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MONTH/YEAR PRICE - Y Prediction (F) error Absolute Error Squared Error Jan2010 1118 Feb2010 1095.4 Mar2010 1113.3 Apr2010 1148.7 May2010 1205.4 Jun2010 1232.9 Jul2010 1193
MONTH/YEAR | PRICE - Y | Prediction (F) | error | Absolute Error | Squared Error |
Jan2010 | 1118 | ||||
Feb2010 | 1095.4 | ||||
Mar2010 | 1113.3 | ||||
Apr2010 | 1148.7 | ||||
May2010 | 1205.4 | ||||
Jun2010 | 1232.9 | ||||
Jul2010 | 1193 | ||||
Aug2010 | 1215.8 | ||||
Sep2010 | 1271.1 | ||||
Oct2010 | 1342 | ||||
Nov2010 | 1369.9 | ||||
Dec2010 | 1390.6 | ||||
Jan2011 | 1356.4 | ||||
Feb2011 | 1372.7 | ||||
Mar2011 | 1424 | ||||
Apr2011 | 1473.8 | ||||
May2011 | 1510.4 | ||||
Jun2011 | 1528.7 | ||||
Jul2011 | 1572.8 | ||||
Aug2011 | 1775.8 | ||||
Sep2011 | 1771.9 | ||||
Oct2011 | 1665.2 | ||||
Nov2011 | 1739 | ||||
Dec2011 | 1652.3 | ||||
Jan2012 | 1652.21 | ||||
Feb2012 | 1742.14 | ||||
Mar2012 | 1673.77 | ||||
Apr2012 | 1649.69 | ||||
May2012 | 1591.19 | ||||
Jun2012 | 1598.76 | ||||
Jul2012 | 1589.9 | ||||
Aug2012 | 1630.31 | ||||
Sep2012 | 1744.81 | ||||
Oct2012 | 1746.58 | ||||
Nov2012 | 1721.64 | ||||
Dec2012 | 1684.76 | ||||
Jan2013 | 1671.85 | ||||
Feb2013 | 1627.57 | ||||
Mar2013 | 1593.09 | ||||
Apr2013 | 1487.86 | ||||
May2013 | 1414.03 | ||||
Jun2013 | 1343.35 | ||||
Jul2013 | 1285.52 | ||||
Aug2013 | 1351.74 | ||||
Sep2013 | 1348.6 | ||||
Oct2013 | 1316.58 | ||||
Nov2013 | 1275.86 | ||||
Dec2013 | 1221.51 | ||||
Jan2014 | 1244.27 | ||||
Feb2014 | 1299.58 | ||||
Mar2014 | 1336.08 | ||||
Apr2014 | 1298.45 | ||||
May2014 | 1288.74 | ||||
Jun2014 | 1279.1 | ||||
Jul2014 | 1310.59 | ||||
Aug2014 | 1295.13 | ||||
Sep2014 | 1236.55 | ||||
Oct2014 | 1222.49 | ||||
Nov2014 | 1175.33 | ||||
Dec2014 | 1200.62 | ||||
Jan2015 | 1250.75 | ||||
Feb2015 | 1227.08 | ||||
Mar2015 | 1178.63 | ||||
Apr2015 | 1198.93 | ||||
May2015 | 1198.63 | ||||
Jun2015 | 1181.5 | ||||
Jul2015 | 1128.31 | ||||
Aug2015 | 1117.93 | ||||
Sep2015 | 1124.77 | ||||
Oct2015 | 1159.25 | ||||
Nov2015 | 1086.44 | ||||
Dec2015 | 1068.25 | ||||
Jan2016 | 1097.91 | ||||
Feb2016 | 1199.5 | ||||
Mar2016 | 1245.14 | ||||
Apr2016 | 1242.26 | ||||
May2016 | 1260.95 | ||||
Jun2016 | 1276.4 | ||||
Jul2016 | 1336.65 | ||||
Aug2016 | 1340.17 | ||||
Sep2016 | 1326.61 | ||||
Oct2016 | 1266.55 | ||||
Nov2016 | 1238.35 | ||||
Dec2016 | 1157.36 | ||||
Jan2017 | 1192.1 | ||||
Feb2017 | 1234.2 | ||||
Mar2017 | 1231.42 | ||||
Apr2017 | 1266.88 | ||||
May2017 | 1246.04 | ||||
Jun2017 | 1260.26 | ||||
Jul2017 | 1236.85 | ||||
Aug2017 | 1283.04 | ||||
Sep2017 | 1314.07 | ||||
Oct2017 | 1279.51 | ||||
Nov2017 | 1281.9 | ||||
Dec2017 | 1264.45 | ||||
Jan-18 |
MAD | |
MSE | |
RMSE |
The data gives the monthly gold price per ounce. Use naive method to predict the gold price for January 2018. Also,complete the table and find the three measures of error.
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