Microsoft Excel 2019 Data Analysis and Business Modeling notes (6th edition)

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.