Question
I essential help creating a study guide with examples (step by step) as well as formulas using a BAII scientific calculator. I essential as much detail as possible! Here goes!
Part 1
• Recognizing variable types- qualitative vs quantitative
• Recognizing data scales for variables- nominal, ordinal, interval, ratio
• Measures of central tendency as well as variation (mean, median, percentiles, variance, standard deviation, etc.). Follow book's techniques for computing median, percentiles, quartiles
• Chebyshev's theorem as well as empirical rule
Part 2
• Counting rules
• Probability rules- one event, more than one event, addition, multiplication, etc
• Using probability tables to calculate simple, joint, conditional probabilities
• Bayes' theorem
• Expected value, variance, as well as standard deviation of discrete probability distributions
• Binomial as well as Poisson discrete distributions
• Normal, exponential, uniform continuous distributions
Part 3
• Identify characteristics which make processes out of control.
• Given sample data collected, when you are asked to calculate UCL and LCL, identify which chart type is appropriate so you can use the correct formulas
• Calculate values for center line, LCL as well as UCL for various control charts discussed in the chapter. Use Control Chart Factors as suitable (that is Table E9 entries)
• Calculate LCL and UCL and decide if a process is in or out of statistical control
Approximation
• Find slope, intercept, r, r2 and so on. From an Excel output as well as interpret each value
• Given regression equations as well as/or printouts from Excel estimate Y
• Given n observations for X and Y compute- slope, intercept, r, r2, SSE, SSR, SST. Using the regression function of your calculator could save a lot of time for a few problems
• SST = SSE + SSR. Use this relationship to calculate r2 or Mean Square Error as well as the Standard Error of the Estimate
• Be able to compute r2 as well as r when the values for SSR, SSE and SST are known
• Convert data units when using regression equations
• Be able to calculate the t-statistic from data given and look up the critical t-value from t-table
Part 4
• Make forecasts using smoothing methods of forecasting- moving average, exponential smoothing, weighted moving average, trend projection and so on
• Calculate forecast accuracy: MAD, MAPD, MSE
• Calculate seasonal factors
• Calculate seasonally-adjusted forecasts
• Specified Excel's multiple regression output, estimate Y
part 5
• PERT/CPM- Given time estimates for each activity as well as precedence relationships, draw and solve project networks to calculate project completion time, ES, EF, LS, LF as well as slack
• For PERT- given triple time estimates for activities, calculate expected time, variance as well as standard deviation for tasks and for project
• Use normal distribution to calculate completion time probability for PERT projects
• Use normal distribution to calculate project completion time for given service level
• Interpret QM software output for crashing projects to answer related questions