# comparing the simple moving average weighted moving average, exponential smoothing, and linear regression analysis time series models.

Complete “Example 13.2: Process Control Chart Design,” located in Chapter 13 of the textbook.

Write a 150-300-word paragraph comparing the simple moving average weighted moving average, exponential smoothing, and linear regression analysis time series models.

Refer to the Excel spreadsheet, “Quality Control Analytics at Toyota,” to complete the “Case: Quality Management Toyota,” at the end of Chapter 13 in the textbook. Answer Questions 1-8.

Refer to the Excel spreadsheet, “Computing Trend and Seasonal Factor From a Linear Regression Line Obtained “to complete the “Example 18.4: Computing Trend and Seasonal Factor From a Linear Regression Line Obtained With Excel,” located in Chapter 18 of the textbook.

After working through the example, reflect write a 150-300-word paragraph explaining the market research, panel consensus, historical analogy, and Delphi method qualitative forecasting techniques.

While APA format is not required for the body of this assignment, solid academic writing is expected, and documentation of sources should be presented using APA formatting guidelines, which can be found in the APA Style Guide, located in the Student Success Center.

You are not required to submit this assignment to Turnitin.orecasting Simple linear regression

Data

Elissa Torres: Forecasting: Submodel = 15; Problem size @ 8 by 2 Forecasts and Error Analysis Tracking Signal

Period Demand (y) Period(x) Forecast Error Absolute Squared Abs Pct Err Cum error Cum Abs Err Mad Track Signal (Cum error/MAD)

2011 Q1 ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0!

2011 Q2 ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0!

2011 Q3 ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0!

2011 Q4 ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0!

2012 Q1 ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0!

2012 Q2 ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0!

2012 Q3 ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0!

2012 Q4 ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0!

Total ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0!

Intercept ERROR:#DIV/0! Average ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0!

Slope ERROR:#DIV/0! Bias MAD MSE MAPE

SE ERROR:#DIV/0!

Forecast ERROR:#DIV/0! 9

Using Linear Regression Method Correlation ERROR:#DIV/0!

Coefficient of determination ERROR:#DIV/0!

Quarter Actual Amount Trend from forecast Ration of Actual/Trend Seasonal Factor(Av. Of Same Qtr for 2011 and 2012)

2011

1 0 ERROR:#DIV/0! ERROR:#DIV/0! 1 ERROR:#DIV/0!

2 0 ERROR:#DIV/0! ERROR:#DIV/0! 2 ERROR:#DIV/0!

3 0 ERROR:#DIV/0! ERROR:#DIV/0! 3 ERROR:#DIV/0!

4 0 ERROR:#DIV/0! ERROR:#DIV/0! 4 ERROR:#DIV/0!

2012

1 0 ERROR:#DIV/0! ERROR:#DIV/0!

2 0 ERROR:#DIV/0! ERROR:#DIV/0!

3 0 ERROR:#DIV/0! ERROR:#DIV/0!

4 0 ERROR:#DIV/0! ERROR:#DIV/0!

Forecast Including Trends Intercept=176.1, Slope=52.3

FITSt = FIT X Seasonal

I-2013 FITS9 9 ERROR:#DIV/0!

I-2013 FITS10 10 ERROR:#DIV/0!

I-2013 FITS11 11 ERROR:#DIV/0!

I-2013 FITS12 12 ERROR:#DIV/0!

Regression

If this is trend analysis then simply enter the past demands in the demand column. If this is causal regression then enter the y,x pairs with y first and enter a new value of x at the bottom in order to forecast y.

RegressionTemplate for 13.2

Quality Control p chart

Number of samples 10

Sample size

Data

Elissa Torres: Quality Control: Submodel = 4; Problem size @ 10 by 1 Results

# Defects % Defects Total Sample Size 0

Sample 1 ERROR:#DIV/0! ERROR:#DIV/0! Total Defects 0

Sample 2 ERROR:#DIV/0! ERROR:#DIV/0! Percentage defects ERROR:#DIV/0!

Sample 3 ERROR:#DIV/0! ERROR:#DIV/0! Std dev of p-bar ERROR:#DIV/0!

Sample 4 ERROR:#DIV/0! ERROR:#DIV/0! z value 3

Sample 5 ERROR:#DIV/0! ERROR:#DIV/0!

Sample 6 ERROR:#DIV/0! ERROR:#DIV/0! Upper Control Limit ERROR:#DIV/0!

Sample 7 ERROR:#DIV/0! ERROR:#DIV/0! Center Line ERROR:#DIV/0!

Sample 8 ERROR:#DIV/0! ERROR:#DIV/0! Lower Control Limit ERROR:#DIV/0!

Sample 9 ERROR:#DIV/0! ERROR:#DIV/0!

Sample 10 ERROR:#DIV/0! ERROR:#DIV/0!

Graph information

Sample 1 ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0!

Sample 2 ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0!

Sample 3 ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0!

Sample 4 ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0!

Sample 5 ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0!

Sample 6 ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0!

Sample 7 ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0!

Sample 8 ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0!

Sample 9 ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0!

Sample 10 ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0! ERROR:#DIV/0!

p-chart

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

Sample

Mean

Enter the sample size then enter the number of defects in each sample.

p-chart

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

Sample

Mean