DAT - Data Origination (Lesson)

Data Origination

Where Does Data Come From?

Data is found everywhere and is not new. The newness of data is the amount of data that is accumulating on a daily basis. Here are two examples of data collection.

  1. A farmer buys 100 trees to plant in an orchard to grow oranges for sale.  
    • The farmer's data.
      • The 100 trees as tangible items.  
      • The cost of the total purchase and the cost of each tree.
      • Maybe the location the tree is planted in?
    • The data created at the merchant, the farm store, for the transaction.
      • Quantity sold
      • Item bought (could include description and specific code)
      • How many of the item bought
      • Individual item sale price
    • Data already known by the merchant and farmer
        • Sales rate for the item
    • Other data generated based on above known data
        • Total cost for all of the orange trees sold (quantity times number bought)
        • Amount of sales tax (total cost (a) times sales tax rate)
        • Total amount that the farmer paid the store

2. Weather stations record the high and low temperatures, barometric pressure, pollen indices, and many more facts for every day of the year.  What can the weather station do with this data?

    • Predict temperatures by day by averaging data across many years.
    • Use data to analyze usual weather phenomenon to predict standard weather patterns.
    • Use data to analyze unusual weather phenomenon to predict weather patterns that differ from the norm.

3. A classroom teacher gives each of her students in computer science a test of data. The teacher grades each individual question and provides a grade to each student based on the questions answered correctly. What data could be derived from this test?

Think about these examples:

    • What data will the student receive when the test is graded?
        • Numeric grade on the test
        • Alphabetic grade on the test
        • The number of problems that were correct
        • The number of problems that were incorrect
        • The correct answers
    • What data will the teacher be able to create to analyze the learning in the classroom in addition to what the student received
        • Number of answers correct
        • Number of answers incorrect
        • Class average or mean numeric grade
        • Class median numeric grade
        • Class range of scores
        • Class mode of scores

Obviously data comes in a variety of forms from numeric to alphabetic, pictorial to observed.  Data allows us to problem solve, to predict a possible solution to a problem as in the cholera outbreak in London.  

Dr. Snow's method of finding a solution to a problem, geographical mapping of data, created a new vision as to how to use data. Epidemiology geographical mapping continues today. A major worldwide look at disease and its cause and control was evident in the ebola crisis in Africa, that attracted attention around the world. Technology now allows scientists to map occurrences and track the movement of the disease.

How is Data Collected Today?

Click each of the key words below to expand the information.

Preparing for Data Collection

When collecting data, asking questions to provide the needed information is the first step.  For example; let's say you wanted to get an average of shoe sizes for boys and girls from ages 8 to 12. What kind of questions would you ask and how would the answer choices need to be given?  Let's look at some examples.

Question 1 - Probably the first question may be the child's age, how would you ask the question? Let's look at some examples

Q1 Choice1 - What is your age?_____ 

         or

Q1 Choice2 - What is your age?  Choose 1

a. 8 years old

b. 9 years old

c. 10 years old

d. 11 years old

e. 12 years old

Let's look at Q1 Choice 1.  Here are some potential answer choices

8

8 1/2

8 years and 4 months

98 months

How will you summarize Q1 Choice1?  It would be hard because of the varied answers.  Q1 Choice 1 is called open-ended questions.  Open-ended questions are questions which require the respondent to elaborate on the answer.  Open-ended questions are used to gain detailed information but each questions must be analyzed individually.  Q1 Choice2 is called a close-ended question.  Closed-ended questions have definite specific answers and are much easy to quantify and proves consistency in responses. Closed-ended questions can be analyzed with charts and tables easily. Close-ended questions are true/false, multiple choice and specific range choices.