Time serises? 1,070,000 EHS Inventory * Inventories are not seasonally adjusted
ID: 3131802 • Letter: T
Question
Time serises?
1,070,000
EHS Inventory
* Inventories are not seasonally adjusted and are thus not revised
* Inventories are not seasonally adjusted and are thus not revised
.
QUESTIONS:
1. PREDICT ALL HOUSING SALES BY REGIONS AND THE ENTIRE US FOR MARCH 2016-JUNE 2016.
2. IS THERE ANY SIGNIFICANT DIFFERENCE AMONG THE REGIONS?
EHS SAAR Year Month U.S. Northeast Midwest South West 2013.01 2013 Jan 4,980,000 640,000 1,180,000 1,950,000 1,210,000 2013.02 Feb 5,060,000 650,000 1,190,000 2,010,000 1,210,000 2013.03 Mar 5,070,000 650,000 1,190,000 2,020,000 1,210,000 2013.04 Apr 5,090,000 660,000 1,180,000 2,040,000 1,210,000 2013.05 May 5,140,000 640,000 1,220,000 2,050,000 1,230,000 2013.06 Jun 5,110,000 660,000 1,200,000 2,040,000 1,210,000 2013.07 Jul 5,270,000 710,000 1,250,000 2,070,000 1,240,000 2013.08 Aug 5,260,000 690,000 1,250,000 2,120,000 1,200,000 2013.09 Sept 5,140,000 670,000 1,200,000 2,060,000 1,210,000 2013.10 Oct 5,040,000 660,000 1,170,000 2,040,000 1,170,000 2013.11 Nov 4,920,000 650,000 1,160,000 2,000,000 1,110,000 2013.12 Dec 4,860,000 630,000 1,150,000 2,000,000 1,080,000 2014.01 2014 Jan 4,740,000 620,000 1,090,000 1,980,000 1,050,000 2014.02 Feb 4,720,000 570,000 1,050,000 2,010,000 1,090,000 2014.03 Mar 4,740,000 620,000 1,090,000 1,970,000 1,060,000 2014.04 Apr 4,780,000 620,000 1,090,000 1,980,000 1,090,000 2014.05 May 4,900,000 620,000 1,130,000 2,040,000 1,110,000 2014.06 Jun 4,970,000 640,000 1,160,000 2,040,000 1,130,000 2014.07 Jul 4,990,000 640,000 1,170,000 2,070,000 1,110,000 2014.08 Aug 4,960,000 650,000 1,190,000 2,020,000 1,100,000 2014.09 Sept 5,030,000 670,000 1,150,000 2,070,000 1,140,000 2014.10 Oct 5,140,000 690,000 1,190,000 2,130,000 1,130,000 2014.11 Nov 5,040,000 680,000 1,150,000 2,110,000 1,100,000 2014.12 Dec 5,070,000 660,000 1,130,000 2,160,000 1,120,000 2015.01 2015 Jan 4,930,000 630,000 1,100,000 2,120,000 1,080,000 2015.02 Feb 4,970,000 600,000 1,120,000 2,130,000 1,120,000 2015.03 Mar 5,250,000 650,000 1,220,000 2,200,000 1,180,000 2015.04 Apr 5,140,000 630,000 1,240,000 2,100,000 1,170,000 2015.05 May 5,290,000 690,000 1,260,000 2,140,000 1,200,000 2015.06 Jun 5,410,000 720,000 1,290,000 2,190,000 1,210,000 2015.07 Jul 5,480,000 700,000 1,280,000 2,260,000 1,240,000 2015.08 Aug 5,290,000 700,000 1,260,000 2,140,000 1,190,000 2015.09 Sept 5,440,000 740,000 1,290,000 2,180,000 1,230,000 2015.10 Oct 5,290,000 740,000 1,280,000 2,120,000 1,150,000 2015.11 Nov 4,860,000 700,000 1,120,000 1,990,000 1,050,000 2015.12 Dec 5,450,000 740,000 1,250,000 2,240,000 1,220,000Explanation / Answer
we will use minitab software for this answer
1. PREDICT ALL HOUSING SALES BY REGIONS AND THE ENTIRE US FOR MARCH 2016-JUNE 2016.
time point exp U.S
39 5236534
40 5244251
41 5251968
42 5259685
time point exp North
39 698067
40 699829
41 701591
42 703353
time point exp Middle
39 1219307
40 1221008
41 1222709
42 1224410
time point exp south
39 2180837
40 2185878
41 2190919
42 2195960
time point exp west
39 1138284
40 1137496
41 1136708
42 1135920
where time poibt 39=march 2016
40=april 2016
41=may2016
42=june 2016
2. IS THERE ANY SIGNIFICANT DIFFERENCE AMONG THE REGIONS?
this is a testing problem of anova. The Anova table we get from minitab is
Source DF SS MS F P
Factor 3 3.75286E+13 1.25095E+13 3252.75 0.000
Error 140 5.38417E+11 3845833333
Total 143 3.80670E+13
S = 62015 R-Sq = 98.59% R-Sq(adj) = 98.56%
Individual 95% CIs For Mean Based on
Pooled StDev
Level N Mean StDev ----+---------+---------+---------+-----
N 36 661944 40058 (*
M 36 1184444 63805 (*
S 36 2077500 78463 (*
W 36 1154444 59591 (*
----+---------+---------+---------+-----
800000 1200000 1600000 2000000
Pooled StDev = 62015
here p-value is 0 so we can say that the regions are differs significantly
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