Regression and correlation are both termed “causal” methods of forecasting. Explain how they are similar in this respect and also how they are different.
Operations Management
Q1. A company has asked YOU to evaluate the firm’s productivity by comparing this year’s performance with last year’s. The following data are available: ______________Last Year This Year OUTPUT 10 500 units 12 100 units
Labor Hours 12 000 13 200 Utilities 7 600 MU 8 250 MU Capital 83 000 MU 88 000 MU Has the company improved its PRODUCTIVITY during the past year?
Q2. A Turkish manufacturing company operating a subsidiary in TRNC shows the following results: TURKEY TRNC Sales (in units) 100.000 20.000 Labor (hours) 20.000 15.000 Raw materials (in MU) 20.000 2.000 Capital Equipment (hrs) 60.000 5.000 a. Calculate single factor productivity figures of labor and capital for the parent and subsidiary. Do the results seem misleading? b. Now compute multifactor labor and capital productivity figures. Are the results better? c. Finally, calculate raw material productivity figures. Explain why these figures might be greater in TRNC.
Q3. What do you see as the main problem with qualitative (judgmental) forecasts? Are they ever better than “objective” methods?
Q4. Regression and correlation are both termed “causal” methods of forecasting. Explain how they are similar in this respect and also how they are different.
Q5. What are the major decision areas in P/OM?
Q6. What is continuous improvement (CI)? What are the major tools for this philosophy?
Q7. How does productivity measurement differ between manufacturing and service operations?
Q8. List the types of quality costs.
Regression and correlation are both termed
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Regression and correlation are both termed
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Regression and correlation are both termed
