Introduction to Data Analysis Handbook - AED Center for Early Care ...

What has been evident in disciplines such as education, public health, nutrition, nursing,
and management, is now becoming evident in early care and education, including Head
Start. Programs now recognize that the quality and quantity of data, be it statistical or
descriptive, is needed to set baselines, identify effective actions, set goals and targets,
monitor progress and evaluate impacts (World Bank Website http://www.worldbank.org/
data/aboutdata/aboutdata.html).
one thing that Migrant and Seasonal Head Start programs can do well is gather data.
Using an upstream program as an example, in late May the data gathering process is swift
and fast during enrollment. if the data relates to a child or family it is shared among
appropriate Head Start staff. When the program ends, the data is stored, and next thing
you know it is March and the program is preparing for pre-service. The question that
one is always left with is: what do we do with all this data and or information? one of the
goals of this handbook is to help you answer this question.
Before you can present and interpret information, there must be a process for gathering
and sorting data. once again, 1,099 is a number - and this number is, in fact, data. The
number 1,099 is a raw number - on its own it has no meaning. Just like many of the crops
that our families pick are raw from which food is prepared, so too, can data be viewed as
the raw material from which information is obtained.
Head Start requires the collection of data in a variety of areas. We collect data in all
of the content service areas. Thus, data collection is something that is not just limited
to children and families, but if the purpose and the questions relate to children and
families it is definitely not good practice to collect data when the children and families
are not available. The data you collect in Head Start can take many forms. The data
could be in the form of numbers, words, pictures, maps, and even newspaper articles.
When collecting data, we are faced with the inevitable question of which is better. The
concept of which is better has the potential to lead to the qualitative versus quantitative
debate, which although exhilarating to some, could cause havoc in program planning and
implementation. These debates fail to achieve an honest understanding of how qualitative
and quantitative data differ, because in many people’s mind the difference between the
two is underscored by the notion that one is better than the other.
Why the Soliloquy? Types of Data
in research circles there has been a long-term debate over the merits of Quantitative
versus Qualitative data. Key influences in this debate are based upon how researchers
were taught, compounded by differences among individuals and their preference in
relating to numbers or to words.
in reality, this debate is largely irrelevant in Head Start. in order to have a high quality
program, we must collect both types of data. There are times when a quantitative
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© AED/TAC-12 Spring 2006. Permission granted to copy for non-commerical uses only.