INFO 1010 (INFO1010)

University Of Denver

Here are the best resources to pass INFO 1010 (INFO1010). Find INFO 1010 (INFO1010) study guides, notes, assignments, and much more.

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Lecture #8 - Linear Programming Lecture #8 - Linear Programming
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    Lecture #8 - Linear Programming

  • Identify the objective, decision cells, and constraints in an optimization problem. Set up an optimization problem in Excel. Set up Solver to solve an optimization problem in Excel.
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Lecture #7 - The Normal Distribution Lecture #7 - The Normal Distribution
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    Lecture #7 - The Normal Distribution

  • Explain the central limit theorem. Apply the empirical rule to a normal data set. Apply Chebychev's theorem to a non-normal data set. Calculate z-scores for values in a data set. Identify outliers in a data set using z-scores.
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Lecture #6 - Measures of Dispersion
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    Lecture #6 - Measures of Dispersion

  • Explain how measures of dispersion describe variability in a data set. Identify skewness and kurtosis in a data set. Calculate the variance and standard deviation of a data set.
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Lecture #5 - Descriptive Statistics Part #2 Lecture #5 - Descriptive Statistics Part #2
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    Lecture #5 - Descriptive Statistics Part #2

  • Construct a box plot to visualize the 5-number of summary of a data set. Match a frequency distribution to a corresponding box plot. Calculate the upper and lower fences for outliers using the interquartile range. Identify outliers using the interquartile range method.
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Lecture #4 - Descriptive Statistics Part #1 Lecture #4 - Descriptive Statistics Part #1
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    Lecture #4 - Descriptive Statistics Part #1

  • Explain the measures of central tendency. Calculate the mean, median, and mode of a data set. Calculate the range, quartiles, and interquartile range of a data set. Construct a 5-number summary of a data set.
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Lecture #3 - Data Analysis Lecture #3 - Data Analysis
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    Lecture #3 - Data Analysis

  • Explain the difference between descriptive and inferential statistics. Identify the types of data and levels of measurement. Calculate relative and cumulative frequencies frequencies. Use pivot tables to explore a new data set.
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Lecture #1 - Introduction to Data Analysis Lecture #1 - Introduction to Data Analysis
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    Lecture #1 - Introduction to Data Analysis

  • Distinguish between quantitative and qualitative data. Understand the distinction between different types of statistics and analytics. Explain how data analysis is used to inform business decision-making. Identify the primary steps in the data analysis lifecyle.
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