Internal examination 3rd semester disaster Msc. Public Health and Disaster Engineering, School of Engineering, Pokhara University

5. POKHARA UNIVERSITY
First Assessment- 2020
Level: Master Full Marks: 100
Program: Msc. Public Health and Disaster Engineering Pass Marks: 60
Course: Probability and statistical analysis Time: 4 hrs
Attempt all questions.
1.a) The incubation periods of a random sample of 7 HIV infected individuals is given below (in years):
12.0 10.5 9.5 6.3 13.5 12.5 7.2
Calculate the sample mean and coefficient of variation of the given series. Suppose instead of 7 individuals,
we had 12 individuals. (We added 5 more randomly selected observations to the original 7) as follows.
12.0 10.5 9.5 6.3 13.5 12.5 7.2 14.9 6.5 8.1 7.9 10.7
Make an educated guess of whether the sample mean and coefficient variation for the 12 observations would
increase, decrease, or remain roughly the same compared to your answer in first based on only 7 observations.
Now actually calculate the sample mean and coefficient of variation to see if you were right. How does your
calculation compare to your educated guess? Why do you think this is? 8
b) The table given below represents the weekly salary of 130 engineers who worked in a certain company. Find
the range of the middle 60% of the workers. 7
Salary in $ >
7
0
>8
5
>1
00
>11
5
>130 >14
5
>1
60
>1
75
c.f. 130 12
2
10
9
79 44 26 14 5
2.a) The probability that a person selected at random from a population will exhibit the classic symptom of
certain disease is 0.2, and the probability that a person selected at random has the disease is 0.23. The probability
that a person who has the symptom also has the disease is 0.18. A person selected at random from the population
does not have the symptom: what is the probability that the person has the disease? 7
b) State Baye’s theorem. In a factory machine X produces 30% of items, machine Y produces 25% and rest
produces by Z per day. 1% of the item produced by machine X is defective, while machine Y and Z produce
defective 3% and 2% respectively. An item drawn at random from day’s items is non defective what is the
probability that it was produced by machine X? 8
3.a) State the conditions to apply for binomial and Poisson distribution. Suppose the ages at time of onset of
certain disease are approximately normally distributed with mean of 11.5 years and standard deviation of 3
years. A child has just come down with the disease. Find the probability that the child is i) over 10 years of age
ii) between 8 to 14 years of age iii) There are 500 children at the time of onset of disease, how many of the
children are under 12 years of age? 8
b) Explain the characteristics of normal curve. In the study of certain aquatic organism, a large number of
samples were taken from a pond, and the number of organisms in each sample was counted. The average number
of organisms per sample was found to be two. Assuming that the number of organisms follows a Poisson
distribution, find the probability that the next sample will contain one or fewer organisms. 7
4.a) How would you minimize the errors that arise in the statistical hypothesis testing? Two different types of
drugs A and B were administered on certain patients for increasing weight. The weight gain in gm by different
patients due to drug A and B was as follows.
Drug A: 8 12 13 9 3 4 10 9
Drug B: 10 8 12 15 6 11 13 12
Would you conclude that both drugs are equally responsible for increase in weight? Use  =0.05. 7
b) The six treatments 1T , 2T , 3T , 4T , 5T and 6T are applied in randomized block design of experiments
resulted the weight gain in grams by patients in different blocks are as:

6. Block 1: 24.7 ( 1T ) 27.7( 2T ) 20.6 ( 3T ) 16.2 ( 4T ) 16.4 ( 5T ) 24.9 ( 6T )
Block 2: 22.7 ( 3T ) 28.8 ( 2T ) 27.3 ( 1T ) 15.0 ( 4T ) 22.5 ( 6T ) 17.0 ( 5T )
Block 3: 26.2 ( 6T ) 19.6 ( 4T ) 38.5 ( 1T ) 36.6 ( 3T ) 39.5 ( 2T ) 15.4 ( 5T )
Block 4: 17.7 ( 5T ) 31.0 ( 2T ) 28.5 ( 1T ) 14.1 ( 4T ) 34.9 ( 3T ) 22.6 ( 6T )
Carry out the ANOVA and test whether the treatments differ significantly at 5% level of significance. 8
5. a) Suppose you are going to do research entitled “Impact of Climate Change on Agriculture Production in
Khudi” Total number of households in Khudi is 1550. You have no time to collect information from all these
households. What will be the appropriate sample size for information collection in Khudi (at 5% margin of error
and 5% level of significance) for this research? How can you apply systematic sampling techniques to collect
the samples from 1550 households if the list of households in Khudi is not available? (7 marks)
b) From a population of 1000 employees of a factory a sample of 50 employees is selected at random. From
this sample, the mean income is found to be Rs. 6000 and standard deviation of income Rs. 500. (8 marks)
i) Find standard error of mean income of all the workers.
ii) Construct 95% confidence interval for mean income of all the workers.
6.a) Explain about Karl Pearson’s correlation coefficient. The profits earned (in thousands) and the working
capitals (in thousands) of eight industries in a state are given below. (5 marks)
X: 75 88 95 70 80 81 50
Y: 120 34 150 115 140 142 100
Use the method of rank correlation to find the relationship between profits and working capital.
b) Why do we need to perform linear regression analysis? Explain briefly with example. The information given
below has been gathered from a random sample of apartment renters in a city. We are trying to predict rent in
rupees per month based on the size of the apartment (number of rooms) and the distance from downtown (in
Km).
Rent Rs. 360 1000 450 350 315
No. of
rooms:
2 6 3 2 1
Distance
(km)
1 2 3 10 4
Calculate the multiple linear regression equation to predict rent. If someone is looking for a 5-bed room
apartment two kilometers from downtown, what rent should be expected to pay? (10 marks)
7) List out the different techniques of sampling. Why is probability sampling technique
better than non-probability sampling? Explain briefly about respondent driven sampling
method. (10 marks)

7. POKHARA UNIVERSITY
First Assessment- 2020
Level: Master Full Marks: 100
Program: Msc. Public Health and Disaster Engineering Pass Marks: 60
Course: Automated System Designed for Emergencies Time: 4 hrs
• Candidates are required to give their answers in their own word.
• Attempt all questions
1. What is smart technology? Explain its key benefits with examples. [7]
2. What is sensor? Explain types of sensors with examples. [8]
3. Point out the difference between integrated sensor and smart sensor with block
diagram? List out the potential advantage of the smart sensor concept. [8]
4. What is system architecture of smart technology? Explain both module level and system
level in detail. [8]
5. What is early warning system? Explain its importance in disaster management with any
two examples. [8]
6. Point out the difference between sensor and transducers. Explain different modes of
instrumentation. [7]
7. What are different types of transducer. Explain the electrical transducer in detail. [7]
8. What is data acquisition system? Explain its different components with block diagram.
[8]
9. Define signal conditioning and its importance in instrumentation system. Explain the
block diagram of signal conditioning. [7]
10. What is telecommunication? Draw the basic component with block diagram and explain.
[7]
11. Explain different type of transmission media with appropriate figure. [8]
12. What is networking? Explain its importance in disaster management with an example
used in Nepal. [7]
13. Short Notes [2*5]:
▪ Internet of things
▪ Importance of smart technology in Public health and disaster engineering
▪ Concept of smart city
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