interpreting results and presenting findings
DESCRIPTION
Interpreting results and presenting findings. Intermediate Food Security Analysis Training Rome, July 2010. Overview. Determining the question you want to answer Using your analysis plan Interpreting results from SPSS Visualizing findings Writing-up your analysis. - PowerPoint PPT PresentationTRANSCRIPT
Interpreting results and presenting findings
Intermediate Food Security Analysis TrainingRome, July 2010
Overview Determining the question you want to answer Using your analysis plan Interpreting results from SPSS Visualizing findings Writing-up your analysis
Determining the question you want to answer The key questions we typically try to answer
in a CFSVA are: Who are the food insecure people? How many are food insecure? Where do they live? Why are they food insecure?
For each question, we must first think about the analysis we need
Food and Nutrition Security Conceptual Framework
What is an analysis plan? The link with the conceptual framework that
sets out your hypotheses A table detailing data to be collected and how
those data will be analyzed A guide to the analytical process
Think back to your analysis plan Who are the food insecure people?
Cross-tabulate various demographic indicators with food consumption groups Sex of household head Dependency issues Education Etc.
Verify differences are significant using hypothesis testing Is the sex of the household head a significant factor
different between the food secure and the food insecure? Are households with a high percentage of dependents
significantly more food insecure? Does education significantly affect food security?
Thinking about an analysis plan How many are food insecure?
Run a frequency on food security groups Where do they live?
Cross-tabulate food consumption groups by strata Urban / rural Agro-ecological / livelihood zones (if available) Administrative zones (governorates, provinces, districts,
etc.) Always verify differences are significant using
hypothesis testing
Thinking about an analysis plan Why are they food insecure? (a bit out of scope for this
training, but good to think about) Keep the conceptual framework for food security analysis in
mind and explore the dataset using the tools you have available to you
Run hypothesis tests on the various data you have. For example: Exposure to shocks Coping strategies index Ability to cope with shocks
Wealth Access to credit Types of livelihoods
Access to markets Etc.
Use regression analysis (in the next training!)
Presenting results: a few pointers A good graph must convey statistical information quickly
and efficiently The minimum ink principle
Avoid images with 3-D effects or fancy shading. Use the minimum amount of ink to get your point across.
The small table principle A small table is better than a large graph. If you graph
contains 20 data points or less, use a table of numbers instead. The rule of seven
If a table has seven or more rows or columns, it probably has more information that can be easily interpreted
The fault of default principle Don't rely on the default options when creating graphs. Try
multiple versions until you get the right information presented
Presenting results: using color Danger in the use of color
Color should be avoided for ordinal data Shades work better with ordinal data
Bright colors can lead to optical illusions For example, areas in bright red sometimes appear larger
than areas in bright green Certain color combinations are difficult to distinguish
Blue against a black background Yellow against a white background
More than 8% of all males and more than 1% of all females are colorblind A red-green deficiency is most common
Color is often culturally biased
A few points about tables Show only two significant digits at most If possible, sort rows with the largest numbers
at the top If you’re showing the same rows (strata of
analysis) repeatedly, you should consider being consistent in the order of the rows
Use a table anytime you have 20 or fewer numbers.
Types of charts and their useChart Type Typical Use CommentsArea Cumulated totals (numbers
or percentages)Percentage, Cumulative
Column/Bar Observations over time or under different conditions; data sets must be small
Vertical (columns), horizontal (bars); multiple columns/bars, columns/bars centered at zero
Segmented Column/Bar Proportional relationships Total100%
Histogram Discrete frequency distribution
Columns/bars without gaps
Line, Curve Trends, functional relations Data point connected by lines or higher order curves
Pie Proportional relationships Segments may be pulled out of the the pie for emphasis (exploded pie chart)
Scatterplot Distribution of data points along one or two dimensions
One-dimensional, two-dimensional
Example of an area chart – FCS/ Food group composition
Food consumption score
Cons
umpt
ion
frequ
ency
Example of a line graph – migration by month
Oct
-08
Nov
-08
Dec
-08
Jan-
09
Feb-
09
Mar
-09
Apr-
09
May
-09
Jun-
09
Jul-0
9
Aug-
09
Sep-
09
Oct
-09
Nov
-09
50%
55%
60%
65%
70%
75%
80%
85%
90%
migration by month (households who has a migrant)
Urban Rural Total food insecure food secure
Example of a segmented bar graph – food consumption groups by marital status
married (several spouses)
single
married (one
spouse)
divorced/separated
widowed
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
8.8%
16.1%
11.8%
11.4%
18.8%
18.3%
14.6%
20.5%
26.7%
26.5%
72.9%
69.3%
67.7%
61.9%
54.8%
poor borderlineacceptablePercent Households
Interpreting results from SPSS Once you’ve created an analysis plan you can start your work in SPSS Each output of SPSS has a lot of information. Understanding these outputs is critical. What do the ANOVA results below tell you about share of food expenditure between urban and rural populations? What would you share in your findings?
Descriptives
share (%) food expenditure (out of the total)
N Mean Std. Deviation Std. Error
95% Confidence Interval for Mean
Minimum Maximum Lower Bound Upper Bound
Urban 1939 39.0292 16.10120 .36565 38.3121 39.7463 .00 88.11
Rural 4623 47.5104 20.58760 .30280 46.9167 48.1040 .00 100.00
Total 6562 45.0042 19.75194 .24384 44.5262 45.4822 .00 100.00
ANOVA
share (%) food expenditure (out of the total)
Sum of Squares df Mean Square F Sig.
Between Groups 98258.038 1 98258.038 261.841 .000
Within Groups 2461320.979 6559 375.259
Total 2559579.017 6560
Presenting your results
Urban / RuralMean share of food
expenditure
Urban 39.0%
Rural 47.5%
Total 45.0%
Never use SPSS outputs for sharing your results!
In this case, a very simple table can illustrate that rural populations spend a larger share on food than urban populations
In the text that describes the table, we can note the statistical significance (depending on our audience)
Table 1 – Average share of food expenditure by urban / rural
The results from the survey showed that rural populations significantly (p<0.05) spent a larger share on food than urban populations, 47.5% as compared to 39.0% respectively.
Sharing results Consider the table below. Does it clearly illustrate any
information?
Illiterate
no formal schooling
or incomplete but can read and
writePrimary
completedSecondary completed
higher completed
‘Ibb’ 42.1% 26.7% 12.4% 9.0% 9.7%
‘Abyan’ 34.3% 28.4% 14.2% 16.2% 6.9%
‘Sana'a City’ 18.3% 24.2% 12.8% 16.4% 28.3%
‘Al Bayda’ 46.8% 32.2% 9.8% 7.2% 4.1%
‘Taiz’ 44.8% 19.5% 8.7% 13.2% 13.7%
‘Hajja’ 51.8% 23.5% 11.3% 7.8% 5.6%
‘Hodeidah’ 61.8% 19.4% 9.9% 6.0% 2.9%
‘Hadramout’ 30.8% 27.8% 20.6% 12.8% 8.1%
‘Dhamar’ 57.3% 23.0% 8.3% 7.0% 4.4%
‘Shabwa’ 32.2% 31.5% 16.4% 13.2% 6.8%
‘Sana'a’ 41.9% 32.5% 10.3% 8.3% 6.9%
‘Aden’ 21.0% 19.6% 15.1% 24.7% 19.6%
‘Lahej’ 35.2% 28.8% 10.5% 18.0% 7.5%
‘Mareb’ 38.2% 26.6% 13.3% 14.0% 7.9%
‘Al Mahweet’ 59.5% 20.8% 8.1% 6.7% 4.9%
‘Al Mahra’ 42.3% 26.7% 15.6% 11.4% 4.0%
‘Amran’ 49.0% 24.6% 9.1% 9.4% 7.8%
‘Ad Daleh’ 38.0% 21.4% 16.2% 15.5% 9.0%
‘Rayma’ 57.2% 27.5% 5.1% 7.1% 3.1%
Total 43.8% 24.0% 11.3% 11.1% 9.8%
What is the highest educational level completed by Household head?
Governorate
Sharing results Generally speaking, ‘the rule of seven’ should be applied during
report writing. If a table has more than six rows or columns, it probably has more information that can be easily interpreted. Consider creating a graphic or creating a table with just the pertinent information
Sharing results Simply sorting data can make a graph much easier to read
and can quickly highlight the point you are illustrating What is missing from this table?
Figure 1: Education level of household head by Governorate
Writing up your results Always remember the question you are trying to
answer when writing. Have a solidly defined report structure prepared before
you write. The analysis plan can help you with this Don’t make assumptions that you cannot backup Think of the results as telling a story. You need to build
your findings over the course of the story and transition from section to section as fluidly as possible. Use the conceptual framework to guide you.
Use visual aids to highlight your points, but don’t rely on them to do all the work. Make sure you have meaningful titles
Get your colleagues to review your work!