The following table represents the sales (in thousands) of mobile sets of a shop for 16 quarters over four years:
| Year | Quarter | |||
|---|---|---|---|---|
| Q_1 | Q_2 | Q_3 | Q_4 | |
| 2011 | 554 | 590 | 616 | 653 |
| 2012 | 472 | 501 | 521 | 552 |
| 2013 | 501 | 531 | 553 | 595 |
| 2014 | 403 | 448 | 460 | 480 |
(a) Compute the seasonal indices for four quarters by Simple average method.
(b) Obtain deseasonlised values.
We are asked to compute seasonal indices using the simple average method and then deseasonalize the data. Let’s solve this step by step manually. --- ### Step 1: Compute annual totals and quarterly averages First, sum sales for each year: * 2011: 554 + 590 + 616 + 653 = 2413 * 2012: 472 + 501 + 521 + 552 = 2046 * 2013: 501 + 531 + 553 + 595 = 2180 * 2014: 403 + 448 + 460 + 480 = 1791 __________ _________ ________ ________ _________ __________ ________ _____.
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The following table represents the sales (in thousands) of mobile sets of a shop for 16 quarters over four years:
| Year | Quarter | |||
|---|---|---|---|---|
| Q_1 | Q_2 | Q_3 | Q_4 | |
| 2011 | 554 | 590 | 616 | 653 |
| 2012 | 472 | 501 | 521 | 552 |
| 2013 | 501 | 531 | 553 | 595 |
| 2014 | 403 | 448 | 460 | 480 |
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.
| Sequence | A | B | C | D | E | |
|---|---|---|---|---|---|---|
| Job 1 | Time (in hours) | 1 | 2 | 3 | 5 | 4 |
| Job 2 | Sequence | C | A | D | E | B |
| Time (in hours) | 3 | 4 | 2 | 1 | 5 |
Use the penalty (Big M) method to solve the following LP problem:
Minimise
Subject to the constraints.
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:$
(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.
(c) Comment on the goodness of fit of the regression line.
In a railway marshalling yard, goods trains arrive at a rate of 36 trains per day. Assuming that the inter-arrival 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
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:$
$
Build a regression model by selecting appropriate regressors in the model using the Stepwise Selection method.
A company has three production facilities S1, S2 and S3 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 D1, D2, D3 and D4 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:
| $D_1$ | $D_2$ | $D_3$ | $D_4$ | Capacity | |
|---|---|---|---|---|---|
| $S_1$ | 19 | 30 | 50 | 10 | 7 |
| $S_2$ | 70 | 30 | 40 | 60 | 9 |
| $S_3$ | 40 | 8 | 70 | 20 | 18 |
| Demand | 5 | 8 | 7 | 14 | 34 |