IGNOU MSTE002 Solved Assignment 2022
 AUTHOR: Narendra Kr. Sharma
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IGNOU MSTE002 Solved Assignment 2022
MSTE002 Solved Assignment is an ebook for students who want to specialise in statistics. This completed assignment will allow them to assess their degree of preparation and will be extremely beneficial. All questions and concerns have been addressed and clarified. As a result, students will comprehend the concepts of any question in the assignment.
Assignment Paper 
IGNOU MSTE002 Solved Assignment 2022 
Subject Name 
Industrial StatisticsII 
No.of Pages in Solution 
38 
Course 
PGDAST 
Language 
ENGLISH 
Session 
2022 
Last Date for Submission of Assignment 
For June Examination 31st March 2022 or as per dates given in the Ignou website For December Examination 30th September 2022 or as per dates given in the Ignou website 
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IGNOU MSTE002 Sample Solution 2022
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IGNOU MSTE002 Solved Assignment 2022
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IGNOU MSTE002 Assignment Question Paper 2022
(Industrial StatisticsII)
Note: All questions are compulsory. Answer in your own words. 1.State whether the following statements are True or False. Give reasons in support of your answers. (a) The solution of a transportation problem with 5 rows (supplies) and 4 columns (destinations) is feasible if number of possible allocations are 8. (b) The moving averages of suitable period in a timeseries are free from the influences of seasonal and cyclic variations. (c) If the basic solutions for a system of equations are ( 2, 0, 1), (0, 1, 3), ( 2, 3, 0), then only (0, 1, 3) is feasible. (d) In the stepwise selection method of multiple regression model, once a variable enters in the model then it always remains in the model. (e) An enterprise requires 1000 units per month. The ordering cost is estimated to be 50 per order. The purchase price is 20 per unit and the carrying cost per unit is 10% of it. Then the economic lot size to be ordered is 775. 2. Use the penalty (Big M) method to solve the following LP problem: Minimise Z = 5x_{1}+ 3x_{2} Subject to the constraints 2x_{1}+ 4x_{2} ≤ 12 x_{l}, x_{2} ≥ 0. 3. A company has three production facilities S_{1} , S_{2} and S_{3} with production capacity of 7, 9 and 18 units (in 100s) per week of a product, respectively. These units are to be shipped to four warehouses D_{1}, D_{2}, D_{3} and D_{4} with requirement of 5, 6, 7 and 14 units (in 100s) per week, respectively. The transportation costs (in Rs) per unit between factories to warehouses are given in the table below:
Obtain optimal solution by the MODI method. 4. Four professors are capable of teaching any one of four different courses. Class preparation time in hours for different topics varies from professor to professor and is given in the table below:
Each professor is assigned only one course. Determine an assignment schedule so as to minimise the total course preparation time for all courses. 5. In a railway marshalling yard, goods trains arrive at a rate of 36 trains per day. Assuming that the interarrival and service time distributions both follow exponential distribution with an average of 30 minutes, calculate the following: (i) Traffic intensity (ii) The mean queue length (iii) Probability that the queue size exceeds 6. Using the graphical method to minimise the time required to process Job 1 and Job 2 on five machines A, B, C, D and E, find the minimum elapsed times an idle times to complete both jobs.
7. A firm wants to know whether there is any linear relationship between the sales (X) and its yearly revenue (Y). The records for 10 years were examined and the following results were obtained: \[ \sum _{n=1}^{10}\:X=265,\sum \:_{n=1}^{10}\:Y=27.73,SS_x=285.6,SS_y=6.978,SS_{xy}=57.456 \] (a) Fit a regression line taking Y as the dependent variable and X as the independent variable. (b) Test whether the sales have any effect on revenue at 5% level of significance. 8. A researcher is interested in developing a linear model for the electricity consumption of a household having an AC (1.5 ton) so that she can predict the electricity consumption. For this purpose, she selects 25 houses and records the electricity consumption (in kWh), size of house (in square feet) and AC hours for one month during summers. The results obtained are: \begin{array}{l} Build a regression model by selecting appropriate regressors in the model using the Stepwise Selection method. 9. The following table represents the sales (in thousands) of mobile sets of a shop for 16 quarters over four years:
(a) Compute the seasonal indices for four quarters by Simple average method. (b) Obtain deseasonlised values. 