Quantitative and Qualitative Research


The "Data Collection Procedures," which are the "step-by-step action plan" for how you will collect your information. This would be something like the following: "On Friday, May 27, 1998, the researcher and two assistants went to School X to administer the XYZ Test of Motivational Level. They administered the test to two classes of 30 fourth graders apiece. The test took 2 1/2 hours to complete." Notice how you are sort of documenting, "journalism class" style, the who-what-when-where of the process of data collection ... so that an outside reader could picture and hopefully reproduce all the steps you took to gather your data.

The "Data Analysis Procedures: "ah, the 'fun stuff!"
This describes how you compiled and analyzed your data, or information, to answer your research question(s)!

We usually think of statistical procedures, but it's only one way, as you will see below.

For quantitative data (information in numbers), you could have:

1. Summary Descriptive Statistics: You sort of "tally up" and present as a "numeric profile:" e.g., means, totals, percentages, and the like. You don't 'test' these: they are just meant to give a broad general summary numeric picture of your data. For instance: how many (total and percent) of subjects in your sample were men and how many were women.
2. Inferential (also called Analytic Statistics): would be the "testables," some of which we'll be learning in Intro to Statistics! For instance, say that you find an average difference in science aptitude test scores between the sixth-grade boys and girls IN YOUR SAMPLE. But say, also, that you want to use this SAMPLE result to see if the same thing would be true FOR THE ENTIRE POPULATION of sixth grade boys and girls in the state (from which you drew this sample and to which you wish to 'project' or 'generalize' the findings/results). Could your sample have been 'just a flukey one?' That is: you do get an average science difference in your sample, but it would NOT hold up in the POPULATION AT LARGE? or is your sample quite representative of this population, so that you CAN confidently predict that the SAMPLE difference in average science aptitude WOULD hold up in the POPULATION AT LARGE? You'd be using an "inferential" or "analytic" statistic (in this case, something called an "independent-samples t-test" -- stay tuned in Intro to Statistics! It'll be coming) to make this decision about "what to assume about the population based on sample results"
   
   But there's another form that data, or information, can take! What if these data are NOT in numbers, but in the form OF WORDS -- that is, qualitative?!

Examples of Qualitative Data:

• Journal notes recorded by teachers who are writing down their day-to-day impressions regarding a new form of teaching reading;
• Written answers to open-ended survey items sent through the mail to sample subjects;
• Existing documents, such as the policy manuals from the three districts described earlier.

If you have qualitative data, you would also describe, under Data Analysis Procedures, how you will summarize and compile these data to address your research question!

There is a third possibility: why not have the best of BOTH worlds? and collect both numeric (quantitative) and verbal (qualitative) data to address your problem statement?!

This is an exciting new direction of research called "multimethod research!"

Having the data both ways in essence is like a "2nd medical opinion," or "2 pieces of evidence (favoring innocence of client) in a jury trial!"

With more than one piece of evidence, you can have greater confidence in the "answer" to your research question(s) if both the numbers and words appear to "point in the same direction!" This is called "convergence" or "triangulation" of the alternative data sources!

Example: You wish to identify the general direction and level of attitudes towards a new teacher incentive program in your school district. You decide to collect the data 2 ways:

1. having the teacher-subjects rate a group of items reflecting their attitude on a 1-5 scale; AND
2. interviewing a small sample of teacher-subjects, letting them express, in their own words and in response to open-ended interview questions, their attitudes.

You compare the above 2 sets of results and find:

1. the teachers who completed the rating scale items on the attitude survey are, on average, giving "moderately favorable" and "very favorable" attitude ratings to the items; AND




2. in the interview sessions, the interview subjects are choosing to voice primarily positive attitudes in the opinions they share with the interviewer.

Go on to Assignment 1: Quiz: Quantitative and Qualitative Research
or
Go back to Collecting and Analyzing Data

E-mail M. Dereshiwsky at statcatmd@aol.com
Call M. Dereshiwsky at (520) 523-1892

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