1-2. Explain the principles of statistical thinking. Why is statistical thinking an important managerial skill?
1-10.Explain the differences between categorical, ordinal, interval, and ratio data.
1-11. Explain the difference between cross-sectional and time-series data.
1-12. What is the difference between a population and a sample?
2-3. Explain the principal types of descriptive statistics measures that are used for describing data.
2-5. What statistical measures are used for describing dispersion in data? How do they differ from one another?
2-6. Explain the importance of the standard deviation in interpreting and drawing conclusions about risk.
2-12. Explain the concept of correlation and how to interpret correlation coefficients of 0.3, 0, and -0.95.
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Statistical Thinking is the process of using statistics when making business decisions. What this looks like in a company is a manager has the ability to choose a project that has a 70% chance of making a profit instead of a project that has only a 30% chance of making the same profit. This is important for the firm to use all available data when making decisions to maximize profitability.
Categorical Data can be organized into "categories" based on an observable trait. Examples would be male/female, eye color, political party or any other characteristic.
Ordinal Data contains values that can be counted and ranked into a certain order. For example, runners position in a race, number of years in school or some other characteristic that can be counted.
Interval Data is measured along a scale with an equivalent measurement. This allows comparison between two pairs. Examples would be temperature or rating something on a scale of 1-10.
Ratio Data has numbers that can be compared to one another. An example of ...
Statistical analysis in business are examined. The principles of statistical thinking are determined.