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CHS Statistics. 1.2: The Nature of Data. Objective: To understand the different types of data. Data. Data ( plural ) – observations (such as measurements, genders, and survey responses) that have been collected Datum ( singular )

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1 2 the nature of data

CHS Statistics

1.2: The Nature of Data

Objective: To understand the different types of data

slide2
Data
  • Data (plural)– observations (such as measurements, genders, and survey responses) that have been collected
    • Datum (singular)
    • Sometimes used to find statistics if the context of the data is randomly selected and/or representative of the population
parameter vs statistic
Parameter vs. Statistic
  • Parameter – a numerical measurement describing some characteristic of a population
  • Statistic – a numerical measurement describing some characteristic of a sample
parameter vs statistic you decide
Parameter vs. Statistic – YOU DECIDE!
  • A recent survey of a sample of MBAs reported that the average salary for an employee with an MBA is more than $82,000.
  • Starting salaries for the 667 MBA graduates for the University Of Chicago Graduate School Of Business increased 8.5% from the previous year.
  • In a random check of a sample of retail stores, the Food and Drug Administration found that 34% of the stores were not storing fish at the proper temperature.
  • When Lincoln was first elected to the presidency, he received 39.82% of the 1,865,908 votes cast.
two types of data
Two Types of Data
  • Quantitative Data – values that answer questions about the quantity or amount (with units) of what is being measured.
    • Examples: income ($), height (inches), weight (pounds)
  • Categorical Data – (qualitative data) can be separated into different categories that are often distinguished by some nonnumeric characteristic
    • Examples: sex, race, ethnicity, zip codes
  • Wait? Hold up! Did I just see a zip codes as categorical data? I thought they were numbers…
categorical vs quantitative you decide
Categorical vs. Quantitative - You Decide!
  • Length of a song
  • Responses in an opinion poll
  • Telephone Number
  • Income of college graduates
  • The genders (male/female) of college graduates
discrete vs continuous data
Discrete vs. Continuous Data
  • Discrete Data– result when a number of possible values is either a finite number or a “countable” number (dealing with counts)
    • Example: the number of students with blonde hair
  • Continuous Data – result from infinitely many possible values that correspond to some continuous scale that covers a range of values without gaps, interruptions, or jumps (often times has units of measure attached)
    • Example: the amount of rainfall in Zelienople this past month
discrete vs continuous data you decide
Discrete vs. Continuous Data – YOU DECIDE!
  • X represents the number of motorcycle accidents in one year in California.
  • x represents the length of time it takes to get to work.
  • x represents the volume of blood drawn for a blood test.
  • x represents the number of rainy days in the month of July in Orlando, Florida.
  • x represents the amount of snow (in inches) that fell in Nome, Alaska last winter.
levels of measurement
Levels of Measurement
  • Nominal – characterized by data that consist of names, labels, or categories only
    • The data cannot be arranged in an ordering scheme (such as high to low)
    • Example: survey responses of yes, no, and undecided
  • Ordinal – can be arranged in some order, but the differences between the data values either cannot be determined or are meaningless
    • Example: grade letters (A, B, C, D, F); movie ratings (1, 2, 3, 4, 5) – while you can find the difference between the ratings, it is meaningless. The difference of 1 or 2 is meaningless, because it cannot be compared to other similar differences.
levels of measurement continued
Levels of Measurement (continued)
  • Interval – similar to the ordinal level, but the difference between any two data values is meaningful. However, there is no natural zero starting point (where none of the quantity is present).
    • Example: temperatures (while 0° F seems like a good starting point, it isn't necessarily)
  • Ratio –similar to the interval, but has a natural zero starting point (where zero indicates none of the quantity is present)
    • Differences and ratios are meaningful
    • Example: weights of adult humans, prices of jeans
levels of measurement you decide
Levels of Measurement – YOU DECIDE!
  • Body temperature in degrees Fahrenheit of a swimmer
  • Collection of phone numbers
  • Final standing for the football Northeastern Conference
  • Heart rate (beats per minute) of an athlete.
1 2 assignment
1.2 Assignment

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