nominal
eg. Who has worked longer at their job, men or women?

25. Hands-on
Let’s use
a bar graph for categorical variables

26. Descriptive statistics 101: Categorical variables, continued
Create Bar graphs to show the relationship between two categorical variables
one is a re-code: married men and married women
Let’s compare age pyramids for married men versus married women
Click on Graphs
Select Legacy Dialogs.
Chose Bar
Click on Clustered
Click on Define
Click on % of cases
Select Married by gender > Category axis
Select Age – (G) > Define Clusters by
Click Paste and Run in your Syntax editor as usual

27. CLUSTERED AGE GRAPH for Married men vs. Married women (AGE PYRAMIDs)

28. Hands-on
Let’s use
Summary statistics to compare distribution of age groups of married men versus married women
Cross tabulation

29. Descriptive statistics 101: Categorical variables, continued
Create a cross tabulation to show correlation between two categorical values
Let’s compare summary statistics of age groups for married men versus married women
Click on Analyse
Select Descriptive statistics
Choose Crosstabs
Select Age – (G) > Rows
Select Married by gender > Columns
Click on Cells
Unselect Observed for Counts
Click on Column for Percentages
Click on Continue
Click Paste and Run in your Syntax editor as usual

30. Descriptive statistics 101: Categorical variables, last slide
Note: you could group age groups into 15 year intervals for example, for a simpler crosstab

31. reSources for your research projects
Where to find data and its must-have documentation?
Odesi – Canadian
ICSPR – International
Ask me: Susan Mowers, Your Data Librarian or
© Susan Mowers
2016