If you made a forecast for Week 19, based on a 3 week weighted moving average,...
If you made a forecast for Week 19, based on a 3 week weighted moving average, with oldest data to most recent data weighted 0.20, 0.30, and 0.50, respectively, how much would your forecast be different from the actual jobless claims?
|
Week |
Jobless claims |
|
(in thousands) |
|
|
1 |
400 |
|
2 |
393 |
|
3 |
392 |
|
4 |
396 |
|
5 |
404 |
|
6 |
385 |
|
7 |
368 |
|
8 |
366 |
|
9 |
387 |
|
10 |
375 |
|
11 |
402 |
|
12 |
355 |
|
13 |
379 |
|
14 |
373 |
|
15 |
361 |
|
16 |
351 |
|
17 |
353 |
|
18 |
351 |
|
19 |
Group of answer choices
None of the stated answers are correct.
3.00
Cannot be determined.
0
5.40
Homework Answers
Add Answer to:
If you made a forecast for Week 19, based on a 3 week weighted
moving average,...
If you made a forecast for Week 8, based on a 4 Week simple moving average,...
If you made a forecast for Week 8, based on a 4 Week simple moving average, how much would your forecast be different from the actual jobless claims? Week Jobless claims in thousands 400 393 В 392 4 396 15 1404 16 385 7 368 18 366 18 19 |10 |11 12 355 113 14 15 116 1351 117 18 19 17 353 18 351 19 217.56 495.06 22.25 None of the stated answers are correct. 14.75
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A supermarket chain analyzed data on sales of a particular brand of snack cracker at 104...
A supermarket chain analyzed data on sales of a particular brand of snack cracker at 104 stores for a certain one week period. The analyst decided to build a regresion model to predict the sales of the snack cracker based on the total sales of all brands in the snack cracker category. c. The difference in category sales between two stores is 150. What is the predicted differnece of the cracker sales between these stores? CategorySales Sales 1348 394 1110...
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Patronage Data:
Fridays
Saturdays
Sundays
391
450
389
362
456
343
407
452
352
438
417
385
436
400
379
452
462
366
334
430
435
393
457
375
433
435
394
367
499
444
379
385
373
349
518
339
345
450
411
371
469
394
377
427
417
336
454
384
383
416
444
388
414
403
404
370
390
389
425
384
390
456
366
389
443
445
440
479
406
397
475
359
394
409
392...
Hi it's python I imported a data which are so many words in txt and I arranged and reshaped with ...
Hi it's python I imported a data which are so many words in txt
and I arranged and reshaped with alphabetically both rows and
columns
I was successful with these steps but I am stuck with next
step
below is my code and screenshot
import numpy as np
import pandas as pd
data=pd.read_csv("/Users/superman/Downloads/words_file2.txt",header=None)
df_input=pd.DataFrame(data)
df_output=pd.DataFrame(np.arange(676).reshape((26,26)),
index =
['a','b','c','d','e','f','g','h','i','j','k','l','m','n','o','p','q','r','s','t','u','v','w','x','y','z'],
columns =
['a','b','c','d','e','f','g','h','i','j','k','l','m','n','o','p','q','r','s','t','u','v','w','x','y','z'])
df_output.index.name="Start"
df_output.columns.name="End"
df_output
This below screen shot is what I have to find
I have to find each word...
Using the following information, I need help posting the closing entries to the T-accounts (using "clos."...
Using the following information, I need help posting the closing
entries to the T-accounts (using "clos." and the correspondjng
number as shown in the journal entry as posting references) as well
as preparing a post-closing trial balance.
L16750 70 39,60 E 39,6 Less: (360) Acum, Depri. Truck (361) Total Plant assets 39, 400 E R _362) Total Assets Liabilities (363) Current liabilities (384) salaries pagable (365) Uncned revenue (386) total liabilities Stockholders' Equity (367) Commons to 25100 (368) Rtained earnings...
Please determine the IDENTITY of the unknown compound and explain how each peak / data point...
Please determine the IDENTITY of the unknown
compound and explain how each peak / data point from the following
instruments led to that identification. What does the gcms
indicate. Thank you very much! (The GCMS data is just a long set of
numbers which is why the question appears so long).
IR of unknown:
NMR unknown Proton Graphs (first is overall graph,
others that follow are zoomed in sections):
NMR unknown Carbon Graphs (first is overall graph,
others that follow...
Database Intro Salesmen Sheet Order_info Sheet Business_Info sheet 1.Create your own table design based on the...
Database Intro
Salesmen Sheet
Order_info Sheet
Business_Info sheet
1.Create your own table design based on the Excel data, and
include all relationships (joins). Apply referential integrity
rules wherever appropriate.
Import the data from Excel to Access to populate
tables:
1. Use the Chen technique and illustrate the E-R diagram for the
tables you created
Note: It may be necessary to change the data composition due to
normalization issues, if you change the composition detail how and
why; (you may find...
HELP needed urgently....Data and question is attacted below..... Thank you in advance there is no data...
HELP needed urgently....Data and question is attacted below.....
Thank you in advance
there is no data link fir this data it’s all in photos.... thank
you
i
have already posted the question
We were unable to transcribe this imageNo. 2 3 4 5 6 7 8 Working Sector Public Own Public Public Private Public Private Private Own Own Private Public Public Public Private 9 10 11 12 13 Public IS 16 17 18 19 20 21 22 23 24 25...
If you made a forecast for Week 8, based on a 4 Week simple moving average, how much would your forecast be different from the actual jobless claims? Week Jobless claims in thousands 400 393 В 392 4 396 15 1404 16 385 7 368 18 366 18 19 |10 |11 12 355 113 14 15 116 1351 117 18 19 17 353 18 351 19 217.56 495.06 22.25 None of the stated answers are correct. 14.75
Using the data below, what is the weighted moving average forecast for the 4th week? The weights are 20,30.50 (oldest period to most recent period) Week Time Series Value 17.00 17.00 7.00 20.00 Submit Answer format: Number: Round to: 1 decimal places. Using the data below and the SES forecast 00.3, what is the error for the 3rd week? Week Time Series Value 6.00 19.00 17.00 23.00 Submit
Patronage Data:
Fridays
Saturdays
Sundays
391
450
389
362
456
343
407
452
352
438
417
385
436
400
379
452
462
366
334
430
435
393
457
375
433
435
394
367
499
444
379
385
373
349
518
339
345
450
411
371
469
394
377
427
417
336
454
384
383
416
444
388
414
403
404
370
390
389
425
384
390
456
366
389
443
445
440
479
406
397
475
359
394
409
392...
Hi it's python I imported a data which are so many words in txt
and I arranged and reshaped with alphabetically both rows and
columns
I was successful with these steps but I am stuck with next
step
below is my code and screenshot
import numpy as np
import pandas as pd
data=pd.read_csv("/Users/superman/Downloads/words_file2.txt",header=None)
df_input=pd.DataFrame(data)
df_output=pd.DataFrame(np.arange(676).reshape((26,26)),
index =
['a','b','c','d','e','f','g','h','i','j','k','l','m','n','o','p','q','r','s','t','u','v','w','x','y','z'],
columns =
['a','b','c','d','e','f','g','h','i','j','k','l','m','n','o','p','q','r','s','t','u','v','w','x','y','z'])
df_output.index.name="Start"
df_output.columns.name="End"
df_output
This below screen shot is what I have to find
I have to find each word...
Using the following information, I need help posting the closing
entries to the T-accounts (using "clos." and the correspondjng
number as shown in the journal entry as posting references) as well
as preparing a post-closing trial balance.
L16750 70 39,60 E 39,6 Less: (360) Acum, Depri. Truck (361) Total Plant assets 39, 400 E R _362) Total Assets Liabilities (363) Current liabilities (384) salaries pagable (365) Uncned revenue (386) total liabilities Stockholders' Equity (367) Commons to 25100 (368) Rtained earnings...
Please determine the IDENTITY of the unknown
compound and explain how each peak / data point from the following
instruments led to that identification. What does the gcms
indicate. Thank you very much! (The GCMS data is just a long set of
numbers which is why the question appears so long).
IR of unknown:
NMR unknown Proton Graphs (first is overall graph,
others that follow are zoomed in sections):
NMR unknown Carbon Graphs (first is overall graph,
others that follow...
Database Intro
Salesmen Sheet
Order_info Sheet
Business_Info sheet
1.Create your own table design based on the Excel data, and
include all relationships (joins). Apply referential integrity
rules wherever appropriate.
Import the data from Excel to Access to populate
tables:
1. Use the Chen technique and illustrate the E-R diagram for the
tables you created
Note: It may be necessary to change the data composition due to
normalization issues, if you change the composition detail how and
why; (you may find...
HELP needed urgently....Data and question is attacted below.....
Thank you in advance
there is no data link fir this data it’s all in photos.... thank
you
i
have already posted the question
We were unable to transcribe this imageNo. 2 3 4 5 6 7 8 Working Sector Public Own Public Public Private Public Private Private Own Own Private Public Public Public Private 9 10 11 12 13 Public IS 16 17 18 19 20 21 22 23 24 25...
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