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Business Statistics Final Exam Review

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Sample vs. Population Page 7 ~1 question The sample is part of the population. Population: The entire set of individuals or objects of interest or the measurements obtained from all individuals or ... objects of interest. Sample: A portion or part of the population of interest. Identify Different Types of Variables ~1 question Qualitative vs. Quantitative (Pages 8 – 9) Qualitative Variable: Gender, religious affiliation, type of automobile owned, state of birth, eye color; i.e. what % of people have blue eyes. Qualitative Data information describing color, odor, shape, or some other physical characteristics. Quantitative Variable: How many and what percent. When a variable studied can be reported numerically the variable is called a Quantitative variable. Quantitative Data is numerical data. Quantitative Variables are either Discrete or Continuous. Discrete vs. Continuous (Page 9) Discrete Variables: Discrete Variables can assume only certain values, and there are “gaps” between the values. Examples of discrete variables are the number of bedrooms in a house (1, 2, 3, 4, etc.) the number of cars arriving at exit 25 on I4 in Florida near Walt Disney World in an hour (326, 421, etc.), and the number of students in a statistics course (25 in section A, 42 in section B and 18 in section C). We count for example the number of cars arriving at Exit 25 on I4, and we count the number of statistics students in each section. Notice that a home can have 3 or 4 bedrooms, but it cannot have 3.65 bedrooms. Thus, there is a “gap” between possible values. Typically, discrete variables result from counting. Continuous Variables: Observations of a continuous variable can assume any value within a specific range. Examples of continuous variables are the air pressure in a tire and the weight of a shipment of tomatoes. Other examples are the amount of raisin brand in a box and the duration of flights between San Diego and a GPA is another example. [Show More]

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