Loyola College Question Paper 2007

Loyola College M.Sc. Statistics April 2007 Reliability Theory Question Paper PDF Download

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LOYOLA COLLEGE (AUTONOMOUS), CHENNAI – 600 034

AC 57

M.Sc. DEGREE EXAMINATION – STATISTICS

FOURTH SEMESTER – APRIL 2007

ST 4955 – RELIABILITY THEORY

 

 

 

Date & Time: 25/04/2007 / 9:00 – 12:00      Dept. No.                                       Max. : 100 Marks

 

 

SECTION-A (10 × 2 = 20 marks)

Answer ALL the questions. Each question carries TWO marks

  1. Define the structure function of the system. Write down the structure function for k  out of  n structure.

 

  1. If x is a path vector and y ≥ x, show that y is also a path vector.
  2. If X1, X2, …, Xn are associated binary random variables, show that

(1-X1),(1-X2),…,(1-Xn) are  also  associated binary random variables.

  1. Show that F is IFRA if and only if (αt) ≥ α(t) for all 0<α<1 and t≥0.
  2. What  do you mean by
  • the number of critical path vectors of component i and
  • relative importance of component i?

 

  1. Define the terms:
  • System Reliability
  • Steady state availability

 

  1. If r(t) = λ; λ,t>0, obtain the corresponding probability distribution of time to failure.

 

  1. In the usual notation, show that MTBF = R*(0).

 

  1. Obtain the reliability of a parallel system consisting of n components, when the reliability of each component is known. Assume that the units are non-repairable.

 

  1. Explain in detail an n unit standby system.

 

SECTION- B (5 × 8=40marks)

Answer any FIVE questions. Each question carries EIGHT marks

 

  1. Consider 2 out of 3 system. Determine the number of critical path vectors of each component. Also determine the relative importance of each component. Are all the three components equally important?

 

  1. Let h be the reliability function of a coherent system. Show that

h( p Ц p‘) ≥ h( p )  Ц  h( p‘)for all 0  ≤ p , p‘ ≤ 1.

Also show that the equality holds if and only if the system is parallel.

 

  1. Suppose T1, T2, T3,…,Tn  are the random variables that are associated. Show that
  1. any subset of the associated random variables is also associated
  2. A set consisting of a single random variable is associated.

 

 

 

 

 

 

 

  1. If X1, X2, …, Xn are associated binary random variables show that

n                 n

  1. a) P [ Π Xi=1] ≥ Π P [ Xi=1]

i=1              i=1

 

n                 n

  1. b) P [ Ц Xi=1] ≤   Ц P [ Xi=1]

i=1              i=1

 

  1. Obtain the reliability function, hazard rate and system MTBF for PH-distribution with representation (α, T).

 

  1. What is a series system? Obtain the system failure time density function for a series system with n independent components. Suppose each of the n independent components has an exponential failure time distribution with constant failure rate λi, i= 1,2,…,n. Find the system reliability.

 

  1. Suppose that gi(t) is the density function for Ti , the time to failure of i th component in a standby system with two independent components and is given by

gi(t) = λi e– λit, i=1,2; λ1≠ λ2.

Obtain the system failure time density function and hence find its expected value.

 

  1. Find the mean life time of a (2,3) system of independent components, when the component lifetimes are uniformly distributed on ( 0, i ), i =1,2,3.

 

SECTION –C (2 × 20=40)

Answer any TWO questions. Each question carries TWENTY marks

 

  1.  a) Show that increasing functions of associated random variables are associated.
  1. b) Show that order statistics Y1:n,Y2:n,…,Yn:n corresponding to n independent

random variables are associated.

  1. c) Give an example of a set of random variables that are not associated. (6+8+6)
  1.  a) If the probability density function of F exists, show that F is an IFR

distribution iff  r(t)↑t

  1. b) Show that Wiebull distribution is a DFR distribution. Hence or otherwise,

establish that exponential distribution is both IFR and DFR.      (10+10)

  1.  a) Obtain the reliability function, hazard rate and the system MTBF for Gamma

distribution with the parameters λ and p.

  1. b) Suppose that gi(t) is the density function for the Ti, the time to failure of i th

component in a standby system with two independent and identical components

and is given by gi(t) = λe– λt, i=1,2; λ,t>0. Obtain the system failure time

density function and hence find its expected value.                      (12+8)

  1. a)  Define the terms: (i) System availability.

(ii) Hazard rate                                                  (4 marks)

  1. A system consists of a single unit, whose lifetime X and repair time Y are

independent random variables with probability density functions f(.) and g(.)

respectively. Assume that initially at time zero, the unit just begins to operate.

Determine the reliability, availability and steady state availability of the

system.                                                                                          (4+6+6)

 

 

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Loyola College M.Sc. Statistics April 2007 Probability Theory Question Paper PDF Download

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LOYOLA COLLEGE (AUTONOMOUS), CHENNAI – 600 034

M.Sc. DEGREE EXAMINATION – STATISTICS

 

SECOND SEMESTER – APRIL 2007

ST 2805 / 2800 – PROBABILITY THEORY

 

 

 

Date & Time: 27/04/2007 / 1:00 – 4:00 Dept. No.                                            Max. : 100 Marks

 

 

Section – A

Answer all the Questions                                                         10 x 2 = 20

 

  1. With reference to tossing a regular coin once and noting the outcome, identify completely all the elements of the probability space. (W,       , P).
  2. Show that the limit of any convergent sequence of events is an event.
  3. Define a random variable and its probability distribution.
  4. If X is a random variable with continuous distribution functions F, obtain the probability of distribution of F(X).
  5. Write down any two properties of the distribution function of a random vector (X,Y).
  6. If X2 and Y2 are independent, are X and Y independent?
  7. Define (i) convergence in quadratic mean and   (ii) convergence in distribution for a sequence of random variables.
  8. If  f  is the characteristic function (CF) of a random variable X, find the CF of (3X+2).
  9. State Kolmogorov’s strong law of large numbers(SLLN).
  10. State Linde berg – Feller central limit theorem.

 

SECTION – B

Answer any FIVE questions.                                                  5 x 8 = 40

 

  1. If X  and Y are independent, show that the characteristic function of X+Y is the product of their characteristic functions.  Is the converse true?  Justify.
  2. State and prove Minkowski’s inequality.
  3. Show that convergence in probability implies convergence in distribution.
  4. State and prove Borel zero – one law.
  5. Find the variance of Y, if the conditional characteristic function of Y given X=x is      and X has frequency function

for x  ³ 1

f (x) =

0,  otherwise

 

  1. Show that Xn  ® X in probability if and only if every subsequence of {Xn} contains a further subsequence, with convergence almost surely.
  2. Using the central limit theorem for suitable Poison random variables, prove that

=

 

 

  1. Deduce Liapounov theorem from Lindeberg – Feller theorem.

 

 

Section – C

Answer any TWO questions                                                   2 x 20 = 40

 

  1. a) Show that the probability distribution of a random variable is determined by its

distribution function.  Is the converse true?                                        (8  marks)

  1. b) Show that the vector X = (X1, X2, …, Xp)  is a random vector if and only Xi,  i=1,2,…p is a real

random variable.                                                                                                          (8 marks)

  1. c) The distribution function of a random variable X is given by

 

0       if  x < 0

F(x) =          if 0 £ x < 1

1       if  1 £ x < ¥

 

Obtain E(X).                                                                                       (4 marks)

 

  1. a) State and prove Kolmogorov zero – one law for a sequence of independent
    random variables. (10 marks)
  2. b) If {Xn , n ³ 1} is a sequence of independent and identically distributed random
    variables with common frequency function e-x,  x  > 0,

prove that P[lim sup   ]=1

(10 marks)

  1. a) State and prove Kolmogorov three series theorem for almost sure convergence
    of the series S Xn of independent random variables.                         (12 marks)
  2. b) Show that convergence in quadratic mean implies convergence in probability.
    Illustrate by an example that the converse is not true.                         (8 marks)

 

  1. a) State and prove Levy continuity theorem for a sequence of characteristic
    functions.           (10 marks)

 

  1. b) State and prove Inversion theorem.           (10 marks)

 

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Loyola College M.Sc. Statistics April 2007 Multivariate Analysis Question Paper PDF Download

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LOYOLA COLLEGE (AUTONOMOUS), CHENNAI – 600 034

AC 43

M.Sc. DEGREE EXAMINATION – STATISTICS

THIRD SEMESTER – APRIL 2007

ST 3801/ 3805 / 3808 – MULTIVARIATE ANALYSIS

 

 

 

Date & Time: 24/04/2007 / 9:00 – 12:00      Dept. No.                                       Max. : 100 Marks

 

 

 

SECTION A

 

10 X 2 =20

 

ANSWER ALL QUESTIONS. EACH CARRIES TWO MARKS

 

 

  1. Write the likelihood function corresponding to a sample of size drawn from .
  2. Mention any two applications of F-distribution in Multivariate Statistical Analysis.
  3. Find the distribution of if.
  4. Mention any two properties of variance-covariance matrix.
  5. How will you obtain the MLE of population correlation coefficient between two variables having bivariate normal distribution?
  6. What do mean by agglomerative algorithms?
  7. Define : Communalities
  8. Define Non-central Chi-square statistic.
  9. What is meant by “Expected Cost of Misclassification”?
  10. Give an unbiased estimator of variance-covariance matrix in

 

 

SECTION B

 

5 X 8 = 40

 

ANSWER ANY FIVE. EACH CARRIES EIGHT MARKS

 

  1. Derive the distribution of where and is a matrix of rank

 

  1. State and prove a characterization of multivariate normal distribution

 

  1. Obtain an expression of under usual notations.

 

  1. Obtain the rule which minimizes Expected Cost of Misclassification(ECM) in the case of two multivariate normal populations assuming priori probabilities are known to be equal and the populations have equal variance-covariance matrices.
  2. Show that where B,C,D and E are matrices of suitable order and mention any two places the above identity is used in multivariate analysis.

 

 

  1. State and prove any two properties of Wishart’s Distribution.

 

  1. Define Generalized variance. Show it is equal to the product of eigen roots of

 

 

  1. Obtain expressions for the first r-principal components in a p-variate normal distribution.

 

SECTION C

 

2 X 20 = 40

 

ANSWER ANY TWO. EACH CARRIES TWENTY MARKS

 

  1. Derive the conditional distribution of a sub vector of
  2. Derive the sampling distribution sample correlation coefficient assuming the population multiple correlation coefficient is zero.

 

  1. Derive the likelihood ratio test for assigned mean based on a sample of size N drawn from assuming is unknown.

 

  1. Write short notes of the following :
  • Similarity and Distance Measures.
  • Discriminant Analysis
  • Cluster Analysis
  • Orthogonal Factor Model

 

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Loyola College M.Sc. Statistics April 2007 Measure And Probability Question Paper PDF Download

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LOYOLA COLLEGE (AUTONOMOUS), CHENNAI – 600 034

M.Sc. DEGREE EXAMINATION – STATISTICS

AC 27

FIRST SEMESTER – APRIL 2007

ST 1809 – MEASURE AND PROBABILITY

 

 

 

Date & Time: 27/04/2007 / 1:00 – 4:00      Dept. No.                                       Max. : 100 Marks

 

 

 

Part A

Answer all the questions.                                                                            10 X 2 = 20

 

  1. Define set of all real numbers as follows. Let An = ( -1/n, 1] if n is odd and

An = ( -1, 1/n] if n is even. Find lim sup An and lim inf An?

  1. Explain Lebesgue-Stieltjes measure with an example.
  2. Define counter measure with an example.
  3. State Borel- Cantelli Lemma.
  4. If h is B– measurable function then show that | h | is also B-measurable

function.

  1. What is induced probability space?
  2. If random variable X takes only positive integral values then show that

E(X) = P[ X ³ n].

  1. Define convergence in r-th mean.
  2. Explain Fatou’s lemma.
  3. State Jordan-Hahn decomposition theorem.

Part B

Answer any five questions.                                                                     5 X 8 = 40

 

  1. If { Ai , i ³ 1) is a sequence of subsets of a set W then show that

Ai = (A i  – A i – 1).

  1. Show that countable additivity of a set function with m(f) = 0 implies finite additivity of a set function.
  2. Prove that every finite measure is a s – finite measure. Is the converse true? Justify.
  3. Let f be B-measurable and if f = 0 a.e. [m] then show that f dm = 0.
  4. State and establish additivity theorem of integral.

 

 

  1. State and establish Minkowski’s inequality.
  2. If XnX then show that (Xn2 + Xn) (X2 + X).
  3. State and establish Levy’s theorem.

Part C

Answer any two questions.                                                                   2 X 20 = 40

 

  1. a). State and establish extended monotone convergence theorem.

b). State and establish basic integration theorem.                                                                  ( 12 + 8)

  1. a). Let Á0 be a field of subsets of W. Let P be a probability measure on

Á0. Let     { An , n ³ 1}and  {Bn,  n ³ 1} be two increasing sequence of sets such that

lim (An) Ì lim (Bn). Then prove that lim P(An) £ lim P(Bn)

b). Define absolute continuity of measures. Show that l << m if and only if  ½l½ << m.

(8 + 12)

  1.  a). Show that Xn  X implies Xn   X. Is the converse true? Justify.

If Xn  C then show that Xn  C, where C is constant.

 

b). State and establish Lindberg Central limit theorem.                                                         (8 + 12)

  1. a). If hdm exists and C є R then show that Chdm = Cdm.

b). If Xn  X and g is continuous then show that g(Xn)  g (X).

(12 + 8)

 

 

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Loyola College M.Sc. Statistics April 2007 Industrial Statistics Question Paper PDF Download

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LOYOLA COLLEGE (AUTONOMOUS), CHENNAI – 600 034

M.Sc. DEGREE EXAMINATION – STATISTICS

AC 48

FOURTH SEMESTER – APRIL 2007

ST 4801 – INDUSTRIAL STATISTICS

 

 

 

Date & Time: 18/04/2007 / 9:00 – 12:00          Dept. No.                                                          Max. : 100 Marks

 

 

SECTION A  

Answer all the questions                                                                             10 x 2 = 20

 

  1. Define rational subgroup concept.
  2. What are chance and assignable causes of variation?
  3. What information is provided by the OC curve of a control chart?
  4. Write down the expression for process capability ratio (PCR) when only the lower specification is known.
  5. Why is the np chart not appropriate with variable sample size?
  6. What is an Average Run Length (ARL)?
  7. Explain an attribute single sampling plan.
  8. Give an expression for AOQ for a single sampling plan.
  9. What is a control chart?
  10. Write a short note an multivariate quality control chart

 

SECTION B  

Answer any five questions                                                              5 x 8= 40

 

  1. A quality characteristic is monitored by a control chart designed so that the probability that a certain out of control condition will be detected on the first sample following the shift to that is 1 – b. Find the following:

a). The probability that the out of control condition will be detected on the second sample following the shift.

b). The expected number of subgroups analyzed before the shift is detected.

  1. A control chart for the fraction non-conforming is to be established using a CL of p = 0.10. What sample size is required if we wish to detect a shift in the process fraction non-conforming to 0.20 with probability 0.50?
  2. Explain the method of constructing control limits for and R charts when the sample sizes are constant.
  3. In designing a fraction non-conforming chart with CL at p =0.20 and 3-sigma control limits, what is the simple size required to yield a positive LCL? What is the value of n necessary to give a probability of .50 of detecting a shift in the process to 0.26?
  4. Estimate process capability using  and R charts for the power supply voltage data. If specifications are at 350 ± 5 V, calculate PCR, PCRk and PCRkm. Interpret these capability ratios.

Sample

  1. 1 2          3          4          5          6          7          8          9          10

x1 :       6          10        7          8          9          12        16        7          9          15

x2:        9          4          8          9          10        11        10        5          7          16

x3:        10        6          10        6          7          10        8          10        8          10

x4:        15        11        5          13        13        10        9          4          12        13

  1. Find a single sampling plan for which p1 = 0.05, a = 0.05 p2 = 0.15 and b = 0.10.
  2. What is chain sampling and skip-lot sampling plans?
  3. Write short notes on V-mask procedure.

SECTION C  

Answer any TWO questions                                                                      2 x 20= 40

 

19 a)  Explain the procedure of obtaining the OC curve for a p-chart with an illustration.

  1. b) Explain process capability analysis with an illustration.        ( 12+8 )

20  a) What are acceptance and rejection lines of a sequential sampling plan for

attributes?. How are the OC and ASN values obtained for this plan

b). A control chart for non-conformities per unit uses 0.95 and 0.05 probability limits.

The center line is at u = 2.4.Determine the control limits if the sample size n =15

(10+10)

21  a) Write a detailed note on the moving average control chart.

  1. b) What are modified control charts?. Explain the method of obtaining control limits

for modified control charts.                                                                              (8+12)

22 a) Explain with an illustration the method of obtaining the probability of acceptance

for a double sampling plan.

  1. b) What are continuous sampling plans and mention a few situations where these plans

are applied.                                                                                                         (12+8)

 

 

 

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Loyola College M.Sc. Statistics April 2007 Estimation Theory Question Paper PDF Download

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     LOYOLA COLLEGE (AUTONOMOUS), CHENNAI – 600 034

M.Sc. DEGREE EXAMINATION – STATISTICS

AC 32

SECOND SEMESTER – APRIL 2007

ST 2808/2806/2801 – ESTIMATION THEORY

 

 

 

Date & Time: 17/04/2007 / 1:00 – 4:00 Dept. No.                                              Max. : 100 Marks

 

 

SECTION – A

Answer all the questions                                                                                   (10 x 2 = 20)

 

  1. Explain the problem of Point estimation.
  2. Give two examples of loss function for simultaneous estimation.
  3. If δ is a UMVUE, then show that δ + 2 is also a UMVUE.
  4. Define Fisher information in the multi-parameter case.
  5. Define minimal sufficient statistic.
  6. Give an example of a family of distributions which is not complete.
  7. Give two examples of scale equivariant estimator.
  8. Let X follow B(1, θ), θ = 0.1,0.2. Find MLE of θ .
  9. Given a random sample from DU{1,2,…, N}, N ε I+, find a consistent estimator of N.
  10. Explain Bayes estimation.

 

SECTION – B

‌‌‌Answer any  five questions                                                                                (5 x 8 = 40)

 

  1. If δ0 is an unbiased estimator of g, show that the class of unbiased estimators of g is

{ δ0 + u‌‌ │‌‌u ε U0}.

  1. Given a random sample from N(μ, σ2), μ ε R , σ > 0, find Cramer-Rao lower bound for

estimating  σ/ μ.

  1. State and establish Bhattacharya inequality.
  2. Let X1,X2,…,Xn be a random sample from U(θ – 1, θ + 1), θ ε R. Show that

(X(1), X(n)) is minimal sufficient but not complete.

  1. State and establish Basu’s theorem.
  2. Given a random sample from E(ξ,1), ξ ε R, find MREE of ξ with respect to i) squared error loss and
  3. ii) absolute error loss.
  4. State and prove the theorem providing MREE of a scale parameter.
  5. Given a random sample from U(0, θ), θ ε R, show that MLE is not CAN. Suggest a CAN estimator.

 

SECTION – C

Answer any two questions                                                                               (2 x 20 = 40)

 

19 a) State and establish Cramer-Rao inequality for the multiparameter case.

  1. b) Let X follow DU{1,2,…,N}, N = 3,4,… Find the UMVUE of g(N). Hence find the UMVUE of N.

20 a) Show that an estimator is QA – optimal if and only if it is D – optimal.

  1. b) Given a random sample from E(ξ, τ), ξ ε R, τ > 0, find UMRUE of (ξ , ξ + τ) with

respect to any loss function, convex in the second argument.

 

21 a) Discuss the problem of equivariant estimation of the percentiles of a location – scale model.

  1. b) Given a random sample of size n from N(μ, τ2), μ ε R, τ > 0, find MREE of (μ+3τ) with respect to

standardized squared error loss.

22 a) State and establish invariance property of CAN estimator.

  1. b) Let (Xi,Yi) , i= 1,2,…,n be a random sample from a bivariate distribution with pdf

 

 

Find MLE of

 

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Loyola College M.Sc. Statistics April 2007 Econometrics Question Paper PDF Download

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LOYOLA COLLEGE (AUTONOMOUS), CHENNAI – 600 034

AC 47

M.Sc. DEGREE EXAMINATION – STATISTICS

SECOND SEMESTER – APRIL 2007

ST 2950/3950 – ECONOMETRICS

 

 

 

Date & Time: 28/04/2007 / 1:00 – 4:00      Dept. No.                                       Max. : 100 Marks

 

 

 

Section A

Answer all questions.                                                                        (10*2=20)

  1. What is the difference between a linear and non-linear model?
  2. Give any two reasons for the inclusion of the ‘disturbance term’ in an econometric model.
  3. Interpret the following statement:

Pr{-0.25 < β2 < 1.3} = 0.95.

  1. Show that in a simple linear model the mean of the observed and estimated Y values are equal.
  2. What is ‘cross – section ‘data? Give an example.
  3. What is meant by ‘linear hypothesis’?
  4.  “In a linear model involving dummy variable, if there are ‘m’ categories for the dummy variable, use only ‘m-1’ independent variables”. Justify the above statement.
  5. Define the term ‘autocorrelation’.
  6. For a four variable regression model, the observed and estimated (under OLS) values of Y are given below:

Observed Y:   10         14        13        12        17

Estimated Y:  10         13        11        14        15

Calculate the standard error of the estimate.

  1. Mention any two consequences of multicollinearity.

 

Section B

Answer any five questions.                                                         (5*8=40)

 

  1. Mention the assumptions in the classical linear regression model.
  2. Suppose that a researcher is studying the relationship between gallons of milk consumed by a family per month (Y) and the price of milk each month (X in dollars per gallon). The sample consists of observations in 12 consecutive months. Analysis of the data reveals the following:

SY = 480;        SX=36;            Sxy=-440

Sx2 = 20;         = 528, where x and y are deviates of X and Y from their respective means.

For this sample, find the following:

  • Least squares intercept and slope
  • Standard error of regression.
  • Standard error of the slope.
  • Test the hypothesis that the slope coefficient is zero at 5% level.
  1. Calculate TSS, ESS, RSS and R2 for the following data assuming a linear model of Y on X.

Y:        12        10        14        13        16        14

X:        2          4          7          10        12        13

  1. Explain the concept of structural change with an example.
  2. What is meant by interval estimation? Derive a 100(1-α) % confidence interval for the slope parameter in a simple linear model.
  3. Explain the various methods of detecting multicollinearity.

 

 

 

  1. Consider the following OLS regression results with standard errors in

parenthesis:

S = 12,000 – 3000X1 + 8000(X1 + X2)

(1000)    (3000)                        n = 25

where S = annual salary of economists with B.A. or higher degree

X1 = 1 if M.A. is highest degree; 0 otherwise

X2 = 1 if Ph.D is highest degree; 0 otherwise

  • What is S for economists with a M.A. degree?
  • What is S for economists with a Ph.D degree?
  • What is the difference in S between M.A.’s and Ph.D’s?
  • At 5% level of significance, would you conclude that Ph.D’s earn more per year than M.A.’s?
  1. Explain the method of estimating the regression parameters in the presence of heteroscedasticity.

 

Section C

Answer any two questions.                                                   (2*20=40)

 

  1. a.) State and prove Gauss – Markov theorem.

b.) Show that for a ‘k’ variable regression model, the estimator

= (e1e)/(n-k) is unbiased for σ2.                                           (12+8).

  1. a.) Derive a test procedure for testing the linear hypothesis Rβ = r where R

is a known matrix of order q x k with q ≤ k and r is a known q x 1

vector.

b.) Explain the procedure for testing the equality of the slope coefficients of

two simple linear models using dummy variables.          (10+10)

  1. a.) Consider the following data on weekly income(Y), gender and status.

Y:        110      100      120      115      145      136      102      150

Gender:       1          1          0          1          0          0          1          0

Status:       0          0          1          1          1          0          1          0

where gender = 1 if male; 0 if female

Status = 1 if minor; 0 if major.

Assuming a linear model of Y on gender and status, estimate the

regression coefficients. Interpret the results.

b.) Define the following:

1.) Standard error of the estimate

2.) Ordinal data

3.) Variance Inflating Factor

4.) Coefficient of Determination.                                          (10+10)

  1. a.) For the following data, use Spearman’s rank correlation test to for the

presence of heteroscedasticity.

Y:        10        14        20        25        13        19        10        35

X:        1.3       2.1       2.5       3.0       1.7       1.9       1.0       2.9

b.) Explain the Breusch – Pagan – Godfrey test.                          (10+10).

 

 

 

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Loyola College M.Sc. Statistics April 2007 C++ For Statistical Applications Question Paper PDF Download

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LOYOLA COLLEGE (AUTONOMOUS), CHENNAI – 600 034

AC 38

M.Sc. DEGREE EXAMINATION – STATISTICS

SECOND SEMESTER – APRIL 2007

ST 2954 – C++ FOR STATISTICAL APPLICATIONS

 

 

 

Date & Time: 24/04/2007 / 1:00 – 4:00      Dept. No.                                       Max. : 100 Marks

 

 

 

Section A

Answer ALL the  questions                                                                                  (10×2=20)

 

  1. What is Non-Inline member function? Give an example
  2. Define type casting.
  3. Discuss the role of delete operator in memory management.

4  What is an exception? Write down the keywords used to handle exceptions in C++.

  1. What is Early-binding ?
  2. Explain the significance of new keyword.
  3. Mention the use of setw and endl manipulators.
  4. What is meant by data abstraction?
  5. What is the purpose of scope resolution operator?

Section B

Answer any FIVE questions                                                                                     (5X8=40)

  1. Explain the chief characteristics of Object Oriented Programming.

12.Discuss the advantage of overriding in Inheritance with an example.

13.. Explain constructor overloading  with an example.

  1. Write a program which overloads the binary operator plus(+) to add any two matrices.
  2. When do you make a class virtual? Give a suitable example.
  3. What is a friend function? What are the merits and demerits of using friend functions?
  4. Write a C++ program to compute the Co-efficient of Variation.
  5. What is meant by Containership? Explain with examples.

 

Section C

Answer any TWO questions                                                                                    (2×20=40)

 

19.[a] Define a class to represent a bank a/c, which include the data members: name, acc_number,

       acc_type and balance. Also, define the member  functions: i] to assign initial values  ii]

Deposit an amount  iii] Withdraw an amount after checking the minimum balance of Rs.1000/-

iv] Display  the name and balance. Write C++ program to test these member functions.

20    Write a program in C++ to perform analysis of variance in Randomized Block Design.

21.[a] Illustrate  with an example ‘passing and returning objects as arguments’ in functions .

[b] Explain the advantages of Polymorphism  by giving an example

  1. Explain different types of inheritance(simple, multiple and multi-level) by giving appropriate

illustrations of your own  choice.

 

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LOYOLA COLLEGE (AUTONOMOUS), CHENNAI – 600 034

AC 25

M.Sc. DEGREE EXAMINATION – STATISTICS

FIRST SEMESTER – APRIL 2007

ST 1810 / 1803 – ADVANCED DISTRIBUTION THEORY

 

 

 

Date & Time: 30/04/2007 / 1:00 – 4:00      Dept. No.                                       Max. : 100 Marks

 

 

SECTION – A                              Answer all the questions                             (10 x 2 = 20)

  1. Define truncated Poisson distribution and find its mean.
  2. Show that the minimum of two independent exponential random variables is exponential.
  3. Define bivariate Poisson distribution.
  4. If (X1,X 2) is bivariate binomial, find the pgf of X1+X 2.
  5. If (X1,X 2) is bivariate normal, find the distribution of 2X1 -3 X 2 .
  6. Find the marginal distributions associated with a bivariate exponential distribution of

Marshall – Olkin.

  1. Find the mean of non-central t – distribution.
  2. Let X (1) ,X(2 ),X (3) be order statistics from exponential distribution.Find E{X (3) – X(1)}.
  3. Let X 1 ,X2 ,X 3 be independent N(0,1) random variables. Examine whether

2X12 + X2 2 + 2X3 2 – X1X3 + 2X2X3  has a chi-square distribution.

  1. Let X 1 ,X2 be independent N(0,1) random variables. Find the MGF of 2X1X2.

 

SECTION – B                              Answer any five questions                            (5 x 8 = 40)

  1. State and establish the mgf of a Power series distribution.Deduce the mgf of Binomial.
  2. For an Inverse Gaussian distribution,derive the cumulants. Hence find the mean and variance.
  3. State and establish the additive property for bivariate Poisson distribution.
  4. Derive the conditional distributions associated with bivariate binomial distribution.
  5. Let X = (X1,X2)/ be such that every linear combination of X1and X2 is distributed as normal.

Show that X is bivariate normal.

  1. If X = (X1,X 2)/ is bivariate exponential(l1, l2, l3), show that X1 and X 2 are independent if and only

if  l3 = 0.

  1. Define non – central chi-square distribution and derive its probability density function.
  2. If X1, X2,X3,X4 are independent N(0 ,1) variables, examine whether X1+ 2X2 -X3 +3X4 is

independent of  (X1– X2)2 + (X3 -X4)2 + (X1 – X­3)2.

 

 

SECTION – C                              Answer any two questions                           (2 x 20 = 40)

19 a) State and establish a characterization of geometric distribution.

  1. b) Let X1, X2, …,Xn denote a random sample from lognormal distribution. Show that

the sample geometric mean is lognormal.

20 a) Define trinomial distribution. State and establish its additive property.

  1. b) If (X1,X 2)/ is bivariate normal with correlation coefficient r , show that the correlation coefficient

between X12 and X22 is r2.

21 a) Define non-central F distribution and derive its pdf .

  1. b) Discuss any two applications of non-central F distribution.

22 a) Let X1, X2, …,Xn be independent N(0,1) variables.State and establish a necessary and sufficient

condition for  X/AX to be distributed as chi-square,where  X =(X1,X2,…,Xn)/ .

  1. b) Explain compound distribution with an illustration

 

 

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LOYOLA COLLEGE (AUTONOMOUS), CHENNAI – 600 034

M.Sc. DEGREE EXAMINATION – STATISTICS

AC 54

FOURTH SEMESTER – APRIL 2007

ST 4807 – ADVANCED OPERATIONS RESEARCH

 

 

 

Date & Time: 20/04/2007 / 9:00 – 12:00          Dept. No.                                                          Max. : 100 Marks

 

 

SECTION A

(10 X 2 = 20)

 

ANSWER ALL QUESTIONS. EACH CARRIES TWO MARKS

 

  1. What is a pure integer programming problem?
  2. Write down the formula for mixed cut.
  3. What is the basic principle used in Dynamic Programming?
  4. What do you mean by problem of dimensionality?
  5. When do you use e-model in stochastic programming ?
  6. What are soft and hard constraints?
  7. List the assumptions made in single item static model.
  8. Mention how the objective function is expressed at the beginning of each iteration in Beal’s method.
  9. Give two examples for setup cost.
  10. What will be your conclusion when the value of the objective function at the end of Phase 1 is non zero in two-phase simplex method?

 

SECTION B

(5 X 8 = 40)

 

ANSWER ANY FIVE. EACH CARRIES EIGHT MARKS

 

  1. Show that the following problem has two optimum solutions :

Maximize : subject to

 

 

 

  1. Describe in detail “Fractional Algortithm”
  2. Describe with an example of your choice Branch and Bound Method
  3. Explain the method of solving  LPP using dynamic programming technique.
  4. Explain how constrained non-linear programs are solved.
  5. Describe the steps used in Beale’s Method
  6. Solve the following inventory problem (Multi item static model with storage constraint).

 

 

1        10        2          0.3       1 sq. ft

2        5          4          0.1       1 sq. ft

3        15        4          0.2       1 sq. ft

 

Assume that = 25 sq. ft

 

 

  1. Explain various elements of a queuing model.

 

 

SECTION C

(2 X 20 = 40)

 

ANSWER ANY TWO. EACH CARRIES TWENTY MARKS

 

 

  1. Explain Capital Budgeting Model. Develop DP solution for the same and illustrate the solution for the following data :

 

Plant 1             Plant 2             Plant 3

 

Proposal          c1        R1       c2        R2       c3        R3

 

1                3          5          3          4          0          0

 

2                4          6          4          5          2          3

 

3                —          —          5          8          3          5

 

4                —          —          —          —          6          9

 

 

  1. Solve the following problem by Wolf’s method.

Minimize

Subject to

,

  1. Kumaravel has Rs.80000/- with him. He wants to buy shares of Lavanya & Co and Sathish & Co. The following table gives the necessary data.

 

Share Price      Annual Return                        Risk Index

 

Lavanya & Co             Rs.25/-             Rs.3/-               0.50

 

Sathish & Co               Rs.50/-             Rs.5/-               0.25

Kumaravel wants to have a minimum return of Rs.9000/- and does not like to lose

more than Rs.700/- . Formulate this as a goal programming problem and solve the

same.

 

  1. In the deterministic model with instantaneous stock replenishment, no shortage, and constant demand rate, suppose that the holding cost per unit is given by for             quantities below q and for quantities above q, . Find the economic lot     size.

 

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AC 52

LOYOLA COLLEGE (AUTONOMOUS), CHENNAI – 600 034

M.Sc. DEGREE EXAMINATION – STATISTICS

FOURTH SEMESTER – APRIL 2007

ST 4805 – APPLIED EXPERIMENTAL DESIGN

 

 

 

Date & Time : 16.04.2007/9.00-12.00   Dept. No.                                                                     Max. 100 Marks

 

 

SECTION – A

Answer all the questions                                                          (10 x 2  = 20 marks)

 

  1. Give any two industrial applications of Experimental Designs.
  2. Obtain the relative efficiency of RBD over CRD.
  3. State the regression model for 22 factorial design.
  4. Define a simple Lattice design, with an example.
  5. Define the FINITE FIELD with an example.
  6. Briefly explain any one of the principles of experimental designs.
  7. What is meant by Whole-plot treatments?
  8. State the parametric conditions of a BIBD.
  9. Give any two advantages of Split-plot design.
  10. When do we go for RLSD ?

 

SECTION-B

 

Answer any Five questions                                                         (5 x 8  = 40 marks)

 

  1. Discuss Fixed, Mixed and Random effect models with suitable illustrations.
  2. Describe, the analysis of variance for a 25 factorial design, stating all the

hypothesis, ANOVA and conclusions

  1. Discuss half fractional factorial design with suitable illustration.
  2. Construct a Lattice Square Design using  nine treatments.
  3. Distinguish between RBD and BIBD with suitable illustration.
  4. Show that all the treatment contrasts are mutually orthogonal in the case of 23 factorial design.
  5. Describe briefly the method of Steepest accent?
  6. Explain the Analysis of Repeated Latin Square Design.

 

SECTION-C

 

Answer any Two questions                                                        (2 x 20  = 40 marks)

 

  1. a)Explain the term Complete Confounding with suitable illustration.

b)Describe in detail confounding in more than two blocks in which two independent and one generalized

interactions are confounded.                                                                                               (6+14-Marks)

 

 

  1. a) Distinguish between the Analysis of RBD and the analysis of RBD when one observation is missing.
  2. b) Derive the missing formula when two observations are missing in the case of RBD.

(10+10-Marks)

  1. a) When do we go for BIBD? Construct a BIBD when the number of treatment v = 5.
  2. b) Develop the analysis of variance for a BIBD, stating all the  hypothesis, ANOVA and conclusions.

(3+5+12-Marks)

22 Write shorts on the following

  1. MOLS
  2. Galois Field
  3. Biological applications of experimental designs
  4. Homogenous Equations                                                                   (5+5+5+5-Marks)

 

 

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LOYOLA COLLEGE (AUTONOMOUS), CHENNAI – 600 034

AC 28

M.Sc. DEGREE EXAMINATION – STATISTICS

FIRST SEMESTER – APRIL 2007

ST 1811  – APPLIED REGRESSION ANALYSIS

 

 

 

Date & Time: 02/05/2007 / 1:00 – 4:00      Dept. No.                                                  Max. : 100 Marks

 

 

Answer ALL the questions                                          SECTION – A                                                    (10 x 2 = 20 marks)

  1. Explain the term ‘partial regression coefficients’.
  2. State an unbiased estimate of the error variance in a multiple linear regression model.
  3. Define ‘PRESS Residuals’.
  4. What is the variance stabilizing transformation used when σ2 is proportional to E(Y)?
  5. Give the expression for the GLS estimator explaining the notations.
  6. Mention any two sources of multicollinearity.
  7. Define ‘Variance Inflation Factor’ of a regression coefficient.
  8. Define a ‘Hierarchical Polynomial Model’.
  9. What is ‘Link function’ in a GLM?
  10. Give the interpretation for a positive coefficient in a logit model.

 

Answer any  FIVE questions:                                      SECTION – B                                                (5 x 8 = 40 marks)

 

  1. Briefly explain the limitations to be recognized and cautions that are needed in applying regression models in practice.

 

  1. A model (with an intercept) relating a response variable to four regressors is to be built based on the following sample of size 10:
Y X1 X2 X3 X4
23.5

15.7

22.8

18.9

17.3

28.4

16.6

23.1

20.0

19.8

 2

3

7

1

5

8

3

7

3

4

 12

22

18

14

20

25

24

17

13

24

 38

33

27

29

34

40

32

37

28

30

 7

18

9

14

11

16

10

8

13

15

Write down the full data matrix. Also, if we wish to test the linear hypothesis  H0: β2 = 2β3, β1 = 0, write down the reduced model under the H0 and also the reduced data matrix.

 

  1. Explain the motivation and give the expressions for ‘studentized’ and ‘externally studentized’ residuals.

 

  1. The following residuals were obtained after a linear regression model was built:  -0.15, 0.03. -0.06, 0.01, 0.23, -0.31, 0.19,  0.15, -0.08, -0.01

Plot the ‘normal probability plot’ on a graph sheet and draw appropriate conclusions.

  1. An investigator has the following data:

Y:   3.2     5.1     4.5     2.4

X:    5        9         6        4

Guide the investigator as to whether the model Y = β0 + β1X or Y1/2 = β0 + β1X is  more appropriate.

 

  1. Discuss the need for ‘Generalized Least Squares’ pointing out the requirements for it. Briefly indicate the ANOVA for a model built using GLS.

 

  1. The following is part of the output obtained while investigating the presence of multicollinearity in the data used for building a linear model. Fill up the missing entries and identify which regressors are involved in collinear relationship(s), if any.
Eigen

Value

(of X’X)

 Singular

value

(of X)

 Condition

Indices

 Variance Decomposition Proportions

X1        X2             X3           X4           X5           X6
2.525 ? ? 0.0180    0.0355      0.0004     0.0005        ?         0.0350
1.783 ? ? 0.0029    0.1590      0.0305      0.0987   0.0032        ?
1.380 ? ? 0.0168    0.0006          ?           0.0500   0.0006    0.0018
0.952 ? ? 0.6830         ?          0.0001      0.0033   0.1004    0.4845
0.245 ? ?      ?        0.1785      0.0025      0.0231   0.7175    0.4199
0.002 ? ? 0.2040    0.2642      0.9664          ?       0.0172    0.0029

 

 

  1. Discuss ‘Spline’ fitting.

 

Answer any TWO Questions                         SECTION – C                                                           (2 x 20 = 40 marks)

 

  1. (a)Obtain the decomposition of the total variation in the data under a multiple

linear regression model. Hence, define SST, SSR and SSRes and indicate the

ANOVA.

(b)Develop the Partial F-Test for the contribution of some ‘r’ of the ‘k’ regressors

in a multiple regression model.                                                               (10 + 10)

 

  1. A model with an intercept is to be built with the monthly mobile phone bill amount (Average over the past six months) of students (Y) as the DV and IDVs as: monthly income of parents (X1), age of the student (X2), number of telephone numbers saved in the mobile (X3) and also dummy variables indicating gender (male / female), class (UG /PG / M/Phil.), residence (day scholar / hostel inmate). The following data collected from 15 students are available:

 

Bill Amt.

(in Rs.)

 Income

(in ‘000 Rs.)

 Age # of Saved

numbers

 Gender Class Residence
230

150

300

225

400

180

125

170

200

350

280

375

450

390

195

 25

12

35

40

45

20

15

18

12

15

21

35

42

37

18

 17

22

21

18

21

24

19

18

20

25

19

23

22

26

17

 50

38

62

43

45

33

27

36

22

35

39

50

47

43

25

 F

F

M

M

M

F

F

M

F

M

F

F

M

M

M

 UG

PG

PG

UG

UG

M.Phil

UG

UG

PG

M.Phil.

UG

PG

PG

M.Phil.

UG

 Day scholar

Hostel inmate

Day scholar

Hostel inmate

Hostel inmate

Hostel inmate

Day scholar

Day scholar

Hostel inmate

Day scholar

Hostel inmate

Day Scholar

Hostel inmate

Hostel inmate

Day Scholar

 

(a) Construct the data matrix for building the model.

 

 

(b) If interaction effects of ‘Class’ with ‘parental income’ and interaction effect of ‘Gender’ with

‘Residence type’ are also to be incorporated in the model, write down the appropriate data matrix.

[You need not build the models].                                                          (10 +10)

 

  1. Build a linear model for a DV with a maximum of four regressors using the Forward Selection method based on a sample of size 25, given the following information:

SST = 2800, SSRes(X1) = 1500, SSRes(X2)  = 1650, SSRes(X3) = 1800,

SSRes(X4) = 1200, SSRes(X1,X2) = 1150, SSRes(X1,X3) = 1380,

SSRes(X1,X4) = 1050, SSRes(X2,X3) = 1300, SSRes(X2,X4) = 1020,

SSRes(X3,X4) = 990, SSRes(X1, X2, X3) = 1000, SSRes(X1, X2, X4) = 900,

SSRes(X1,X3, X4) = 850, SSRes(X2,X3,X4) = 750, SSRes(X1,X2,X3, X4) = 720.

 

  1. (a)Discuss ‘sensitivity’, ‘specificity’ and ‘ROC’ of a logistic regression model

and the objective behind these measures.

(b) The following data were used to build a logistic model and the estimates were

β0 = 3.8, β1 = –5.2, β2 = 2.2

DV 1 1 0 1 0 0 1 0 1 0 0 0 1 1 0 1 1 1 1 0
X1 -3 1 0 2 -2 4 1 -1 5 2 3 -2 0 -4 1 2 -1 -2 -3 4
X2 0 2 -3 2 -4 -1 0 3 2 -3 4 -5 1 -1 -4 3 4 -3 1 1

 

Compute the logit score for each record. Construct the Gains Table and

compute the KS statistic.                                                                            (8 + 12)

 

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LOYOLA COLLEGE (AUTONOMOUS), CHENNAI – 600 034

AC 37

M.Sc. DEGREE EXAMINATION – STATISTICS

SECOND SEMESTER – APRIL 2007

ST 2953 – ACTUARIAL STATISTICS

 

 

 

Date & Time: 24/04/2007 / 1:00 – 4:00      Dept. No.                                       Max. : 100 Marks

 

 

 

PART-A

 

Answer all the questions                                 (10×2=20)

  1. Define immediate annuity certain and annuity certain due.
  2. A has invested Rs1000 in NSC. After 15 years he is entitled to get Rs1750.What rate

of interest is realized in the transaction.

  1. Given Sn how will you find an ?

Given an how will you find Sn ?

  1. Find the nominal rate per annum convertible quarterly corresponding to an effective rate of 9%.
  2. Define e
  3. Given a complete table of ax:n how will you find Ax:n..
  4. Expand Rx in terms of Cx.
  5. Explain double endowment assurance.
  6. A pays Rs500 at the end of every year for 10 years @ 8% per annum.What is the value of all these payments at the end of 6 years?
  7. Distinguish between a perpetual annuity and a life annuity.

 

PART-B

 

Answer any 5 questions:                                            (5x 8 = 40)

 

  1. A loan of 5000 is to be repaid by payments of Rs2500 at the end of 1 year ,Rs1500

at the end of 2 years  and the balance at the end of 4½ years. What should the final

payment be if interest is reckoned at 9% per annum convertible half-yearly?

  1. PF deductions are made monthly at a rate of Rs2000 per month and credited to PF

account. Find the accumulated value at the end of 10 years @ 10% pa.

  1. Derive the formula for increasing annuity when the successive installments form an

Arithmetic progression.

  1. Three persons are aged 30,35,40 respectively find the probability that

i)one of them dies before 45 while the others survive to 55.

ii)atleast one of them attains 65.

  1. Calculate office annual premium for an endowment assurance for Rs15,000 to a

person aged 30 for 25years.provide for first year expenses at 50% of premiums and 15% sum assured; and renewal expenses of 5% of premiums and 6% sum assured.

  1. Calculate the net annual premium under a children referred endowment assurance for

Rs25,000 on the life of a child aged 5 , the assurance being vested at the age 21 and maturing at age 55 .Calculate also the additional premium for the benefit  of  waiver  of premiums payable during the deferment period in the event of death of the childs father aged 39 at 6% interest.

 

 

 

 

 

  1. A deposits annually Rs200 per annum for 10 years, the first deposit being made one year from now, and after 10 years the annual deposit is enhanced to Rs.300 per annum.  Immediately after depositing the 15th payment he closes his account, What is the  amount payable to him if interest is allowed at 9% pa?
  2. Derive the formulae for

ax:n  and a x:n

and decreasing temporary assurance.                                           (2+2+4)

 

PART-C

       Answer any two questions                                                       2×20=40

 

19.a).Aloan of Rs.7500 is to be repaid with interest at 8% per annum by means of level annual

payments, the first one being made at the end of first year . Find the principal

payments contained in the 10th payment.Immediately after the 10th payment  is

made the lender desires to have the balance repaid in 3 level annual payments

including  principal and interest; to which the borrower agreed provided a rate of

7% per annum is used for this agreement.Find the revised level payment.                       (15)

  1. b) Under settlement of property A will recieveRs1800 per annum ad infinitum the first

payment being receivable at the end of 6 years from now .Find the present value of

A’s rights at 9% pa.                                                                                                             (5)

20.a) A special policy provides for the following benefits:

i)an initial sum of Rs10,000/- with guranteed annual additions of Rs250 for

each years premium paid after the first,if death occurs within the term of

assurance.

ii)Rs 10,000 payable on survivance to the end of the term of assurance.

iii)Free paid-up assurance of Rs10,000/- payable at death after expiry of the

term of assurance

Calculate net annual premium under the policy on the life of (35) for 25 years (12)

  1. Calculate the net annual premium limited to 15 years for a temporary assurance on

(40) providing the following benefits.

i)Rs5000 on death during the first 5 years.

ii)Rs10,000 on death during the next 5 years.

iii)Rs15,000 on death during the last 10 years.

  1. Explain the stages in the construction of life table in detail.
  2. a)Derive the formula for

an, Sn 

            b)Payments of i)Rs50 at the end of each half year for the first 5years followed by

ii)Rs50 at the end of each quarter for the next 5 years are made into

an account to which interest is credited  at the rate of 9% per annum

convertible half yearly. Find the present value and accumulated

value at the end of 10 years.

c)A sum of Rs150 is deposited in a bank at the beginning of each year.What is the

amount to the credit of the depositor at the end of 20 years if inerest is credited

to the account at  6% for the first 10 years

7% for the next 5 years and

8% thereafter ?

(6+7+7)

 

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LOYOLA COLLEGE (AUTONOMOUS), CHENNAI – 600 034

HP 06

M.Sc. DEGREE EXAMINATION – MEDICAL LAB. TECH.

THIRD SEMESTER – APRIL 2007

ML 3875 – PHARMACEUTICAL CHEMISTRY AND TOXICOLOGY

 

 

 

Date & Time: 03/05/2007 / 9:00 – 12:00      Dept. No.                                       Max. : 100 Marks

 

 

PART A

 

Answer all the questions                                                         (2×10=20 Marks)

 

  1. Mention any two functions in the action of drugs.
  2. What are isotopes? Give the different isotopes of hydrogen.
  3. Give the name and structure of any two sweetening agent used in drugs.

4.What is ‘Biosterism’? Explain with an example.

  1. What is meant by ‘Chelation’? Mention any two important aspects of chelation in

medicine.

  1. What are the four basic types of damage caused by toxic materials?
  2. Define Fetal Alcohol Syndrome.
  3. What is Genetic Toxicity?
  4. What is meant by first pass biotransformation?
  5. List the advantages of scintillation counter over GM counter.

 

 

PART B

 

Answer any four of the following:                                                            (10×4=40 Marks)

 

  1. Explain the role of chemical structure in pharmacological activity taking any two

functional groups.

  1. What is ‘Metabolite antagonism’? Explain with two examples.
  2. How is radioactivity measured using Geiger- Muller counter and Scintillation

counter?

  1. How are teratogens classified? Which is the most sensitive period for teratogens in

pregnancy.

  1. Discuss the physiological barriers in drug distribution.
  2. List the different immunoassay techniques. Explain RIA.

 

PART  C

 

Answer any two of the following:                                                              (20×2=20 Marks)

 

  1. Explin the different types of pharmaceutical aids used in drugs.
  2. (a). Discuss the importance of biological testing of drugs.

(b). Explain briefly the role of solubility, partition coefficient and steric factors in

designing drugs.

19.Write in detail absorption, distribution and excretion of toxic substances.

20.Describe in detail the different routes of elimination of drugs from the body.

 

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LOYOLA COLLEGE (AUTONOMOUS), CHENNAI – 600 034

HP 04

M.Sc. DEGREE EXAMINATION – MEDICAL LAB. TECH.

THIRD SEMESTER – APRIL 2007

ML 3902 – PATHOGENS OF HUMAN IMPORTANCE

 

 

 

Date & Time: 28/04/2007 / 9:00 – 12:00      Dept. No.                                        Max. : 100 Marks

 

 

Section –A

Answer all the questions                                                          2X10=20marks

  1. Distinguish bacteremia from septicemia
  2. Mention the most frequent types of hospital-acquired infections.
  3. Expand the abbreviations of the following.

MMR, HSV, DPT, CFT.

  1. Draw the structure of Streptococcus pyogenes and add a note on morphology.
  2. List any four diseases caused by Rickettsial species.
  3. Distinguish encystation from excystation.
  4. List any four clinical features of Wuchereria bancrofti.
  5. Mention the enzymes and their activity in Streptococcus pyogenes.
  6. Distinguish virulence and invasiveness.
  7. What are the clinical features of poliovirus?

Section-B

Answer any four of the following                                           4X10=40marks

 

  1. Explain the pathogenesis and clinical conditions of Shigella dysenteriae.
  2. What are the physical methods of sterilization? Explain filtration techniques in detail.
  3. Describe in detail the measures to prevent hospital-acquired infections.
  4. Discuss the clinical features of H.influenzae
  5. Draw and explain the life cycle of Taenia solium.
  6. Explain the spread of community-acquired infections.

Section-C

Answer any two of the following                                           2X20=40marks.

 

  1. Describe the life cycle of malarial parasite with suitable diagrams.
  2. Describe in detail the pathogenesis and clinical features of AIDS.
  3. Explain in detail the streptococcal infection.
  4. Write a detailed account on the control and prevention of hospital-acquired infections.

 

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Loyola College M.Sc. Medical Lab Technology April 2007 Non Invasive Techniques Question Paper PDF Download

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HP 02

LOYOLA COLLEGE (AUTONOMOUS), CHENNAI – 600 034

M.Sc. DEGREE EXAMINATION – MEDICAL LAB TECHNOLOGY

FOURTH SEMESTER – APRIL 2007

ML 4801 – NON INVASIVE TECHNIQUES

 

 

 

Date & Time : 16.04.2007/9.00-12.00   Dept. No.                                                                    Max. 100 Marks

 

 

Section-A

Answer all the questions                                                          10X2=20 marks

  1. What is the significance of breast compression in mammography?
  2. What is epilepsy? Differentiate gradmal from petimal epilepsy.
  3. What is the purpose of opthalmoscopy?
  4. Mention the three factors that are responsible for image quality in MRI.
  5. Distinguish conventional and Helical Computed Tomography.
  6. Mention the types of brain waves and the frequencies that are observed in EEG.
  7. What are the equipments that are used in fluorescein angiography.
  8. Expand: CRVO, OPPG, BRVO, WPW
  9. What are the four densities that can be observed on an X-ray?
  10. Distinguish radiopharmaceuticals from radionucleides.

 

Section-B

Answer any four of the following                                        4X10=40 marks

  1. Describe the principle and abnormal findings of mammography.
  2. Explain the equipment and the techniques that are used in fluorescein angiography.
  3. Write short notes on abnormal interpretations of Electrocardiography.
  4. Explain the patient preparation and procedure of OPG and OPPG.
  5. Explain the types of indirect ophthalmoscopy.
  6. Give an account on the types of biomedical signals.

 

Section –C

Answer any two of the following                                         2X20=40 marks.

  1. Explain in detail Positron emission tomography.
  2. Describe the principle, procedure and abnormal findings of ultrasonography.
  3. Describe the working mechanism, procedure and limitations of Magnetic resonance

imaging.

  1. Explain the principle and procedure of Electromyography and visual acuity test.

 

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