This document contains tables and conclusions from statistical tests performed on sectoral survey data. Table 1 shows results of Multinomial and Runs tests for different parameters in rural, urban and combined sectors. Most parameters are accepted except for type of worker. Table 2 shows estimates of key parameters like number of establishments by broad activity types. Table 3 gives relative standard errors for the estimates. Table 4 shows divergence between estimates, with most requiring further examination due to high relative standard errors or divergence values. The document analyzed sectoral data statistically and identified parameters requiring more examination.
This presentation attempts to create a mathematical model that can be used to estimate the fair market value of HDB resale flats. A regression model from a statisical software package is used to collate publicly available data to arrive at the fair value. In the conclusions, some suggestions are given to home buyers based on results of the study.
This presentation attempts to create a mathematical model that can be used to estimate the fair market value of HDB resale flats. A regression model from a statisical software package is used to collate publicly available data to arrive at the fair value. In the conclusions, some suggestions are given to home buyers based on results of the study.
Presentation on the report_ https://www.slideshare.net/IstiaqueHasan2/applications-of-statistical-techniques which have covered a statistical analysis on BD Lamps, Aftab Auto and BSRM Steels Limited.
Sheet1EgyptGDP by Expenditure2005 US $assumptionsYearYCGIXMconsump.docxmaoanderton
Sheet1EgyptGDP by Expenditure2005 US $assumptionsYearYCGIXMconsumption functionC=-20.4862982766+0.7460897862Y200078737.729587024359249.64476852068727.885739464114772.050070512318701.439762282822713.2907537555200181512.515401750161320.14166497139154.938252751614178.318154531519316.843630253422457.7263007577trend GDPRy=b=0.0449366764200284109.10396237862913.11581920269608.681548019114890.796453816617812.52306429221116.0129229523200386728.495429143964038.45466320599914.042190424114245.241694184719917.172763625621386.4158822964Import DemandM=Y200490302.410904929765505.324210443810219.402832902215062.944389646424588.468437457925073.7289655206200594456.32180659368828.574449917810505.54611219116613.541606264229555.835798517631047.1761602976Last 5 Years I/Y2006100973.80801124173280.255156930910832.567002848618828.680487085135839.555510440837807.25014606442007108092.58754227678448.702815302610853.00580853323303.261026347444184.732677089148697.1147849961Average X/Y 2000-20142008115850.57130333682468.862631922311084.468017679126904.537682077556892.991343073361500.28837141622009121295.54815456186997.952484219511701.700575548524458.670620090148636.545512291150499.32103758822010127481.62111044390561.662750439712228.920051973626409.362141840347185.293750957248903.61758476782011129951.22178650396646.473530784312691.844470412225854.165324178847773.639059688753014.9005985612012132810.148665824103875.04631698313090.473830644927909.894081772946675.394483525858740.66004710312013135600.392703195105792.35175105713543.886890700825226.460439558849428.986791371558391.29316949322014138533.933462906113520.54398606614333.703188862626394.252007270943224.867059992358939.4327792858projected2015144759.232830929108023.9023228282016151264.278476652112877.2518286452017158061.641358557117948.6963012062018165164.457336287123248.036274032019172586.452555608128785.5126872132020180341.969974099134571.826677975
Sheet1Y=XC=YXYx-xbary-ybar(x-xbar)(y-ybar)(x-xbar)^2787385925078737.729587024359249.6447685206-1547698.68024508-1154197.462231451786349889037.832395371204832.35C=-20.4862982766+0.7460897862815136132081512.515401750161320.1416649713-1544923.89443035-1152126.9653351779948478163.572386789839581.84841096291384109.10396237862913.1158192026-1542327.30586972-1150533.991180771774499990929.372378773518431.35867286403886728.495429143964038.4546632059-1539707.91440296-1149408.652336761769753598886.152370700461675.1903026550590302.410904929765505.3242104438-1536133.99892717-1147941.782789531763392401332.062359707662659.98944566882994456.32180659368828.5744499178-1531980.08802551-1144618.532550051753532800251.662346962990106.6410097473280100973.80801124173280.2551569309-1525462.60182086-1140166.851843041739281892322.382327036149554.0610809378449108092.58754227678448.7028153026-1518343.82228982-1134998.404184671723317815302.62305367962685.6711585182469115850.57130333682468.8626319223-1510585.83852876-1130978.244368051708439719626.52281869575563.6512129686998121295.54815456186997.9524842195.
A fund allocation for the Philippine government, proposing for a frontline-biased and needs-based allocation; it is based on the concept that regions, particularly the underdeveloped and emerging regions, be allocated more funds to accelerate development; it proposes to refer to the National Capital Region (NCR) as the benchmark in determine the add-on increment for the other regions; it incorporates the regions' GRDP performance as the basis for urgency for development, and consequently, the basis for the increment factor; after this process, the 20-80 ratio is also applied wherein the central office shares only 20% of the proposed funds, and the regions get a total of 80%, disaggregated according to the increment factored in its percent shares of funds
This presentation provides an overview of Greek international trade. Included are Greece's top trading partners in goods and services as, well as highlighting the current trade with the Balkans region.
This Slideshare presentation is a partial preview of the full business document. To view and download the full document, please go here:
http://flevy.com/browse/business-document/excel-model-for-valuation-of-natural-gas-firm-1138
DESCRIPTION
This is an valuation model of Petronet LNG. This model covers the different valuation types to arrive at the fair value of a stock.
Fixed Capital Analysis PowerPoint Presentation SlidesSlideTeam
Presenting this set of slides with name - Fixed Capital Analysis Powerpoint Presentation Slides. This deck consists of total of fourty slides. It has PPT slides highlighting important topics of Fixed Capital Analysis Powerpoint Presentation Slides. This deck comprises of amazing visuals with thoroughly researched content. Each template is well crafted and designed by our PowerPoint experts. Our designers have included all the necessary PowerPoint layouts in this deck. From icons to graphs, this PPT deck has it all. The best part is that these templates are easily customizable. Just click the DOWNLOAD button shown below. Edit the colour, text, font size, add or delete the content as per the requirement. Download this deck now and engage your audience with this ready made presentation.
Presentation on the report_ https://www.slideshare.net/IstiaqueHasan2/applications-of-statistical-techniques which have covered a statistical analysis on BD Lamps, Aftab Auto and BSRM Steels Limited.
Sheet1EgyptGDP by Expenditure2005 US $assumptionsYearYCGIXMconsump.docxmaoanderton
Sheet1EgyptGDP by Expenditure2005 US $assumptionsYearYCGIXMconsumption functionC=-20.4862982766+0.7460897862Y200078737.729587024359249.64476852068727.885739464114772.050070512318701.439762282822713.2907537555200181512.515401750161320.14166497139154.938252751614178.318154531519316.843630253422457.7263007577trend GDPRy=b=0.0449366764200284109.10396237862913.11581920269608.681548019114890.796453816617812.52306429221116.0129229523200386728.495429143964038.45466320599914.042190424114245.241694184719917.172763625621386.4158822964Import DemandM=Y200490302.410904929765505.324210443810219.402832902215062.944389646424588.468437457925073.7289655206200594456.32180659368828.574449917810505.54611219116613.541606264229555.835798517631047.1761602976Last 5 Years I/Y2006100973.80801124173280.255156930910832.567002848618828.680487085135839.555510440837807.25014606442007108092.58754227678448.702815302610853.00580853323303.261026347444184.732677089148697.1147849961Average X/Y 2000-20142008115850.57130333682468.862631922311084.468017679126904.537682077556892.991343073361500.28837141622009121295.54815456186997.952484219511701.700575548524458.670620090148636.545512291150499.32103758822010127481.62111044390561.662750439712228.920051973626409.362141840347185.293750957248903.61758476782011129951.22178650396646.473530784312691.844470412225854.165324178847773.639059688753014.9005985612012132810.148665824103875.04631698313090.473830644927909.894081772946675.394483525858740.66004710312013135600.392703195105792.35175105713543.886890700825226.460439558849428.986791371558391.29316949322014138533.933462906113520.54398606614333.703188862626394.252007270943224.867059992358939.4327792858projected2015144759.232830929108023.9023228282016151264.278476652112877.2518286452017158061.641358557117948.6963012062018165164.457336287123248.036274032019172586.452555608128785.5126872132020180341.969974099134571.826677975
Sheet1Y=XC=YXYx-xbary-ybar(x-xbar)(y-ybar)(x-xbar)^2787385925078737.729587024359249.6447685206-1547698.68024508-1154197.462231451786349889037.832395371204832.35C=-20.4862982766+0.7460897862815136132081512.515401750161320.1416649713-1544923.89443035-1152126.9653351779948478163.572386789839581.84841096291384109.10396237862913.1158192026-1542327.30586972-1150533.991180771774499990929.372378773518431.35867286403886728.495429143964038.4546632059-1539707.91440296-1149408.652336761769753598886.152370700461675.1903026550590302.410904929765505.3242104438-1536133.99892717-1147941.782789531763392401332.062359707662659.98944566882994456.32180659368828.5744499178-1531980.08802551-1144618.532550051753532800251.662346962990106.6410097473280100973.80801124173280.2551569309-1525462.60182086-1140166.851843041739281892322.382327036149554.0610809378449108092.58754227678448.7028153026-1518343.82228982-1134998.404184671723317815302.62305367962685.6711585182469115850.57130333682468.8626319223-1510585.83852876-1130978.244368051708439719626.52281869575563.6512129686998121295.54815456186997.9524842195.
A fund allocation for the Philippine government, proposing for a frontline-biased and needs-based allocation; it is based on the concept that regions, particularly the underdeveloped and emerging regions, be allocated more funds to accelerate development; it proposes to refer to the National Capital Region (NCR) as the benchmark in determine the add-on increment for the other regions; it incorporates the regions' GRDP performance as the basis for urgency for development, and consequently, the basis for the increment factor; after this process, the 20-80 ratio is also applied wherein the central office shares only 20% of the proposed funds, and the regions get a total of 80%, disaggregated according to the increment factored in its percent shares of funds
This presentation provides an overview of Greek international trade. Included are Greece's top trading partners in goods and services as, well as highlighting the current trade with the Balkans region.
This Slideshare presentation is a partial preview of the full business document. To view and download the full document, please go here:
http://flevy.com/browse/business-document/excel-model-for-valuation-of-natural-gas-firm-1138
DESCRIPTION
This is an valuation model of Petronet LNG. This model covers the different valuation types to arrive at the fair value of a stock.
Fixed Capital Analysis PowerPoint Presentation SlidesSlideTeam
Presenting this set of slides with name - Fixed Capital Analysis Powerpoint Presentation Slides. This deck consists of total of fourty slides. It has PPT slides highlighting important topics of Fixed Capital Analysis Powerpoint Presentation Slides. This deck comprises of amazing visuals with thoroughly researched content. Each template is well crafted and designed by our PowerPoint experts. Our designers have included all the necessary PowerPoint layouts in this deck. From icons to graphs, this PPT deck has it all. The best part is that these templates are easily customizable. Just click the DOWNLOAD button shown below. Edit the colour, text, font size, add or delete the content as per the requirement. Download this deck now and engage your audience with this ready made presentation.
1. TABLE-1: Sector wise parameters were tested using Multinomial and Runs test.
PARAMETER
RURAL URBAN RURAL + URBAN
C.V. T.V. (5%) T.V. (1%) C.V. T.V. (5%) T.V. (1%) C.V. T.V. (5%) T.V. (1%)
MULTINOMIAL TEST
TYPE OF ENTERPRISE 4.444 3.841 6.635 1.835 3.841 6.635 0.739 3.841 6.635
TYPE OF WORKER 65.09 7.815 11.345 300.86 7.815 11.345 348.003 7.815 11.345
BROAD ACTIVITY TYPE 0.171 7.815 11.345 5.021 7.815 11.345 4.527 7.815 11.345
RUNS TEST
GVA 496 363.558 354.844 10575 8069.108 8029.115 10875 8455.364 8414.435
C.V. – Calculated Value T.V. – Tabulated Value
Conclusion after comparing the calculated and tabulated values
PARAMETERS
DECISION
RURAL URBAN RURAL + URBAN
5% 1% 5% 1% 5% 1%
MULTINOMIAL TEST
TYPE OF
ENTERPRISE
REJECT ACCEPT ACCEPT ACCEPT ACCEPT ACCEPT
TYPE OF WORKER REJECT REJECT REJECT REJECT REJECT REJECT
BROAD ACTIVITY
TYPE
ACCEPT ACCEPT ACCEPT ACCEPT ACCEPT ACCEPT
RUNS TEST
GVA ACCEPT ACCEPT ACCEPT ACCEPT ACCEPT ACCEPT
2. TABLE-2: Sector wise parameters were estimated for State & Central Samples separately.
TYPE OF ENTERPRISE
STATE CENTER POOLED (I.V.) POOLED (W.A.)
RURAL URBAN
RURAL +
URBAN
RURAL URBAN
RURAL +
URBAN
RURAL URBAN
RURAL +
URBAN
RURAL URBAN
RURAL +
URBAN
OAE 17632 634133 651765 19741 599638 649337 19726 630299 651390 18687 616885 635572
ESTABLISHMENT 6960 495361 502321 8022 496690 504712 7563 495365 502326 7491 496026 503517
ALL 24593 1129494 1154086 27763 1096328 1124092 27626 1128503 1153521 26178 1112911 1139089
3
Method of Inverse Variance Method of Weighted Average
Pie Chart indicating the share of different categories of Enterprises.
3. BROAD ACTIVITY TYPE
STATE CENTER POOLED (I.V.) POOLED (W.A.)
RURAL URBAN
RURAL +
URBAN
RURAL URBAN
RURAL +
URBAN
RURAL URBAN
RURAL +
URBAN
RURAL URBAN
RURAL +
URBAN
MANUFACTURING 4607 237320 241927 5731 195983 201714 5646 236676 241781 5169 216651 221820
TRADING 10041 459181 469222 12822 495713 508535 10996 460508 470348 11432 477447 488878
OTHER SERVICES 9827 420890 430717 9362 380141 388113 9386 419968 428734 9594 400516 410110
ALL 24475 1117390 1141866 27915 1071837 1098362 26028 1117152 1140863 26195 1094614 1120809
Method of Inverse Variance Method of Weighted Average
Pie Chart indicating the share of different categories of Broad Activities.
4. Method of Inverse Variance Method of Weighted Average
Pie Chart indicating the division of Gross Value Added between Rural & Urban Enterprises.
G.V.A STATE CENTER POOLED(I.V.) POOLED (W.A.)
RURAL 525840612 1004325354 719898322 765082983
URBAN 37625533141 29435716862 36990267134 33530625002
RURAL+ URBAN 38151373750 30440042217 37510418687 34295707983
5. TABLE-3: Sector wise relative standard error (RSE) for key parameters
TYPE OF ENTERPRISE
STATE CENTER POOLED (I.V.) POOLED (W.A.)
RURAL URBAN
RURAL +
URBAN
RURAL URBAN
RURAL +
URBAN
RURAL URBAN
RURAL +
URBAN
RURAL URBAN
RURAL +
URBAN
OAE 35.720 4.751 3.656 2.709 14.210 8.591 2.701 4.507 3.364 16.913 7.325 4.662
ESTABLISHMENT 17.550 1.342 1.080 13.298 25.034 24.847 10.625 1.340 1.079 10.825 12.552 12.465
ALL 30.577 3.256 2.535 5.771 19.114 18.784 5.673 3.210 2.512 14.685 9.558 9.357