Q1]. [30%] The data for this question given in the table below come from the sample data folder of MINITAB. The data give you the monthly number of people employed (in units of 1000) in the retail trade industry in the state of Wisconsin from January 1970 to December 1974. Copy this timeseries data into an excel spreadsheet in your home area first before you start your analysis. You can use Excel to answer this question. Month 1970 1971 1972 1973 1974 1 322 322 330 348 361 2 317 318 326 345 354 3 319 320 329 349 357 4 323 326 337 355 367 5 327 332 345 362 376 6 328 334 350 367 381 7 325 335 351 366 381 8 326 336 354 370 383 9 330 335 355 371 384 10 334 338 357 375 387 11 337 342 362 380 392 12 341 348 368 385 396 (a) (b) (c) (d) Draw a time series plot of the data and comment on any noticeable patterns. Describe an appropriate time series model for this data, giving your reasons, and obtain estimates of the components of your model using the decomposition method. Using your model forecast the monthly number of people employed in the retail trade industry in Wisconsin for each month of 1975. Clearly show all your working and steps you used in the calculation of your forecast. Discuss the accuracy of your forecast. Discuss the limitations of the decomposition method compared with the exponential smoothing method.
Q1]. [30%] The data for this question given in the table below come from the sample data folder of MINITAB. The data give you the monthly number of people employed (in units of 1000) in the retail trade industry in the state of Wisconsin from January 1970 to December 1974. Copy this timeseries data into an excel spreadsheet in your home area first before you start your analysis. You can use Excel to answer this question. Month 1970 1971 1972 1973 1974 1 322 322 330 348 361 2 317 318 326 345 354 3 319 320 329 349 357 4 323 326 337 355 367 5 327 332 345 362 376 6 328 334 350 367 381 7 325 335 351 366 381 8 326 336 354 370 383 9 330 335 355 371 384 10 334 338 357 375 387 11 337 342 362 380 392 12 341 348 368 385 396 (a) (b) (c) (d) Draw a time series plot of the data and comment on any noticeable patterns. Describe an appropriate time series model for this data, giving your reasons, and obtain estimates of the components of your model using the decomposition method. Using your model forecast the monthly number of people employed in the retail trade industry in Wisconsin for each month of 1975. Clearly show all your working and steps you used in the calculation of your forecast. Discuss the accuracy of your forecast. Discuss the limitations of the decomposition method compared with the exponential smoothing method.
Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018
18th Edition
ISBN:9780079039897
Author:Carter
Publisher:Carter
Chapter10: Statistics
Section10.6: Summarizing Categorical Data
Problem 10CYU
Related questions
Question
![Q1]. [30%]
The data for this question given in the table below come from the sample data folder of
MINITAB. The data give you the monthly number of people employed (in units of 1000) in
the retail trade industry in the state of Wisconsin from January 1970 to December 1974. Copy
this timeseries data into an excel spreadsheet in your home area first before you start your
analysis. You can use Excel to answer this question.
Month
1970
1971
1972
1973
1974
1
322
322
330
348
361
2
317
318
326
345
354
3
319
320
329
349
357
4
323
326
337
355
367
5
327
332
345
362
376
6
328
334
350
367
381
7
325
335
351
366
381
8
326
336
354
370
383
9
330
335
355
371
384
10
334
338
357
375
387
11
337
342
362
380
392
12
341
348
368
385
396
(a)
(b)
(c)
(d)
Draw a time series plot of the data and comment on any noticeable patterns.
Describe an appropriate time series model for this data, giving your reasons, and obtain
estimates of the components of your model using the decomposition method.
Using your model forecast the monthly number of people employed in the retail trade
industry in Wisconsin for each month of 1975. Clearly show all your working and steps
you used in the calculation of your forecast. Discuss the accuracy of your forecast.
Discuss the limitations of the decomposition method compared with the exponential
smoothing method.](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F31dfe0cc-6d64-49ad-9528-17a3fb263a5f%2Ff857f562-db41-45ec-9f01-120a21e37e32%2Fjr7ryem_processed.png&w=3840&q=75)
Transcribed Image Text:Q1]. [30%]
The data for this question given in the table below come from the sample data folder of
MINITAB. The data give you the monthly number of people employed (in units of 1000) in
the retail trade industry in the state of Wisconsin from January 1970 to December 1974. Copy
this timeseries data into an excel spreadsheet in your home area first before you start your
analysis. You can use Excel to answer this question.
Month
1970
1971
1972
1973
1974
1
322
322
330
348
361
2
317
318
326
345
354
3
319
320
329
349
357
4
323
326
337
355
367
5
327
332
345
362
376
6
328
334
350
367
381
7
325
335
351
366
381
8
326
336
354
370
383
9
330
335
355
371
384
10
334
338
357
375
387
11
337
342
362
380
392
12
341
348
368
385
396
(a)
(b)
(c)
(d)
Draw a time series plot of the data and comment on any noticeable patterns.
Describe an appropriate time series model for this data, giving your reasons, and obtain
estimates of the components of your model using the decomposition method.
Using your model forecast the monthly number of people employed in the retail trade
industry in Wisconsin for each month of 1975. Clearly show all your working and steps
you used in the calculation of your forecast. Discuss the accuracy of your forecast.
Discuss the limitations of the decomposition method compared with the exponential
smoothing method.
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