Questions and Answers
What does the term 'population' refer to in statistical analysis?
In situations where a complete census is impractical, what method is typically used to gather information?
What does the size of a sample usually represent in statistics?
What does the term 'statistical inference' refer to?
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Which statement best describes reliability in the context of statistical inference?
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Which of the following best defines a sample in statistics?
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Why might a complete census be impossible to conduct?
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What is the typical notation for the size of the population in statistical terms?
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What is the mean of a set of measurements?
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Which statement about the median is true?
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How is the median defined when the number of observations is even?
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In a dataset, what does the median represent?
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Which of the following measures is considered the best known and most reliable measure of central tendency?
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What happens to the median if extreme values are added to the dataset?
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Which measure can be used to describe the central tendency when the distribution is skewed?
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If a dataset has the values 3, 7, 9, and 11, what is the median?
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What defines the mode in a set of numbers?
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Which statement about the mode is correct?
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What is the correct formula for calculating the range of a data set?
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Why is the range not considered a stable measurement of variability?
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In what scenario might the mode not exist?
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What aspect of the mode makes it a simple measure of central tendency?
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Which of the following best describes the utility of the range in a data set?
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Which of the following statements is true about the mode?
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What is the primary goal of parametric regression?
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What limitation is associated with the classical chi-squared test?
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Which statistical test is designed specifically for testing hypotheses based on t-distribution?
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In which scenario is Monte Carlo simulation suggested as a better approach?
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What characteristic makes t-tests versatile for data analysis?
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What type of test is the chi-squared test specifically used for?
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Which of the following statements is true regarding the number of parameters in parametric regression?
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What is the primary hypothesis for the chi-squared test?
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What is the method used to find the present value of future cash flows?
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What does an optimization model aim to achieve?
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In linear programming, what is typically optimized?
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Which of the following describes future value?
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What is a common issue with profitability indexes when dealing with multiple solutions?
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What is a constraint in optimization problems?
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In the context of optimization, what does the term 'maximize' refer to?
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Which statement best describes compounding in the context of investments?
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Study Notes
Cost Engineering Overview
- Population refers to the collection of elements relevant to decision-making; denoted by N.
- A census of a large population may be impractical, requiring sampling.
- Sample size is typically denoted by n, used for statistical inference about the population.
- Statistical inference estimates or predicts characteristics about a population from sample data.
Descriptive Statistics
- Mean: The sum of measurements divided by the number of measurements, serves as a reliable measure of central tendency.
- Median: The middle value in an ordered data set; if even, it is the average of the two middle values; represents the 50th percentile.
- Mode: The most frequently occurring value in a data set; may be non-unique or nonexistent.
- Range: The difference between the highest and lowest values in a data set; sensitive to extreme values.
Statistical Methods
- Chi-squared Test: Evaluates how well theoretical distributions match empirical data; useful for testing the null hypothesis.
- For small sample sizes, Monte Carlo simulation can be more accurate than classical chi-squared tests.
- T-tests: Hypothesis tests focusing on populations with normal distributions; also effective for non-normally distributed populations.
Time Value of Money
- Present Value: Calculates value based on discounting future cash flows to the present time, using a cost of capital.
- Future Value: Represents the cost or benefit at a future date, considering the time value of money.
Optimization Techniques
- Optimization Model: A mathematical approach to identify the best choice among alternatives under given constraints.
- Linear Programming: A method for solving optimization problems by maximizing or minimizing a linear function subjected to linear constraints. For example, blending different grades of fuel to achieve desired specifications.
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