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