Description
Complete Example 13.2: Process Control Chart Design, located in Chapter 13 of the textbook using the Excel spreadsheet, “Process Control Chart Design.”
Answer questions 1-8 from Case: Quality Management-Toyota, located at the end of Chapter 13 in the textbook.
Refer to the Excel spreadsheet, “Computing Trend and Seasonal Factor,” to complete 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 examples, write a 150-300-word paragraph explaining the following:
- Comparison of the simple moving average, weighted moving average, exponential smoothing, and linear regression analysis time series models
- Description of 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 LopesWrite.
Number of samples
Sample size
p chart
10
Data
# Defects
Sample 1
Sample 2
Sample 3
Sample 4
Sample 5
Sample 6
Sample 7
Sample 8
Sample 9
Sample 10
Graph information
Sample 1
Sample 2
Sample 3
Sample 4
Sample 5
Sample 6
Sample 7
Sample 8
Sample 9
Sample 10
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% Defects
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Results
Total Sample Size
Total Defects
Percentage defects
Std dev of p-bar
z value
Upper Control Limit
Center Line
Lower Control Limit
0
0
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3
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p-chart
1
0.9
0.8
Mean
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0
1
2
3
4
5
6
Sample
7
8
9
10
Forecasting
Data
Period
2011 Q1
2011 Q2
2011 Q3
2011 Q4
2012 Q1
2012 Q2
2012 Q3
2012 Q4
Simple linear regression
Demand (y)
Intercept
Slope
Forecasts and Error Analysis
Forecast
Error
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Total
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Average
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Bias
Period(x)
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Forecast
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Using Linear Regression Method
9
Trend from
Actual Amount forecast
Quarter
2011
Ration of
Actual/Trend
1
2
3
4
0
0
0
0
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2
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4
0
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2012
Forecast Including Trends
FITSt
I-2013 FITS9
I-2013 FITS10
I-2013 FITS11
I-2013 FITS12
Intercept=176.1, Slope=52.3
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9
10
11
12
FIT X Seasonal
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1
2
3
4
nd Error Analysis
Absolute
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MAD
SE
Correlation
Coefficient of determination
Seasonal Factor(Av. Of Same
Qtr for 2011 and 2012)
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Squared
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MSE
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Abs Pct Err
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MAPE
Tracking Signal
Cum error Cum Abs ErrMad
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Regression
1.5
1
0.5
0
0
0.2
0.4
Series1
0.6
0.8
Linear (Series1)
1
1.2
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