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2. List of statistical tools used in project management - Wikipedia

   en.wikipedia.org/wiki/List_of_statistical_tools...

   PERT network chart for a seven-month project with five milestones (10 through 50) and six activities (A through F). work breakdown structure, A work breakdown structure (WBS), in project management is a deliverable oriented decomposition of a project into smaller components. A Gantt chart is a type of bar chart, that illustrates a project ...

3. EWMA chart - Wikipedia

   en.wikipedia.org/wiki/EWMA_chart

   In statistical quality control, an EWMA chart (or exponentially weighted moving average chart) is a type of control chart used to monitor either variables or attributes-type data using the monitored business or industrial process's entire history of output. [1]

4. Tracking signal - Wikipedia

   en.wikipedia.org/wiki/Tracking_signal

   In statistics and management science, a tracking signal monitors any forecasts that have been made in comparison with actuals, and warns when there are unexpected departures of the outcomes from the forecasts. Forecasts can relate to sales, inventory, or anything pertaining to an organization's future demand.

5. Moving average - Wikipedia

   en.wikipedia.org/wiki/Moving_average

   In statistics, a moving average (rolling average or running average or moving mean [1] or rolling mean) is a calculation to analyze data points by creating a series of averages of different selections of the full data set. Variations include: simple, cumulative, or weighted forms. Mathematically, a moving average is a type of convolution.

6. Critical path method - Wikipedia

   en.wikipedia.org/wiki/Critical_path_method

   The project has two critical paths: activities B and C, or A, D, and F – giving a minimum project time of 7 months with fast tracking. Activity E is sub-critical, and has a float of 1 month. The critical path method ( CPM ), or critical path analysis ( CPA ), is an algorithm for scheduling a set of project activities. [ 1 ]

7. Autoregressive moving-average model - Wikipedia

   en.wikipedia.org/wiki/Autoregressive_moving...

   In the statistical analysis of time series, autoregressive–moving-average (ARMA) models are a way to describe a (weakly) stationary stochastic process using autoregression (AR) and a moving average (MA), each with a polynomial. They are a tool for understanding a series and predicting future values.