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1.1 Minitab for Windows
1.2 (.1)
StatàBasic Statistics à Display Descriptive Statistics
.1
1.3 Display Descriptive Statistics, .2.
.2 Display Descriptive Statistics Minitab
- Variables Profit (C1)
- Graphs, Display Descriptive Statistics- Graphs
- Graphical Summary OK
- OK Display Descriptive Statistics, (.3).
. 3.
1.4 .3 , . 1.
1 -
Minitab | |
Mean | |
StDev | |
Skewness | , - , - , |
Kurtosis | - , . , , - . |
Minimum | |
Median | |
Maximum | |
1st Quartile | . 25 % |
3rd Quartile | (Q3). 75 % . |
95% confidence interval for Mu | 95% |
95% confidence interval for Sigma | 95% |
95% confidence interval for Median | 95% |
1.5 .
2
2.1 GraphàTime Series Plot . .4.
.4
2.2 StatàTime Series à Autocorrelation. Autocorrelation Function, .5.
.5 Autocorrelation Function Minitab
- Series (C1)
- Store ACF, Store t statistics Store Ljung-Box Q Statistics
OK Autocorrelation Function, , .6 5.
5
- Lag ;
- ACF1
- TSTA1 t-;
- LBQ1 Q-.
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5
Lag | ACF1 | TSTA1 | LBQ1 |
0,35720483 | 2,369428777 | 6,005880595 | |
0,11732431 | 0,694639567 | 6,669222215 | |
0,2401706 | 1,406630878 | 9,516739219 | |
0,68599833 | 3,848422097 | 33,32878062 | |
0,06785047 | 0,294265165 | 33,56770013 | |
-0,2190849 | -0,948299259 | 36,1242353 | |
-0,1196512 | -0,50763371 | 36,90738126 | |
0,28073742 | 1,184145494 | 41,33845126 | |
-0,2148486 | -0,878658885 | 44,00781379 | |
-0,419388 | -1,685831281 | 54,47822112 | |
-0,2919431 | -1,104369035 | 59,70571017 |
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- StatàTime Series à Moving Average
- ( 7) 1
- MA Length 4.
- Generate Forecasts 1 Number of forecasts.
. 7 Moving Average Minitab for Windows
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- ( 9) 1
- Weight to Use in smoothing. Optimal Arima.
- Generate Forecasts 1 Number of forecasts.
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3.3
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. 9 Single Exponential Smoothing Minitab for Windows
. 10
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- StatàTime Series à Double Exp Smoothing
- ( 11) 1
. 11 Double Exponential Smoothing Minitab for Windows
- Weight to Use in smoothing. Optimal Arima.
- Generate Forecasts 1 Number of forecasts/
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. 12
3.4
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- ) StatàTime Series à Winters Method
- ) ( 13) 1
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- ) Weight to Use in smoothing. , 13.
- ) Generate Forecasts 1 Number of forecasts.
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. 13 Winters Method Minitab for Windows
14.
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) StatàTime SeriesàTrend Analysis
) Trend Analysis ( ) (.15).
.15 Trend Analysis Minitab for Windows
) :
- Variable () C1;
- Model Type ( ) .
- Generate forecasts ( ) 1 Number of forecasts ( ), 1
- Title () .
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) 1 . StatàTime SeriesàDecomposition.
) Decomposition (), . 16.
. 16. Decomposition Minitab
- Variable () 1
- , Seasonal Length ( ) 4
- Model Type ( ) Multiplicative (), Model Components ( ) Trend plus seasonal ( )
- Fist obs. is in seasonal period ( ) 1
- Generate forecasts 4 Number of forecasts
) Storage... (), Decomposition - Storage, . 17.
Puc. 17. Decomposition - Storage Minitab
- Storage Trend Line ( ), Detrended data ( ), Seasonals ( ), Seasonally adjusted data ( )
- , Decomposition. . 7.
7
Y | TREN1 | DETR1 | SEAS1 | DESE1 |
100,5 | 274,9532 | 0,365517 | 0,6769 | 148,4709 |
205,5 | 273,8682 | 0,750361 | 1,032843 | 198,9654 |
258,8 | 272,7831 | 0,948739 | 1,165822 | 221,9892 |
271,6981 | 0,909097 | 1,124435 | 219,666 | |
128,8 | 270,6131 | 0,475956 | 0,6769 | 190,2792 |
294,2 | 232,6365 | 1,264634 | 1,124435 | 261,6426 |
188,1 | 231,5515 | 0,812346 | 0,6769 | 277,8844 |
241,6 | 230,4665 | 1,048309 | 1,032843 | 233,9174 |
229,3814 | 1,076809 | 1,165822 | 211,8676 | |
237,4 | 228,2964 | 1,039876 | 1,124435 | 211,1283 |
) , . 18-19.
Time Series Decomposition for Y Fitted Trend Equation Yt = 276,0 - 1,08504*t Seasonal Indices Period Index 1 0,67690 2 1,03284 3 1,16582 4 1,12443 Accuracy Measures MAPE 17,36 MAD 41,37 MSD 2674,04 Forecasts Period Forecast 45 153,799 46 233,553 47 262,358 48 251,824 |
.18 Minitab for Windows
, (). , .
. 19.
. 20
. 20 .
= 0,6769à67,6%
= 1,0328à103,3%
= 1,1658à116,6%
= 1,1244à112,4%
. 20 , 1,0. , 32,4% , , , 17% , 13% .
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