1. Ch. 2 - Data Part I – Exploring and Understanding Data 74 Jones 103562 Yorktown, PA Red $115.25 154 Gonzalez 3.42 3/17/05 Female 32 21.3337.378 Samuel France A4598

2. What are Data? Data are pieces of information (singular = datum) Consider 17, 21, 44, and 76. What do these numbers tell us? To be useful, the data must be in context This context is often provided in a data table Last NameAgeSystolic Blood Pressure Exercise level Smith17104High Martinez21111Moderate Kim44123Low Curry76118Moderate (Nothing!)

3. The Five (or Six) W’s In establishing context for our data, it is useful to think like a journalist, and establish the answers to the “five W’s”: – Who? – What? – When? – Where? – Why? Answering these questions can help us understand what data is telling us Adding “How” can also provide useful information We will not always be able to answer all of these questions, but we should try to answer as many as we can

4. Who? The “Who” refers to the individual cases we are collecting information about (each row in a data table usually represents one case) Who: 4 patients in a clinic Last NameAgeSystolic Blood Pressure Exercise level Smith17104High Martinez21111Moderate Kim44123Low Curry76118Moderate

5. Who? Cases are not always people; sometimes the “who” will refer to things or events Here are some purchasing records for a high school In this table, the cases (“Who”) are the individual orders Order DateDepartmentItemSupplierCost 3/5/07Foreign Language Copy TonerStaples$308.00 5/1/07MathematicsCalculatorsTexas Instruments $500.00 6/2/08Student Activities PizzaPapa John’s$173.72

6. What? The characteristics recorded about each individual are called variables They identify “what” is being recorded about each case What: last name, age, systolic blood pressure, exercise level Last NameAgeSystolic Blood Pressure Exercise level Smith17104High Martinez21111Moderate Kim44123Low Curry76118Moderate

7. Variable Types There are two types of variables in statistics: – Categorical: Identifies which “category” a case falls into (examples: gender, political party, first name, department…) – Quantitative: Measures the quantity (amount) of something (examples: age, height, weight, blood pressure, GPA, cost…) – For quantitative variables, it is important to pay attention to the units (feet, kilograms, dollars, etc.) being used

8. Categorical or Quantitative? Last NameAgeSystolic Blood Pressure Exercise level Smith17104High Martinez21111Moderate Kim44123Low Curry76118Moderate Last Name: Age: Blood Pressure:Exercise Level: Be careful! Just because values are numerical does not always mean they are quantitative Last NameStudent IDCreditsZip Code Alexander10345110592507 Michaelson20451721092506 Gomez10168114592507 Categorical Quantitative

9. When, Where, How and Why? Knowing when, where and how data was collected can help us understand its limitations Knowing why data was collected is one of the most important indicators telling us what we should do first when we look at a data set – this tells us what we are trying to learn from the data

10. Examples For each example, identify as many of the “W’s” as possible, name each variable and state whether the variable is categorical or quantitative. For quantitative variables, identify the units used. 1)A Consumer Reports article on energy bars gave the brand name, flavor, price, number of calories, and grams of protein and fat. Who? What? When? Where? Why? How? Variables: Energy bars Brand name, flavor, price, calories, grams of protein & fat Unknown To provide consumers with info to compare bars Categorical: name, flavor Unknown Quantitative: price ($), # calories (calories), protein (g) & fat (g)

11. Examples 2)A report on the Boston Marathon listed each runner’s gender, country, age and time Who?What? When?Where? Why?How? Variables: RunnersGender, country, age, time Date of marathonBoston To publish race results? Categorical: gender, country Unknown Quantitative: age (years), time (minutes?)

12. Homework Assignment 2-1 pg. 17 #15, 17, 20 Complete the class survey on my website