STATISTICAL ANALYSIS & ASTHMATIC PATIENTS IN SULAIMANIYAH GOVERNORATE IN THE TUBER-CLOSES CENTER

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1 March 3. Vol., No. ISSN 37-3 IJRSS & K.A.J. All rights reserved STATISTICAL ANALYSIS & ASTHMATIC PATIENTS IN SULAIMANIYAH GOVERNORATE IN THE TUBER-CLOSES CENTER Dr. Mohammad M. Faqe Hussai (), Asst. Lecturer Roqia Abdulkadir Jamel () Uiversity of Sulaimai, Presidecy of Slemai Polytechic Uiversity ; Abstract This paper is study of the people who was affected with asthma diseases durig the period (5-). Asthma is a disease affectig the airways that carry air to ad from your lugs. People who suffer from this chroic coditio (log-lastig or recurret) are said to be asthmatic. The iside walls of a asthmatic's airways are swolle or iflamed. This swellig or iflammatio makes the airways extremely sesitive to irritatios ad icreases your susceptibility to a allergic reactio. i this study applied two models, the first model is sigle expoetial smoothig model(sesm) ad secod model is the double expoetial smoothig model (SDEM),ad after that it compare betwee the two models depedig o the measures (MAPE, MAD, MSD), ad after the process of compariso the double expoetial smoothig model was selected ". Depedig o the double expoetial smoothig model the cofidece limit ad predictio of umbers of people who is affected with these diseases are obtaied subsequet the years ad 3. I the fial of this study the umber of male ad female affected with asthma disease are icreasig i the years ad 3 for both geders.the study recommed that the Miistry of Health must be more attetio ad care, for the patiets who affected with this type of the disease i the sulaymaiyah goverorate ad the supply of medicies ad ope more health ceters for the purpose of their care ad treatmets. Keywords: Method of Aalysis, the model, Forecastig Performace Measures, Aalysis the data. Method of Aalysis [][4] I this paper, two differet types of uivariate forecastig model were developed o the same data set for the purpose of fidig the best fit models. These models are Sigle Expoetial Model, Double Expoetial Model. The applicatio of uivariate models (Sigle Expoetial Model, Double Expoetial Model) as forecastig provide the advatage of simplicity, less costly to develop ad easier to uderstad. Each model type has its uique characteristics which defie its suitability to be fitted to that data. Data collected were aalyzed usig Microsoft Office Excel ad MINITAB.

2 March 3. Vol., No. ISSN 37-3 IJRSS & K.A.J. All rights reserved The Model - Sigle Expoetial Smoothig Model [][3][6] Sigle expoetial smoothig model is the simplest model i the group of the expoetial smoothig techiques. The model requires oly oe parameter, which is costat, α, to geerate the fitted values ad forecast. I this model, the forecast for the ext ad all subsequet periods are determied by adjustig the curret period forecast by a portio of the differece betwee the curret forecast ad curret actual value. Hece, mathematically the model ca represeted as: ( )..() Where: = sigle expoetial smoothed value i period = the actual value at time period = ukow smoothig costat to be determied. The value is betwee ad. = the forecast made i period The best parameter value, α ca be determied by usig solver facility that available i Excel software based o the estimatio part of the data. The best value of α is defied based o the smallest value of MSD - Double Expoetial Smoothig Model [][3] [6] This model is useful for series that exhibits a liear tred characteristic, the mai advatage of double expoetial smoothig method over sigle expoetial is it ability to geerate multiple-ahead-forecast. Let: S t be the expoetially smoothed value of Y t at time t S t be the double expoetially smoothed value of Y t at time t Computes the sigle expoetially smoothed value: S t = αy t + ( α)s t-.() Computes the double expoetially smoothed value: S t = αs t + ( α)s t-.(3) 5

3 March 3. Vol., No. ISSN 37-3 IJRSS & K.A.J. All rights reserved Next, = S t S t Ad, computes the adjustmet factors: = ( ) Forecast for m-step-ahead are computed usig the equatio:.(4) As i expoetial modelig, the mai difficulty ecoutered whe usig this method is the determiatio of the size α. As usual, the criterio is to choose α such that the MSD is miimum. Agai, solver used to solve this problem []. 3 Forecastig Performace Measures [5] [7] Mea Forecast Error (MFE or Bias): Measures average deviatio of forecast from actual. (5) Mea Absolute Deviatio (MAD): Measures average absolute deviatio of forecast from actual (6) Mea Absolute Percetage Error (MAPE): Measures absolute error as a percetage of the forecast. MFE MAD t..(7) Stadard Squared Error (MSE): Measures variace of forecast error t MAPE MSE t ( A t F ) A t F t t t At Ft A ( A t F ) t t () 4 Aalysis the data: I this research, asthma disease data was used. The data was obtaied from the hospital i Sulaimaiyah goverorate. A mothly data set for 7 years period (5 to ) is used ad the data are show i the figure below: - 6

4 March 3. Vol., No. ISSN 37-3 IJRSS & K.A.J. All rights reserved Figure (): Show the umbers of people ifected with the asthma disease durig the year First: We draw the curve of the umber of people ifected with asthma durig the year (5-).The horizotal axis for time ad (5-) the vertical axis value of umbers of (male, female) patiets with asthma disease Figure () : The time series of the umber of male patiets ifected with asthma disease durig the years (5-) 7

5 March 3. Vol., No. ISSN 37-3 IJRSS & K.A.J. All rights reserved Figure (3): The time series of the umber of female patiets ifected with asthma disease durig Secod: We are fidig the values of the measuremets (MAPE,MAD,MSD ) for the two the years (5-) models below ad accordig to the data the males ifected with this type of disease: Table (): show the measures of the two models Model α γ MAPE MAD MSD Sigle Expoetial Double Expoetial Figure (4): Show Smoothig Plot for (Sigle Expoetial Smoothig)

6 March 3. Vol., No. ISSN 37-3 IJRSS & K.A.J. All rights reserved Figure (5): Show Smoothig Plot for (Double Expoetial Smoothig) Through the table () we compariso betwee the two models by the measures of (MAPE, MAD, MSD).From the measures we ote that the best model is double expoetial smoothig model because the values of measures (MAPE, MAD, MSD) be less tha the measures of sigle expoetial smoothig model. Table () : Show the predictio ad cofidece iterval of the umbers of male patiets ifected with asthma disease durig the year (-3) Year Period Forecastig Lower Upper Year Period Forecastig Lower Upper Depedig o the table above we ote that the umber of the people who ifected with the asthma disease i the goverorate of Sulaymaiyah of the male patiets are icreased 9

7 March 3. Vol., No. ISSN 37-3 IJRSS & K.A.J. All rights reserved over the years, 3 ad this reaso is due to lack of health awareess amog the people ad the people who ifected with this type of the disease are ot revisio a specialist doctor for the purpose of takig the ecessary treatmet Figure (6): Show the predictio of the umber of male patiets ifected with the asthma diseases Third: We are fidig the values of the measuremets (MAPE,MAD,MSD ) for the two models below ad accordig to the data the female ifected with this type of disease: Table (3): Show the measures of the two models Model α γ MAPE MAD MSD Sigle Expoetial Double Expoetial Figure (7): Show Smoothig Plot for (Sigle Expoetial Smoothig) 3

8 March 3. Vol., No. ISSN 37-3 IJRSS & K.A.J. All rights reserved Figure (): Show Smoothig Plot for (Double Expoetial Smoothig) Through the table (3) we compariso betwee model because the values of measures (MAPE, the two models by the measures of (MAPE, MAD, MSD) be less tha the measures of sigle MAD, MSD).From the measures we ote that expoetial smoothig model. the best model is double expoetial smoothig Table (4): Show the predictio ad cofidece iterval of the umbers of patiets ifected with asthma disease durig the year (-3) Year Period Forecastig Lower Upper Year Period Forecastig Lower Upper Depedig o the table above we ote that the umber of the people who ifected with the asthma disease i the goverorate of Sulaymaiyah of the female patiets are icreased over the years, 3 ad this reaso is due to lack of health awareess amog the people ad the people who ifected with this type of the disease are ot revisio a specialist doctor for the purpose of takig the ecessary treatmet. 3

9 March 3. Vol., No. ISSN 37-3 IJRSS & K.A.J. All rights reserved Figure (9): Show the predictio of the umber of female patiets ifected with the asthma diseases 5 Coclusios & Recommedatios: 5- Coclusios Through this study, we get a set of coclusios ad must be ecessary metioed as follows: - ) Through the data aalysis we ote that the appropriate model to predict the umber of males patiets ifected with asthma disease is double expoetial smoothig model ) The appropriate model to predict the umber of female patiets ifected with asthma is double expoetial smoothig model 3) From the data aalysis we see that the umbers of male ad female patiet ifected with asthma disease are icreases durig the year (-3). 5- Recommedatios: There is a set of recommedatios for this study ad these recommedatios are: - : ) People with this type of disease must take care of them by the govermet ad ope more health ceters for a dagerous disease that affects the respiratory system to humas. ) Provides more data ad iformatio by the health ceter for researchers to coduct more research i this type of disease. 3) Usig statistical measuremets more accurate to aalyze this type of disease. Refereces [] A. Pakratz,(93). Forecastig with uivariate Box-Jekis models, Joh Wiley, Joh Wiley & Sos New York. [] Bowerma, B.L., O Coell, R.T. & Koehler, A.B. (5). Forecastig, Time Series, ad Regressio A Applied Approach. Ed: 4. Uited States of America: Thomso Brooks/Cole. [3] C. Chatfield, B. Koehler, K. Ord, ad D. Syder (). A ew look at models for expoetial smoothig, The Statisticia 5, o., [4] Hake, J.E. & Wicher, D.W. (5). Busiess Forecastig. Ed:. Uited States of America: Pearso Pretice Hall. [5] Krajewski,L.J.,Ritzma,L.R.,,(993).Operatios Maagemet, Strategy ad Aalysis, Addisio -Wesley Publishig Compay,Ic.,P.436 [6] Mohd Alias Lazim (7). Itroductory Busiess Forecastig. A Practical Approach. Shah Alam: Pusat Peerbita Uiversiti, Uiversiti Tekologi Mara. [7] Makridakis,S.,Wheelwright,S.C.,(99).Forecastig Methods for Maagemet, Joh Wiley & Sos New York,P.3. [] Wilso, J.H & Keatig, B. (). Busiess Forecastig, Ed:4. New York: McGraw- Hill. 3