Chap 1 - Chapter 1 Data and Statistics Learning Objectives...

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Chapter 1 Data and Statistics Learning Objectives 1. Obtain an appreciation for the breadth of statistical applications in business and economics. 2. Understand the meaning of the terms elements, variables, and observations as they are used in statistics. 3. Obtain an understanding of the difference between categorical, quantitative, crossectional and time series data. 4. Learn about the sources of data for statistical analysis both internal and external to the firm. 5. Be aware of how errors can arise in data. 6. Know the meaning of descriptive statistics and statistical inference. 7. Be able to distinguish between a population and a sample. 8. Understand the role a sample plays in making statistical inferences about the population. Solutions: 1 - 1
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Chapter 1 1. Statistics can be referred to as numerical facts. In a broader sense, statistics is the field of study dealing with the collection, analysis, presentation and interpretation of data. 2. a. 10 b. 5 c. Categorical variables: Class and Fuel Type Quantitative variables: Cylinders, City MPG, and Highway MPG d. Variable Measurement Scale Class Nominal Cylinders Ratio City MPG Ratio Highway MPG Ratio Fuel Type Nominal 3. a. Average for city driving = 182/10 = 18.2 mpg b. Average for highway driving = 261/10 = 26.1 mpg On average, the fuel efficiency rating for highway driving is 7.9 mpg greater than the average for city driving. c. 3 of 10 or 30% have four cylinder engines d. 7 of 10 or 70% will run on regular fuel 4. a. 7 b. 5 c. Categorical variables: State, Campus Setting, and NCAA Division Quantitative variables: Endowment ($ billions) and % Applicants Admitted 5. a. Average endowment = 74.6/7 = $10.657 billion b. Average percentage admitted = 111/7 = 15.86% c. 3 of 7 or 42.9% have NCAA Division III varsity teams d. 3 of 7 or 42.9% have a City: Midsize campus setting 6. a. Quantitative b. Categorical c. Categorical d. Quantitative e. Categorical 7. a. Although the data are recorded as numbers, the numbers are codes for the ratings of Fair (1), Average (2), Good (3) and Excellent (4). Thus the variables are categorical with each data value 1 - 2
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Data and Statistics corresponding to a rating category for the variable.
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