EFFECT OF SORBET FREEZING PROCESS ON DRAW TEMPERATURE AND ICE CRYSTAL SIZE USING FOCUSED BEAM REFLECTANCE METHOD (FBRM) ONLINE MEASUREMENTS
|
|
- Garry Robinson
- 5 years ago
- Views:
Transcription
1 ICR 2011, August Prague, Czech Republc ID: 949 EFFECT OF SORBET FREEZING PROCESS ON DRAW TEMPERATURE AND ICE CRYSTAL SIZE USING FOCUSED BEAM REFLECTANCE METHOD (FBRM) ONLINE MEASUREMENTS M. ARELLANO A,B, J. E. GONZALEZ A,B, D. LEDUCQ A, H. BENKHELIFA B, D. FLICK B, G. ALVAREZ A a Cemagref. UR Géne des Procédés Frgorfques. Cemagref, 1 rue Perre-Glles de Gennes, Antony, 92160, France Antony, France. gracela.alvarez@cemagref.fr b AgroParsTech.UMR n 1145 Ingénere Procédés Alments. Pars, France. benkhel@agroparstech.fr ABSTRACT Durng sorbet and ce cream manufacturng s desred to obtan, a narrow ce crystal sze dstrbuton wth a small mean sze, n order to get a smooth texture n the fnal product. We studed the nfluence of the mx flow rate, the evaporaton temperature of the refrgerant flud and the dasher speed the draw temperature and on the ce crystal sze durng sorbet freezng n order to dentfy optmal operatng condtons. We used the focused beam reflectance method (FBRM) to follow the evoluton of the ce crystal sze. The FBRM probe, provdes accurate and repeatable nformaton about the chord length dstrbuton (CLD) of ce crystals. Wth ths probe t s possble to follow onlne the development of the ce crystals n sorbets or slurres contanng up to 40% of ce. The effect of refrgerant flud temperature was very mportant; by decreasng refrgerant temperature we reduce sgnfcantly the ce crystal sze and we obtan as expected lower draw temperature. Hgh dasher speeds slghtly decrease the ce crystal chord length, due to the attrton of the bgger ce crystals, whch produces new smaller ce nucle by secondary nucleaton. Also, an ncrease of the dasher speed slghtly warms the product, due to the dsspaton of frctonal energy nto the product. As expected low mx flow rates result n lower draw temperatures because the product remans longer n contact wth the freezer wall, extractng thus more heat from the product. Nevertheless, the mx flow rate dd not show a sgnfcant effect on the ce crystal sze. Keywords: Ice crystal sze; sorbet; ce cream; Focused beam reflectance method; Freezng; Scraped surface heat exchanger. 1. INTRODUCTION Durng the freezng process of sorbet and ce cream, t s necessary to obtan a narrow ce crystal sze dstrbuton (CSD) and small ce crystals (<50 µm). The qualty of the fnal product s related to the ce crystal sze because t confers a smooth texture and good palatablty to the product. Therefore, n order to mprove the qualty of the fnal product, we need to assess the process condtons that affect the most drectly the ce crystal sze. The process condtons that nfluence the mechansm of ce crystallzaton wthn a freezer are the evaporaton temperature of the refrgerant flud, the dasher rotatonal speed and the mx flow rate. The evaporaton temperature of the refrgerant flud provdes the degree of supercoolng enough to trgger ce nucleaton and t also determnes the heat removal rate of the system. The resdence tme of the product wthn the freezer s determned by the mx flow rate, whch would also affect the heat removal rate, and consequently the nucleaton and growth mechansms of the ce crystals. The scrapng acton of the blades orgnates frctonal heat whch may be dsspated nto the product and lead to the ncrease of ts draw temperature (Russell et al., 1999). However, the rotaton of the dasher helps also to mprove the heat transfer coeffcent between the freezer wall and the product, leadng to the reducton of the product s ext temperature (Ben Lakhdar et al., 2005).
2 ICR 2011, August Prague, Czech Republc Several methods have been used n lterature, to characterze the ce CSD. Nevertheless, some of these methods partally destroy the ce crystal structure durng sample preparaton, and none of these methods has been able to measure drectly onlne the ce crystal sze durng the freezng process. Recently, Haddad A. et al. (2010) have used the onlne focused beam reflectance method (FBRM), to successfully follow the evoluton of the ce CSD durng the batch freezng of sucrose/water solutons. The FBRM probe s a laser reflecton technque, whch provdes real tme nformaton about the chord length dstrbuton (CLD) of the ce crystals. One of the man advantages of ths technque s ts sutablty for n stu measurements of partculates at hgh sold concentratons. Despte the fact that the FBRM technque gves no nformaton about the partcle s morphology and t measures a CLD rather than a CSD, ths measure can be useful to follow the evoluton of crystals' sze durng the freezng process. The am of ths research s to use the FBRM technque to study onlne the nfluence of the process condtons on the ce crystal chord length as well as on the draw temperature durng the freezng of lemon sorbet. 2. MATERIALS & METHODS 2.1 Expermental setup - Sorbet freezng Lemon sorbet (25.7 % w/w sweeteners solds, 0.5 % w/w locust bean gum/guar gum/ hypromellose stablser blend) was produced n a contnuous plot freezer at a laboratory scale (WCB MF 50) wth a maxmum capacty of kg s -1. The dasher speed was studed from 57 to 105 rad.s -1 and the evaporaton temperature of the refrgerant flud R22 (Chlorodfluoromethane) was changed between -10 to -20 C accordng to the expermental condtons. 2.2 Expermental desgn and data treatment An expermental desgn of type central composte was used to assess the nfluence of the process condtons, such as the mx flow rate (MFR), the dasher rotatonal speed (DRS) and the evaporaton temperature of R22 (TR22), on the response varables of mean ce crystal chord length (MCL) and draw (ext) temperature (DT) of sorbet. The central composte expermental desgn was composed of a 2 3 factoral desgn wth expermental ponts at ±1, a 'composte' desgn wth ponts at the extremes of the expermental regon (±α, wth α = 1.68) and a common central pont of the two desgns at zero (Sablan et al., 2007). The values of the expermental desgn and the real freezng condtons are shown n Table 1. Table 1. Operatng condtons for the central composte expermental desgn a. Process Condtons Coded Values Factors Coded varables - α α MFR (kg.s -1 ) X TR22 ( C) X DRS (rad.s -1 ) X a MFR = mx flow rate; TR22 = evaporaton temperature of R22; DRS = dasher rotatonal speed. Analyss of varance (ANOVA) at a 95% confdence nterval was performed to fnd relatonshps between the process condtons and the responses of MCL and DT durng sorbet freezng. The second-order polynomal used to predct the expermental behavour of the responses was gven by equaton 1: y X 3 1 X 2 3 j1 X j X j (1) where y s the response, β 0, β, β and β j are regresson coeffcents for ntercepton, lnear, quadratc and nteracton effects, respectvely, and X X j are coded levels of the expermental factors.
3 ICR 2011, August Prague, Czech Republc 2.3. Ice crystal sze measurements A Mettler-Toledo Lasentec FBRM probe (Model S400A-8) was used to measure ce crystal chord length onlne. Ths devce generates a focused laser beam (780 nm) whch scans a crcular path at the nterface between the probe's wndow and the partcles n suspenson. When a partcle s ntersected by the laser beam, t reflects the laser lght durng the tme t s been scanned (cf. fgure 1a). Smultaneously, the tme perod of reflecton s detected by the FBRM probe and then multpled by the tangental speed of the laser beam, yeldng thus a dstance across the partcle, whch s a chord length. The FBRM probe measures thousands of chords per second provdng a CLD (number of counts per second sorted by chord length nto 100 logarthmc sze classes). Departng from ths nformaton, the mean chord length of the ce crystals was obtaned by the equaton 2: c n c / n, (2) mean where n s the number of partcles for each of the sze classes of chord length c. 1 The FBRM probe was nserted nto the outlet ppe of the freezer wth a 45 angle relatve to the flow (cf. fgure 1b), so as to renew contnually the sorbet flow that was beng measured. In order to avod condensaton at the nsde surface of the FBRM probe wndow, a purge was carred out wth ntrogen at 1 bar, wth a flow rate of 5 l/mn. Once the steady state of the freezer was establshed, the chord length acquston data was synchronzed wth draw temperature and recorded every 5 seconds for a perod of 10 mnutes. Fgure 1a. Measurement prncple of a partcle's chord length by the FBRM probe (Mettler-Toledo). Fgure 1b. FBRM probe nserted at the outlet ppe of the freezer. 2.4 Draw temperature measurements We measured the product's draw (ext) temperature onlne by usng a calbrated Pt100 probe (Baumer, accuracy of 0.1 C). The Pt100 probe was nserted nto the outlet ppe of the freezer before the product's ext (cf. fgure 1b). The draw temperature determnes the ce mass fracton wthn sorbet. A decrease of the draw temperature wll be accompaned by an ncrease of the ce mass fracton. The relatonshp between the draw temperature of sorbet and ts ce mass fracton s establshed by the sorbet's equlbrum freezng pont curve, or "lqudus curve" of the mx, whch was determned prevously n our laboratory, based on dfferental scannng calormetrc (DSC) measurements. 3. RESULTS & DISCUSSION
4 ICR 2011, August Prague, Czech Republc Table 2 shows the real process condtons under whch the onlne ce crystal CLD and draw temperature measurements were taken, as well as the mean values of the obtaned responses. Each condton was performed twce and 5 tmes for run 10. It can be seen from table 2, that the use of the FBRM sensor enables us to follow onlne the development of the ce crystals n sorbets contanng up to 40% of ce, whch was one of the objectves of ths research. Table 2. Real freezng condtons durng measurements and obtaned responses a. Coded values Factors Responses Run MFR TR22 DRS MCL DT IMF MFR TR22 DRS kg.s -1 C rad.s -1 µm ºC % α α α α α α a MFR = Mx flow rate; TR22 = Evaporaton temperature of R22; DRS = Dasher rotatonal speed; MCL = Mean chord length; DT = Draw temperature; IMF = Ice mass fracton. Accordng to the global ANOVA analyss shown n table 3, the mean chord length response showed a sgnfcant model regresson (P < ) wth a value of R 2 = 0.94, a varaton coeffcent CV = 2.36% and dd not show a sgnfcant lack of ft (P = 0.62). In the same manner, the draw temperature of sorbet had a sgnfcant regresson model (R 2 = 0.99, CV = 2.24%, P < ) and dd not show a sgnfcant lack-of-ft (P = 0.83). Thus, these models can be used to predct the expermental behavour of mean chord length and draw temperature responses, respectvely. Table 3. Global Analyss of Varance for Responses of MCL and DT a Response R 2 adjusted CV (%) F Value P-value (model) Lack-of-Ft MCL < * 0.62 DT < * 0.83 a MCL = Mean Chord Length; DT = Draw temperature; CV = Coeffcent of varaton; * = sgnfcant nfluence at 95% confdence nterval. The ANOVA analyss of the draw temperature response shown n table 4, ndcates that t was sgnfcantly nfluenced at a 95% confdence nterval by the mx flow rate (β 1 )and the evaporaton temperature of the refrgerant flud (β 2 ), for both ther lnear and quadratc terms (P < for β 1, P < for β 2, P = for β 11 and P = for β 22 ), as well as ther nteracton (P < for β 12 ). In the same manner, the dasher speed had a sgnfcant effect on the draw temperature for ts lnear term (P = for β 3 ) and for ts nteracton wth the mx flow rate (P = for β 13 ). Regardng the mean chord length, we can observe from the ANOVA analyss shown n table 4, that the evaporaton temperature sgnfcantly affected MCL at a 95% confdence nterval n ts lnear and quadratc terms (P < for β 2 and P < for β 22 ). The dasher speed also sgnfcantly affected the MCL response n ts lnear term (P = for β 3 ). Whlst the mx flow rate dd not show a sgnfcant effect. Table 4. Regresson coeffcents of the expermental behavor model and sgnfcance levels at 95% (P-values) for responses of MCL and DT a. Intercepton Lnear Interacton Quadratc Response β 0 β 1 β 2 β 3 β 12 β 13 β 23 β 11 β 22 β 33 DT E E E-4 P-value < * < * < * * * * * * MCL E E E-5
5 ICR 2011, August Prague, Czech Republc P-value < * < * * < * a MCL = Mean Chord Length; DT = Draw temperature; Coeffcents (β) subndex : 1 = Mx flow rate; 2 = Evaporaton temperature R22; 3 = Dasher rotatonal speed; * = sgnfcant nfluence at 95% confdence nterval. The nfluence of operatng condtons on the draw temperature of sorbet s shown n Fgure 2, where we can observe the contour plots of the draw temperature behavour as a functon of the evaporaton temperature, mx flow rate and dasher speed. It can be seen n fgure 2 that the use of lower refrgerant s flud temperatures lead to lower product s temperatures and thus to hgher ce mass fractons (cf. Table 2, runs 10, 13 and 14), whch effect s undoubtedly due to the hgher amount of supercoolng appled to the product. Fgure 2. Influence of operatng condtons on the draw temperature of sorbet (n ºC). (A) Dasher speed set at rad.s -1. (B) Evaporaton temperature set at C. (C) Mx flow rate set at kg.s -1. We can also observe n fgure 2, that the relatonshp between the mx flow rate and the draw temperature of sorbet s drectly proportonal (cf. table 4, DT β1; table 2, ponts 9, 10 and 11). In other words, at a gven refrgerant's flud temperature, a decrease of the mx flow rate would lead to a reducton of the product s ext temperature. It s our opnon that ths effect s due to the longer resdence tme of the product wthn the freezer, when operatng at lower mx flow rates, snce the sorbet wll reman longer tme n contact wth the freezer wall, allowng more tme for heat removal, and therefore leadng to the decrease of the draw (ext) temperature, as well as to the ncrease of the ce mass fracton. Ben Lakhdar et al. (2005) also reported durng the freezng of 30% sucrose/water solutons, that low product's temperatures (hgh ce mass fractons) were obtaned by a reducton of the product s flow rate at a gven refrgerant's flud temperature. Also n fgure 2 (cf. plots B and C; table 4, DT β 3 ) we can see that the relatonshp between the draw temperature and the dasher speed s drectly proportonal. Therefore, an ncrease of the dasher speed would lead to a very slght ncrease of the draw temperature (cf. table 2, runs 10, 12 and 15). We consder that ths slght nfluence s due to a compensatory effect, between the frctonal energy produced by the scrapng acton of the dasher (whch s dsspated nto the product and ncreases ts temperature), and the mprovng of the heat transfer coeffcent between the product and the freezer wall (whch would reduce the draw temperature and compensate the warmng of the product). Russell et al. (1999) reported a more mportant
6 ICR 2011, August Prague, Czech Republc warmng of the ce cream, whch effect was attrbuted to the ncrease of the mechancal dsspaton, caused by the ncrease of the dasher speed. On the other hand, Ben Lakhdar et al. (2005) reported that an ncrease of the dasher speed mproves the heat transfer coeffcent, whch led to lower product temperatures. Fgure 3. Influence of operatng condtons on the mean chord length of sorbet (n µm). (A) Dasher speed set at rad.s -1. (B) Evaporaton temperature set at C. (C) Mx flow rate set at kg.s -1. Fgure 3 shows the contour plots of the mean ce crystal chord length response as a functon of the evaporaton temperature, mx flow rate and dasher speed. We can observe n fgure 3 (plot A and C), that the sgnfcant nfluence of TR22 s drectly proportonal to the MCL (cf. table 4, MCL β 2 and β 22 ). Ths means that the use of lower R22 evaporaton temperatures would lead to the reducton of the mean ce crystal chord length (cf. table 2, runs 10, 13 and 14). We beleve ths effect s due to the larger level of supercoolng to whch the sorbet s exposed to, when low refrgerant flud temperatures are used. Ths would mprove the heat removal rate, and enhance the ce nucleaton rate wthn the freezer, reducng thus the ce crystal sze. Koxholt et al. (2000) also found smaller values of ce CSD when lower refrgerant flud temperatures were employed. It s generally thought that shorter resdence tmes (hgher mx flow rates) lead to smaller ce CSD (Koxholt et al., 2000; Russell et al., 1999). However, as we can see n fgure 3 and table 4 (plots A and B; table 4, MCL β 1 ), the mx flow rate dd not show a sgnfcant nfluence on the mean ce crystal chord length. We are of the opnon that ths result s due to a compensatory effect that s produced wthn the freezer, ths s, when low mx flow rates are used (long resdence tmes), the draw temperature of sorbet decreases and smultaneously, ts ce mass fracton ncreases, as well as ts apparent vscosty (cf. table 4, runs 9, 10 and 11). Ths effect would lead to a hgher shear wthn the product, and enhance the attrton of the larger ce crystals, resultng n the producton of new ce nucle by secondary nucleaton. However, snce the resdence tme of the product s longer, the ce crystal coarsenng would be also enhanced, counteractng thus the ce nucleaton rate wthn the product. We can also observe n fgure 3 (plots B and C; table 4, MCL β 3 ) that an ncrease of the scrapng acton of the dasher slghtly reduces the mean ce crystal chord length (cf. table 2, runs 10, 12 and 15). We beleve that
7 ICR 2011, August Prague, Czech Republc ths nfluence s due to the hgher shear rate of the product that s generated when hgher dasher speeds are used, whch may lead to the producton of new smaller ce nucle by secondary nucleaton, nduced by the ce debrs produced from the attrton of the larger ce crystals. 4. CONCLUSIONS Our research has demonstrated that the FBRM sensor s a convenent tool that allowed us to follow onlne the evoluton of the ce crystal chord length n concentrated ce suspensons sorbets contanng up to 40% of ce. Our results have shown that the use of low evaporaton temperatures leads to the reducton of the mean ce crystal chord length and to the decrease of the draw temperature of sorbet, and whch effects are manly due to the hgher level of supercoolng appled to the product. An ncrease of the dasher speed would slghtly reduce the ce crystal chord length, due to the hgher shear of the product whch leads to the attrton of the ce crystals, and produces new smaller ce nucle by secondary nucleaton. Hgher dasher speeds would lead to a very slght ncrease of the draw temperature, due to the frctonal energy dsspated nto the product, whch effect s n part counteracted by the mprovng of the heat transfer coeffcent between the product and the freezer wall. Long resdence tmes (low mx flow rates) lead to the decreasng of the product s temperature, due to the fact that the product remans longer tme n contact wth the freezer wall, and therefore more heat s removed from the product. However, the mx flow rate dd not show a sgnfcant effect on the ce crystal sze. ACKNOWLEDGEMENTS The research leadng to these results has receved fundng from the European Communty's Seventh Framework Programme (FP7/ ) under grant agreement CAFÉ n KBBE REFERENCES 1. Haddad A., Benkhelfa H., Alvarez G., Flck D. (2010). Study of crystal sze evoluton by focused beam reflectance measurement durng the freezng of sucrose/water solutons n a scraped surface heat exchanger. Process Bochemstry. 2. Sablan S., Rahman S., Datta A. et Mujumdar A Handbook of Food and Boprocess Modellng. Chap. 9. Pages CRC Press. 3. Koxholt M., Esenmann B., Hnrchs, J. (2000). Effect of process parameters on the structure of ce cream. Possble methos of optmzng freezer technology. European Dary Magazne. January Russell A.B., Cheney P.E., Wantlng S.D. (1999). Influence of freezng condtons on ce crystallzaton n ce cream. Journal of Food Engneerng. 39: Ben Lakhdar M., Cerecero R., Alvarez G., Gulpart J., Flck D. Lallemand A. (2005). Heat transfer wth freezng n a scraped surface heat exchanger. Appled Thermal Engneerng. 25:45-60.
Online ice crystal size measurements by the focused beam reflectance method (FBRM) during sorbet freezing.
Onlne ce crystal sze measurements by the focused beam reflectance method (FBRM) durng sorbet freezng. M. Arellano a,b, J. E. Gonzalez a,b, G. Alvarez a, H. Benkhelfa b, D. Flck b, D. Leducq a a Cemagref.
More informationOnline ice crystal size measurements by the focused beam reflectance method (FBRM) during sorbet freezing.
Proceda Food Scence 1 (2011) 1256 1264 11 th Internatonal Congress on Engneerng and Food (ICEF11) Onlne ce crystal sze measurements by the focused beam reflectance method (FBRM) durng sorbet freezng. Marcela
More informationChapter 13: Multiple Regression
Chapter 13: Multple Regresson 13.1 Developng the multple-regresson Model The general model can be descrbed as: It smplfes for two ndependent varables: The sample ft parameter b 0, b 1, and b are used to
More informationStatistics II Final Exam 26/6/18
Statstcs II Fnal Exam 26/6/18 Academc Year 2017/18 Solutons Exam duraton: 2 h 30 mn 1. (3 ponts) A town hall s conductng a study to determne the amount of leftover food produced by the restaurants n the
More informationis the calculated value of the dependent variable at point i. The best parameters have values that minimize the squares of the errors
Multple Lnear and Polynomal Regresson wth Statstcal Analyss Gven a set of data of measured (or observed) values of a dependent varable: y versus n ndependent varables x 1, x, x n, multple lnear regresson
More informationNegative Binomial Regression
STATGRAPHICS Rev. 9/16/2013 Negatve Bnomal Regresson Summary... 1 Data Input... 3 Statstcal Model... 3 Analyss Summary... 4 Analyss Optons... 7 Plot of Ftted Model... 8 Observed Versus Predcted... 10 Predctons...
More informationComparison of Regression Lines
STATGRAPHICS Rev. 9/13/2013 Comparson of Regresson Lnes Summary... 1 Data Input... 3 Analyss Summary... 4 Plot of Ftted Model... 6 Condtonal Sums of Squares... 6 Analyss Optons... 7 Forecasts... 8 Confdence
More informationAnswers Problem Set 2 Chem 314A Williamsen Spring 2000
Answers Problem Set Chem 314A Wllamsen Sprng 000 1) Gve me the followng crtcal values from the statstcal tables. a) z-statstc,-sded test, 99.7% confdence lmt ±3 b) t-statstc (Case I), 1-sded test, 95%
More informationLab 2e Thermal System Response and Effective Heat Transfer Coefficient
58:080 Expermental Engneerng 1 OBJECTIVE Lab 2e Thermal System Response and Effectve Heat Transfer Coeffcent Warnng: though the experment has educatonal objectves (to learn about bolng heat transfer, etc.),
More informationLINEAR REGRESSION ANALYSIS. MODULE IX Lecture Multicollinearity
LINEAR REGRESSION ANALYSIS MODULE IX Lecture - 31 Multcollnearty Dr. Shalabh Department of Mathematcs and Statstcs Indan Insttute of Technology Kanpur 6. Rdge regresson The OLSE s the best lnear unbased
More informationDr. Shalabh Department of Mathematics and Statistics Indian Institute of Technology Kanpur
Analyss of Varance and Desgn of Experment-I MODULE VII LECTURE - 3 ANALYSIS OF COVARIANCE Dr Shalabh Department of Mathematcs and Statstcs Indan Insttute of Technology Kanpur Any scentfc experment s performed
More informationStatistics for Managers Using Microsoft Excel/SPSS Chapter 14 Multiple Regression Models
Statstcs for Managers Usng Mcrosoft Excel/SPSS Chapter 14 Multple Regresson Models 1999 Prentce-Hall, Inc. Chap. 14-1 Chapter Topcs The Multple Regresson Model Contrbuton of Indvdual Independent Varables
More information/ n ) are compared. The logic is: if the two
STAT C141, Sprng 2005 Lecture 13 Two sample tests One sample tests: examples of goodness of ft tests, where we are testng whether our data supports predctons. Two sample tests: called as tests of ndependence
More informationBy Dr. Erkan KARACABEY 1 Dr. Cem BALTACIOĞLU 2 and Dr. Erdoğan KÜÇÜÖNER 1
Optmzaton of ol uptake of predred and deep-fat-fred fred carrot slces as a functon of process condtons By Dr. Erkan KARACABEY 1 Dr. Cem BALTACIOĞLU 2 and Dr. Erdoğan KÜÇÜÖNER 1 1 Food Engneerng Deparment,
More informationDepartment of Quantitative Methods & Information Systems. Time Series and Their Components QMIS 320. Chapter 6
Department of Quanttatve Methods & Informaton Systems Tme Seres and Ther Components QMIS 30 Chapter 6 Fall 00 Dr. Mohammad Zanal These sldes were modfed from ther orgnal source for educatonal purpose only.
More informationWeek3, Chapter 4. Position and Displacement. Motion in Two Dimensions. Instantaneous Velocity. Average Velocity
Week3, Chapter 4 Moton n Two Dmensons Lecture Quz A partcle confned to moton along the x axs moves wth constant acceleraton from x =.0 m to x = 8.0 m durng a 1-s tme nterval. The velocty of the partcle
More informationSTATISTICS QUESTIONS. Step by Step Solutions.
STATISTICS QUESTIONS Step by Step Solutons www.mathcracker.com 9//016 Problem 1: A researcher s nterested n the effects of famly sze on delnquency for a group of offenders and examnes famles wth one to
More informationIntroduction to Vapor/Liquid Equilibrium, part 2. Raoult s Law:
CE304, Sprng 2004 Lecture 4 Introducton to Vapor/Lqud Equlbrum, part 2 Raoult s Law: The smplest model that allows us do VLE calculatons s obtaned when we assume that the vapor phase s an deal gas, and
More informationUNIVERSITY OF TORONTO Faculty of Arts and Science. December 2005 Examinations STA437H1F/STA1005HF. Duration - 3 hours
UNIVERSITY OF TORONTO Faculty of Arts and Scence December 005 Examnatons STA47HF/STA005HF Duraton - hours AIDS ALLOWED: (to be suppled by the student) Non-programmable calculator One handwrtten 8.5'' x
More informationLINEAR REGRESSION ANALYSIS. MODULE IX Lecture Multicollinearity
LINEAR REGRESSION ANALYSIS MODULE IX Lecture - 30 Multcollnearty Dr. Shalabh Department of Mathematcs and Statstcs Indan Insttute of Technology Kanpur 2 Remedes for multcollnearty Varous technques have
More informationStatistics for Managers Using Microsoft Excel/SPSS Chapter 13 The Simple Linear Regression Model and Correlation
Statstcs for Managers Usng Mcrosoft Excel/SPSS Chapter 13 The Smple Lnear Regresson Model and Correlaton 1999 Prentce-Hall, Inc. Chap. 13-1 Chapter Topcs Types of Regresson Models Determnng the Smple Lnear
More informationHere is the rationale: If X and y have a strong positive relationship to one another, then ( x x) will tend to be positive when ( y y)
Secton 1.5 Correlaton In the prevous sectons, we looked at regresson and the value r was a measurement of how much of the varaton n y can be attrbuted to the lnear relatonshp between y and x. In ths secton,
More informationTurbulence classification of load data by the frequency and severity of wind gusts. Oscar Moñux, DEWI GmbH Kevin Bleibler, DEWI GmbH
Turbulence classfcaton of load data by the frequency and severty of wnd gusts Introducton Oscar Moñux, DEWI GmbH Kevn Blebler, DEWI GmbH Durng the wnd turbne developng process, one of the most mportant
More informationPredictive Analytics : QM901.1x Prof U Dinesh Kumar, IIMB. All Rights Reserved, Indian Institute of Management Bangalore
Sesson Outlne Introducton to classfcaton problems and dscrete choce models. Introducton to Logstcs Regresson. Logstc functon and Logt functon. Maxmum Lkelhood Estmator (MLE) for estmaton of LR parameters.
More informationLecture Notes for STATISTICAL METHODS FOR BUSINESS II BMGT 212. Chapters 14, 15 & 16. Professor Ahmadi, Ph.D. Department of Management
Lecture Notes for STATISTICAL METHODS FOR BUSINESS II BMGT 1 Chapters 14, 15 & 16 Professor Ahmad, Ph.D. Department of Management Revsed August 005 Chapter 14 Formulas Smple Lnear Regresson Model: y =
More information2010 Black Engineering Building, Department of Mechanical Engineering. Iowa State University, Ames, IA, 50011
Interface Energy Couplng between -tungsten Nanoflm and Few-layered Graphene Meng Han a, Pengyu Yuan a, Jng Lu a, Shuyao S b, Xaolong Zhao b, Yanan Yue c, Xnwe Wang a,*, Xangheng Xao b,* a 2010 Black Engneerng
More informationChapter 11: Simple Linear Regression and Correlation
Chapter 11: Smple Lnear Regresson and Correlaton 11-1 Emprcal Models 11-2 Smple Lnear Regresson 11-3 Propertes of the Least Squares Estmators 11-4 Hypothess Test n Smple Lnear Regresson 11-4.1 Use of t-tests
More informationPHYS 450 Spring semester Lecture 02: Dealing with Experimental Uncertainties. Ron Reifenberger Birck Nanotechnology Center Purdue University
PHYS 45 Sprng semester 7 Lecture : Dealng wth Expermental Uncertantes Ron Refenberger Brck anotechnology Center Purdue Unversty Lecture Introductory Comments Expermental errors (really expermental uncertantes)
More informationProblem Set 9 Solutions
Desgn and Analyss of Algorthms May 4, 2015 Massachusetts Insttute of Technology 6.046J/18.410J Profs. Erk Demane, Srn Devadas, and Nancy Lynch Problem Set 9 Solutons Problem Set 9 Solutons Ths problem
More informationChapter 12 Analysis of Covariance
Chapter Analyss of Covarance Any scentfc experment s performed to know somethng that s unknown about a group of treatments and to test certan hypothess about the correspondng treatment effect When varablty
More informationLinear Approximation with Regularization and Moving Least Squares
Lnear Approxmaton wth Regularzaton and Movng Least Squares Igor Grešovn May 007 Revson 4.6 (Revson : March 004). 5 4 3 0.5 3 3.5 4 Contents: Lnear Fttng...4. Weghted Least Squares n Functon Approxmaton...
More informationx i1 =1 for all i (the constant ).
Chapter 5 The Multple Regresson Model Consder an economc model where the dependent varable s a functon of K explanatory varables. The economc model has the form: y = f ( x,x,..., ) xk Approxmate ths by
More informationPolynomial Regression Models
LINEAR REGRESSION ANALYSIS MODULE XII Lecture - 6 Polynomal Regresson Models Dr. Shalabh Department of Mathematcs and Statstcs Indan Insttute of Technology Kanpur Test of sgnfcance To test the sgnfcance
More informationCinChE Problem-Solving Strategy Chapter 4 Development of a Mathematical Model. formulation. procedure
nhe roblem-solvng Strategy hapter 4 Transformaton rocess onceptual Model formulaton procedure Mathematcal Model The mathematcal model s an abstracton that represents the engneerng phenomena occurrng n
More informationStatistics for Business and Economics
Statstcs for Busness and Economcs Chapter 11 Smple Regresson Copyrght 010 Pearson Educaton, Inc. Publshng as Prentce Hall Ch. 11-1 11.1 Overvew of Lnear Models n An equaton can be ft to show the best lnear
More information2016 Wiley. Study Session 2: Ethical and Professional Standards Application
6 Wley Study Sesson : Ethcal and Professonal Standards Applcaton LESSON : CORRECTION ANALYSIS Readng 9: Correlaton and Regresson LOS 9a: Calculate and nterpret a sample covarance and a sample correlaton
More informationStatistics Chapter 4
Statstcs Chapter 4 "There are three knds of les: les, damned les, and statstcs." Benjamn Dsrael, 1895 (Brtsh statesman) Gaussan Dstrbuton, 4-1 If a measurement s repeated many tmes a statstcal treatment
More informationExample: (13320, 22140) =? Solution #1: The divisors of are 1, 2, 3, 4, 5, 6, 9, 10, 12, 15, 18, 20, 27, 30, 36, 41,
The greatest common dvsor of two ntegers a and b (not both zero) s the largest nteger whch s a common factor of both a and b. We denote ths number by gcd(a, b), or smply (a, b) when there s no confuson
More informationChapter 14 Simple Linear Regression
Chapter 4 Smple Lnear Regresson Chapter 4 - Smple Lnear Regresson Manageral decsons often are based on the relatonshp between two or more varables. Regresson analss can be used to develop an equaton showng
More information(IP), II. EXPERIMENTAL SET-UP
Applcaton of Response Surface Methodology For Determnng MRR and TWR Model In De Snkng EDM of AISI 1045 Steel M. B. Patel* P. K. Patel* J. B. Patel* Prof. B. B. Patel** *(Fnal Year Under Graduate student,
More informationwhere I = (n x n) diagonal identity matrix with diagonal elements = 1 and off-diagonal elements = 0; and σ 2 e = variance of (Y X).
11.4.1 Estmaton of Multple Regresson Coeffcents In multple lnear regresson, we essentally solve n equatons for the p unnown parameters. hus n must e equal to or greater than p and n practce n should e
More informationWeek 9 Chapter 10 Section 1-5
Week 9 Chapter 10 Secton 1-5 Rotaton Rgd Object A rgd object s one that s nondeformable The relatve locatons of all partcles makng up the object reman constant All real objects are deformable to some extent,
More informationCOMPOSITE BEAM WITH WEAK SHEAR CONNECTION SUBJECTED TO THERMAL LOAD
COMPOSITE BEAM WITH WEAK SHEAR CONNECTION SUBJECTED TO THERMAL LOAD Ákos Jósef Lengyel, István Ecsed Assstant Lecturer, Professor of Mechancs, Insttute of Appled Mechancs, Unversty of Mskolc, Mskolc-Egyetemváros,
More informationA study on the effect of ball diameter on breakage properties of clinker and limestone
Indan Journal of Chemcal Technology Vol. 9, May 202, pp. 80-84 A study on the effect of ball dameter on breakage propertes of clnker and lmestone Vedat Denz* Department of Chemcal Engneerng, Htt Unversty,
More information829. An adaptive method for inertia force identification in cantilever under moving mass
89. An adaptve method for nerta force dentfcaton n cantlever under movng mass Qang Chen 1, Mnzhuo Wang, Hao Yan 3, Haonan Ye 4, Guola Yang 5 1,, 3, 4 Department of Control and System Engneerng, Nanng Unversty,
More informationEVALUATION OF THE VISCO-ELASTIC PROPERTIES IN ASPHALT RUBBER AND CONVENTIONAL MIXES
EVALUATION OF THE VISCO-ELASTIC PROPERTIES IN ASPHALT RUBBER AND CONVENTIONAL MIXES Manuel J. C. Mnhoto Polytechnc Insttute of Bragança, Bragança, Portugal E-mal: mnhoto@pb.pt Paulo A. A. Perera and Jorge
More informationLecture 16 Statistical Analysis in Biomaterials Research (Part II)
3.051J/0.340J 1 Lecture 16 Statstcal Analyss n Bomaterals Research (Part II) C. F Dstrbuton Allows comparson of varablty of behavor between populatons usng test of hypothess: σ x = σ x amed for Brtsh statstcan
More informationKernel Methods and SVMs Extension
Kernel Methods and SVMs Extenson The purpose of ths document s to revew materal covered n Machne Learnng 1 Supervsed Learnng regardng support vector machnes (SVMs). Ths document also provdes a general
More informationAn identification algorithm of model kinetic parameters of the interfacial layer growth in fiber composites
IOP Conference Seres: Materals Scence and Engneerng PAPER OPE ACCESS An dentfcaton algorthm of model knetc parameters of the nterfacal layer growth n fber compostes o cte ths artcle: V Zubov et al 216
More informationTorsion Stiffness of Thin-walled Steel Beams with Web Holes
Torson Stffness of Thn-walled Steel Beams wth Web Holes MARTN HORÁČEK, JNDŘCH MELCHER Department of Metal and Tmber Structures Brno Unversty of Technology, Faculty of Cvl Engneerng Veveří 331/95, 62 Brno
More informationSTAT 511 FINAL EXAM NAME Spring 2001
STAT 5 FINAL EXAM NAME Sprng Instructons: Ths s a closed book exam. No notes or books are allowed. ou may use a calculator but you are not allowed to store notes or formulas n the calculator. Please wrte
More informationPhysics 207: Lecture 20. Today s Agenda Homework for Monday
Physcs 207: Lecture 20 Today s Agenda Homework for Monday Recap: Systems of Partcles Center of mass Velocty and acceleraton of the center of mass Dynamcs of the center of mass Lnear Momentum Example problems
More informationPrinciples of Food and Bioprocess Engineering (FS 231) Solutions to Example Problems on Heat Transfer
Prncples of Food and Boprocess Engneerng (FS 31) Solutons to Example Problems on Heat Transfer 1. We start wth Fourer s law of heat conducton: Q = k A ( T/ x) Rearrangng, we get: Q/A = k ( T/ x) Here,
More informationModeling of Dynamic Systems
Modelng of Dynamc Systems Ref: Control System Engneerng Norman Nse : Chapters & 3 Chapter objectves : Revew the Laplace transform Learn how to fnd a mathematcal model, called a transfer functon Learn how
More informationAdiabatic Sorption of Ammonia-Water System and Depicting in p-t-x Diagram
Adabatc Sorpton of Ammona-Water System and Depctng n p-t-x Dagram J. POSPISIL, Z. SKALA Faculty of Mechancal Engneerng Brno Unversty of Technology Techncka 2, Brno 61669 CZECH REPUBLIC Abstract: - Absorpton
More informationAssignment 5. Simulation for Logistics. Monti, N.E. Yunita, T.
Assgnment 5 Smulaton for Logstcs Mont, N.E. Yunta, T. November 26, 2007 1. Smulaton Desgn The frst objectve of ths assgnment s to derve a 90% two-sded Confdence Interval (CI) for the average watng tme
More informationTemperature. Chapter Heat Engine
Chapter 3 Temperature In prevous chapters of these notes we ntroduced the Prncple of Maxmum ntropy as a technque for estmatng probablty dstrbutons consstent wth constrants. In Chapter 9 we dscussed the
More informationStatistics for Economics & Business
Statstcs for Economcs & Busness Smple Lnear Regresson Learnng Objectves In ths chapter, you learn: How to use regresson analyss to predct the value of a dependent varable based on an ndependent varable
More informationStatistics MINITAB - Lab 2
Statstcs 20080 MINITAB - Lab 2 1. Smple Lnear Regresson In smple lnear regresson we attempt to model a lnear relatonshp between two varables wth a straght lne and make statstcal nferences concernng that
More informationSTUDY OF A THREE-AXIS PIEZORESISTIVE ACCELEROMETER WITH UNIFORM AXIAL SENSITIVITIES
STUDY OF A THREE-AXIS PIEZORESISTIVE ACCELEROMETER WITH UNIFORM AXIAL SENSITIVITIES Abdelkader Benchou, PhD Canddate Nasreddne Benmoussa, PhD Kherreddne Ghaffour, PhD Unversty of Tlemcen/Unt of Materals
More informationAssessment of Site Amplification Effect from Input Energy Spectra of Strong Ground Motion
Assessment of Ste Amplfcaton Effect from Input Energy Spectra of Strong Ground Moton M.S. Gong & L.L Xe Key Laboratory of Earthquake Engneerng and Engneerng Vbraton,Insttute of Engneerng Mechancs, CEA,
More informationTransfer Functions. Convenient representation of a linear, dynamic model. A transfer function (TF) relates one input and one output: ( ) system
Transfer Functons Convenent representaton of a lnear, dynamc model. A transfer functon (TF) relates one nput and one output: x t X s y t system Y s The followng termnology s used: x y nput output forcng
More informationNumber Average Molar Mass. Mass Average Molar Mass. Z-Average Molar Mass
17 Molar mass: There are dfferent ways to report a molar mass lke (a) Number average molar mass, (b) mass average molar mass, (c) Vscosty average molar mass, (d) Z- Average molar mass Number Average Molar
More informationThermal-Fluids I. Chapter 18 Transient heat conduction. Dr. Primal Fernando Ph: (850)
hermal-fluds I Chapter 18 ransent heat conducton Dr. Prmal Fernando prmal@eng.fsu.edu Ph: (850) 410-6323 1 ransent heat conducton In general, he temperature of a body vares wth tme as well as poston. In
More informationIf two volatile and miscible liquids are combined to form a solution, Raoult s law is not obeyed. Use the experimental data in Table 9.
9.9 Real Solutons Exhbt Devatons from Raoult s Law If two volatle and mscble lquds are combned to form a soluton, Raoult s law s not obeyed. Use the expermental data n Table 9.3: Physcal Chemstry 00 Pearson
More informationDUE: WEDS FEB 21ST 2018
HOMEWORK # 1: FINITE DIFFERENCES IN ONE DIMENSION DUE: WEDS FEB 21ST 2018 1. Theory Beam bendng s a classcal engneerng analyss. The tradtonal soluton technque makes smplfyng assumptons such as a constant
More informationPh.D. Qualifying Examination in Kinetics and Reactor Design
Knetcs and Reactor Desgn Ph.D.Qualfyng Examnaton January 2006 Instructons Ph.D. Qualfyng Examnaton n Knetcs and Reactor Desgn January 2006 Unversty of Texas at Austn Department of Chemcal Engneerng 1.
More informationModule 3 LOSSY IMAGE COMPRESSION SYSTEMS. Version 2 ECE IIT, Kharagpur
Module 3 LOSSY IMAGE COMPRESSION SYSTEMS Verson ECE IIT, Kharagpur Lesson 6 Theory of Quantzaton Verson ECE IIT, Kharagpur Instructonal Objectves At the end of ths lesson, the students should be able to:
More informationNumerical Heat and Mass Transfer
Master degree n Mechancal Engneerng Numercal Heat and Mass Transfer 06-Fnte-Dfference Method (One-dmensonal, steady state heat conducton) Fausto Arpno f.arpno@uncas.t Introducton Why we use models and
More informationNUMERICAL DIFFERENTIATION
NUMERICAL DIFFERENTIATION 1 Introducton Dfferentaton s a method to compute the rate at whch a dependent output y changes wth respect to the change n the ndependent nput x. Ths rate of change s called the
More informationBoostrapaggregating (Bagging)
Boostrapaggregatng (Baggng) An ensemble meta-algorthm desgned to mprove the stablty and accuracy of machne learnng algorthms Can be used n both regresson and classfcaton Reduces varance and helps to avod
More informationGouy-Chapman model (1910) The double layer is not as compact as in Helmholtz rigid layer.
CHE465/865, 6-3, Lecture 1, 7 nd Sep., 6 Gouy-Chapman model (191) The double layer s not as compact as n Helmholtz rgd layer. Consder thermal motons of ons: Tendency to ncrease the entropy and make the
More informationMEASUREMENT OF MOMENT OF INERTIA
1. measurement MESUREMENT OF MOMENT OF INERTI The am of ths measurement s to determne the moment of nerta of the rotor of an electrc motor. 1. General relatons Rotatng moton and moment of nerta Let us
More informationDesign and Manufacturing Engineering Department, Politeknik Perkapalan Negeri Surabaya, Surabaya, Indonesia 2
OPTIMIZATION OF MULTIPLE PERFORMANCE CHARACTERISTICS IN WIRE ELECTRICAL DISCHARGE MACHINING (WEDM) PROCESS OF BUDERUS 28 TOOL STEEL USING TAGUCHI-GREY- FUZZY METHOD D. A. Purnomo 1,2, B. O. P. Soepangkat
More informationNANYANG TECHNOLOGICAL UNIVERSITY SEMESTER I EXAMINATION MTH352/MH3510 Regression Analysis
NANYANG TECHNOLOGICAL UNIVERSITY SEMESTER I EXAMINATION 014-015 MTH35/MH3510 Regresson Analyss December 014 TIME ALLOWED: HOURS INSTRUCTIONS TO CANDIDATES 1. Ths examnaton paper contans FOUR (4) questons
More informationCorrelation and Regression. Correlation 9.1. Correlation. Chapter 9
Chapter 9 Correlaton and Regresson 9. Correlaton Correlaton A correlaton s a relatonshp between two varables. The data can be represented b the ordered pars (, ) where s the ndependent (or eplanator) varable,
More informationUNR Joint Economics Working Paper Series Working Paper No Further Analysis of the Zipf Law: Does the Rank-Size Rule Really Exist?
UNR Jont Economcs Workng Paper Seres Workng Paper No. 08-005 Further Analyss of the Zpf Law: Does the Rank-Sze Rule Really Exst? Fungsa Nota and Shunfeng Song Department of Economcs /030 Unversty of Nevada,
More informationFinancing Innovation: Evidence from R&D Grants
Fnancng Innovaton: Evdence from R&D Grants Sabrna T. Howell Onlne Appendx Fgure 1: Number of Applcants Note: Ths fgure shows the number of losng and wnnng Phase 1 grant applcants over tme by offce (Energy
More informationIce crytal nucleaton, growth and breakage modellng n a craped urface heat exchanger H. Benkhelfa (a, M. Arellano (a,b G. Alvarez (b, D. Flck (a (a UMR n 45 AgroParTech/INRA, Ingénere-Procédé-Alment, 6
More informationAssignment 4. Adsorption Isotherms
Insttute of Process Engneerng Assgnment 4. Adsorpton Isotherms Part A: Compettve adsorpton of methane and ethane In large scale adsorpton processes, more than one compound from a mxture of gases get adsorbed,
More informationGlobal Sensitivity. Tuesday 20 th February, 2018
Global Senstvty Tuesday 2 th February, 28 ) Local Senstvty Most senstvty analyses [] are based on local estmates of senstvty, typcally by expandng the response n a Taylor seres about some specfc values
More informationThis column is a continuation of our previous column
Comparson of Goodness of Ft Statstcs for Lnear Regresson, Part II The authors contnue ther dscusson of the correlaton coeffcent n developng a calbraton for quanttatve analyss. Jerome Workman Jr. and Howard
More informationDECADAL DECLINE ( )OF LOGGERHEAD SHRIKES ON CHRISTMAS BIRD COUNTS IN ALABAMA, MISSISSIPPI, AND TENNESSEE
DEPARTMENT OF MATHEMATICS TECHNICAL REPORT DECADAL DECLINE (1992-22)OF LOGGERHEAD SHRIKES ON CHRISTMAS BIRD COUNTS IN ALABAMA, MISSISSIPPI, AND TENNESSEE DR. STEPHEN J. STEDMAN AND DR. MICHAEL ALLEN AUGUST
More informationChapter 8 Indicator Variables
Chapter 8 Indcator Varables In general, e explanatory varables n any regresson analyss are assumed to be quanttatve n nature. For example, e varables lke temperature, dstance, age etc. are quanttatve n
More informationA Robust Method for Calculating the Correlation Coefficient
A Robust Method for Calculatng the Correlaton Coeffcent E.B. Nven and C. V. Deutsch Relatonshps between prmary and secondary data are frequently quantfed usng the correlaton coeffcent; however, the tradtonal
More informationFirst Year Examination Department of Statistics, University of Florida
Frst Year Examnaton Department of Statstcs, Unversty of Florda May 7, 010, 8:00 am - 1:00 noon Instructons: 1. You have four hours to answer questons n ths examnaton.. You must show your work to receve
More informationDO NOT OPEN THE QUESTION PAPER UNTIL INSTRUCTED TO DO SO BY THE CHIEF INVIGILATOR. Introductory Econometrics 1 hour 30 minutes
25/6 Canddates Only January Examnatons 26 Student Number: Desk Number:...... DO NOT OPEN THE QUESTION PAPER UNTIL INSTRUCTED TO DO SO BY THE CHIEF INVIGILATOR Department Module Code Module Ttle Exam Duraton
More informationBasically, if you have a dummy dependent variable you will be estimating a probability.
ECON 497: Lecture Notes 13 Page 1 of 1 Metropoltan State Unversty ECON 497: Research and Forecastng Lecture Notes 13 Dummy Dependent Varable Technques Studenmund Chapter 13 Bascally, f you have a dummy
More informationName: SID: Discussion Session:
Name: SID: Dscusson Sesson: Chemcal Engneerng Thermodynamcs 141 -- Fall 007 Thursday, November 15, 007 Mdterm II SOLUTIONS - 70 mnutes 110 Ponts Total Closed Book and Notes (0 ponts) 1. Evaluate whether
More informationChapter 11: I = 2 samples independent samples paired samples Chapter 12: I 3 samples of equal size J one-way layout two-way layout
Serk Sagtov, Chalmers and GU, February 0, 018 Chapter 1. Analyss of varance Chapter 11: I = samples ndependent samples pared samples Chapter 1: I 3 samples of equal sze one-way layout two-way layout 1
More informationCOMPARISON OF SOME RELIABILITY CHARACTERISTICS BETWEEN REDUNDANT SYSTEMS REQUIRING SUPPORTING UNITS FOR THEIR OPERATIONS
Avalable onlne at http://sck.org J. Math. Comput. Sc. 3 (3), No., 6-3 ISSN: 97-537 COMPARISON OF SOME RELIABILITY CHARACTERISTICS BETWEEN REDUNDANT SYSTEMS REQUIRING SUPPORTING UNITS FOR THEIR OPERATIONS
More informationChapter 6. Supplemental Text Material
Chapter 6. Supplemental Text Materal S6-. actor Effect Estmates are Least Squares Estmates We have gven heurstc or ntutve explanatons of how the estmates of the factor effects are obtaned n the textboo.
More informationMACHINE APPLIED MACHINE LEARNING LEARNING. Gaussian Mixture Regression
11 MACHINE APPLIED MACHINE LEARNING LEARNING MACHINE LEARNING Gaussan Mture Regresson 22 MACHINE APPLIED MACHINE LEARNING LEARNING Bref summary of last week s lecture 33 MACHINE APPLIED MACHINE LEARNING
More informationCHAPTER 14 GENERAL PERTURBATION THEORY
CHAPTER 4 GENERAL PERTURBATION THEORY 4 Introducton A partcle n orbt around a pont mass or a sphercally symmetrc mass dstrbuton s movng n a gravtatonal potental of the form GM / r In ths potental t moves
More informationCopyright 2017 by Taylor Enterprises, Inc., All Rights Reserved. Adjusted Control Limits for P Charts. Dr. Wayne A. Taylor
Taylor Enterprses, Inc. Control Lmts for P Charts Copyrght 2017 by Taylor Enterprses, Inc., All Rghts Reserved. Control Lmts for P Charts Dr. Wayne A. Taylor Abstract: P charts are used for count data
More informationMAE140 - Linear Circuits - Winter 16 Final, March 16, 2016
ME140 - Lnear rcuts - Wnter 16 Fnal, March 16, 2016 Instructons () The exam s open book. You may use your class notes and textbook. You may use a hand calculator wth no communcaton capabltes. () You have
More informationPsychology 282 Lecture #24 Outline Regression Diagnostics: Outliers
Psychology 282 Lecture #24 Outlne Regresson Dagnostcs: Outlers In an earler lecture we studed the statstcal assumptons underlyng the regresson model, ncludng the followng ponts: Formal statement of assumptons.
More informationLinear Regression Analysis: Terminology and Notation
ECON 35* -- Secton : Basc Concepts of Regresson Analyss (Page ) Lnear Regresson Analyss: Termnology and Notaton Consder the generc verson of the smple (two-varable) lnear regresson model. It s represented
More informationRegulation No. 117 (Tyres rolling noise and wet grip adhesion) Proposal for amendments to ECE/TRANS/WP.29/GRB/2010/3
Transmtted by the expert from France Informal Document No. GRB-51-14 (67 th GRB, 15 17 February 2010, agenda tem 7) Regulaton No. 117 (Tyres rollng nose and wet grp adheson) Proposal for amendments to
More informationTHE ROYAL STATISTICAL SOCIETY 2006 EXAMINATIONS SOLUTIONS HIGHER CERTIFICATE
THE ROYAL STATISTICAL SOCIETY 6 EXAMINATIONS SOLUTIONS HIGHER CERTIFICATE PAPER I STATISTICAL THEORY The Socety provdes these solutons to assst canddates preparng for the eamnatons n future years and for
More information