Slideshare uses cookies to improve functionality and performance, and to provide you with relevant advertising. If you continue browsing the site, you agree to the use of cookies on this website. See our User Agreement and Privacy Policy.

Slideshare uses cookies to improve functionality and performance, and to provide you with relevant advertising. If you continue browsing the site, you agree to the use of cookies on this website. See our Privacy Policy and User Agreement for details.

Successfully reported this slideshow.

Like this document? Why not share!

No Downloads

Total views

2,172

On SlideShare

0

From Embeds

0

Number of Embeds

6

Shares

0

Downloads

76

Comments

0

Likes

1

No embeds

No notes for slide

- 1. EX.NO:01 ANALYSIS DESCRIPTIVE MEASURES ONDATE:08.03.10 STUDENTS MARKSThe marks of 12 students in mathematics are as follows:Students 1 2 3 4 5 6 7 8 9 10 11 12Marks 45 67 78 98 100 72 91 34 94 61 82 92CALCULATE THE FOLLOWING:1.CENTRL TENDENCY MEAN MEDIAN MODE SUM2. DISPERSION STANDARD DEVIATION VARIANCE RANGE MINIMUM MAXIMUM S.E.MEAN3.DISTRIBUTION SKEWNESS KURTOSIS 1
- 2. AIM: To analysis the descriptive measures of students marks using SPSSALGORITHM:STEP1: Open SPSS software 13.0STEP2: Click and select „Data view‟STEP3: Type the marks of the students in the marks columnSTEP4: Click on <Analyze><Descriptive statistics><Frequencies>STEP5: Select the marks and click on the scrollbarSTEP6: Click on the “Statistics bar” and select all central tendency and dispersion, distribution boxes then click on continue and “okSTEP7: Solve the solution tables and Generate reports. 2
- 3. OUTPUT: 3
- 4. 4
- 5. RESULT: Thus, the descriptive measures like central tendency, dispersion anddistribution of student‟s marks are analyzed and output is verified using SPSS 13.0. 5
- 6. EX.NO:02 DIAGRAMMATIC ANALYSIS ONDATE:08.03.10 STUDENTS MARKSThe Quiz final marks are as follows:Name Suji Ravi Bini Devi Sumi Siji Vani Gayana Deepa Saji Suthi CibiMarks 45 67 78 98 100 72 91 34 94 61 82 92FIND THE FOLLOWING: 1. Frequencies 2. Bar graph 3. pichart 4. histogram 5. Create a title for the aboveAIM: To analysis students marks diagrammatically using SPSS 13.0ALGORITHM:STEP1: Open SPSS software 13.0STEP2: Click and select „Data view‟STEP3: Type the final marks of the students in the marks columnSTEP4: Click on <Analyze><Descriptive statistics><Frequencies>STEP5: Select the marks and click on the scrollbarSTEP6: Click on the “Charts “and select bar graph, pichart, histogram then click On continue and “ok”STEP7: Type the name of the charts and Generate reports. 6
- 7. OUTPUT: 7
- 8. BAR CHART: 8
- 9. PICHART: 9
- 10. FINAL QUIZ MARKS DETAILS: 10
- 11. RESULT: Thus, students marks has diagrammatically been analyzed and output is verifiedusing SPSS 13.3. 11
- 12. EX.NO:03 HYPOTHESIS TESTING ON SALES ANDDATE:15.3.10 EXPENDITURE DATA(T-TEST)The Following data have been taken from the marketing companysales 50 55 67 74 80 85 89 95 98 99 100 110Expenditure 45 67 78 98 100 72 91 34 94 61 86 89 From the above data find out: 1.Means 2.One sample T- test 3.One way ANOVAAIM: To analysis sales and expenditure using T-TestALGORITHM:STEP1: Open SPSS software 13.0STEP2: Click and select „Data view‟STEP3: Type the sales and expenditure of the companySTEP4: Click on <Analyze><compare means><one sample T test> <One-Way ANOVA>STEP5: Select the sales and click on the scrollbarSTEP6: Select the Expenditure and click on the scrollbar and click “ok”STEP7: solve the solution tables and Generate reports. 12
- 13. OUTPUT: 13
- 14. 14
- 15. 15
- 16. 16
- 17. RESULT: Thus, Sales and Expenditure are analyzed by T – test and output isVerified using SPSS 13.0. 17
- 18. EX.NO:04 CHI SQUARE TESTING ON PERFORMANCE INDATE:15.3.10 STRESSFULL SITUATIONThe Following data have been taken the test of mental performance in stress full situationfor 10 boys and10 girls Boys 2 2 4 1 4 3 0 2 7 5 Girls 4 4 6 0 6 5 2 3 6 4 Analysis the above data using chi square testAIM: To analysis the performance in stress full situation using chi-square testALGORITHM:STEP1: Open SPSS software 13.0STEP2: Click and select „Data view‟STEP3: Type the boys and girls mental performanceSTEP4: Click on <Analyze><non parametric test><chi square test>STEP5: Select the boys and click on the scrollbarSTEP6: Select the girls and click on the scrollbar and click “ok”STEP7: solve the solution tables and Generate reports 18
- 19. OUTPUT: 19
- 20. RESULT: Thus, the performance in stress full situation by using Chi-Square test isanalyzed. 20
- 21. EX.NO:05 FINDING THE CORRELATIONDATE:23.3.10 COEFFICIENTCalculate the Karl Pearson correlation coefficient for the following data x 28 41 40 38 35 33 40 32 36 33 y 23 34 33 34 30 26 28 31 36 38Aim: To find the correlation coefficient using SPSSALGORITHM:STEP1: Open SPSS software 13.0STEP2: Click and select „Data view‟STEP3: Type the X and Y valuesSTEP4: Click on <Analyze><correlate><Bivarite><Pearson>STEP5: Select the x and y and click on the scrollbarSTEP6: Click “ok” to solve the solution tablesSTEP7: Generate reports 21
- 22. OUTPUT: 22
- 23. RESULT: Thus, correlation coefficient is found out and verified the output using SPSS 13.0 23
- 24. EX.NO:06 FINDING THE REGRESSIONDATE:23.3.10Calculate the regression for the following data X 1 5 3 2 1 1 7 3 Y 6 1 0 0 1 2 1 3Aim:To find the Regression using SPSS 13.0ALGORITHM:STEP1: Open spss Package 13.0STEP2: Click and select „Data view‟STEP3: Type the X and Y valuesSTEP4: Click on <Analyze><regression><linear>STEP5: Select the x click on the scrollbar of dependentSTEP6: Select the y click on the scrollbar of independentSTEP7: click “ok” to solve the solution tables Generate reports 24
- 25. OUTPUT: 25
- 26. RESULT: Thus Regression is found out and output is verified using SPSS 13.0 26
- 27. EX.NO:07 LINEAR PROGRAMMING PROBLEMDATE:30.3.10 Problem : Max Z=15x1+6x2+9x3+2x4. Subject to the constraints, 2x1+x2+5x3+6x4≤20 3x1+x2+3x3+25x4≤24 7x1+x4≤70. x1,x2,x3,x4≥0Aim: To solve the Linear Programming Problem using the TORA.ALGORITHM:STEP1: Open the TORA softwareSTEP2: Choose the type of problem to be solvedSTEP3: Enter the problemSTEP4: Save the problem using F8keySTEP5: View the given data to ensure the correctness of given problemSTEP6: Solve the problem either by automated procedure or user guided Procedure.STEP7: view the solution and print the solution 27
- 28. OUTPUT: 28
- 29. 29
- 30. 30
- 31. 31
- 32. RESULT: Thus, Linear Programming Problem is solved and output isverified using TORA software. 32
- 33. EX.NO:08 TRANSPORTATION PROBLEMDATE:07.4.10Problem: A company has factories at three different bases S1, S2, S3. Which supply item towarehouse D1, D2, D3 monthly factory capacity are 140,160,120 respectively. Monthly warehouse requirements are 100, 160, and 70 respectively. Unit shippingcost are given (rupees) in following details. Plant D1 D2 D3 D4 Supply S1 16 19 12 0 140 S2 12 13 19 0 160 S3 14 28 8 0 120 Demand 100 150 70 100 420Aim: To solve the Transportation Problem using the TORA software.ALGORITHM:STEP1: Open the TORA softwareSTEP2: Choose the type of problem to be solvedSTEP3: Enter the problemSTEP4: Save the problem using F8keySTEP5: View the given data to ensure the correctness of given problem 33
- 34. STEP6: Solve the problem either by automated procedure or user guided ProcedureSTEP7: view the solution and print the solution 34
- 35. OUTPUT: 35
- 36. 36
- 37. RESULT: Thus, the Transportation Problem is solved and output is verifiedusing TORA software. 37
- 38. EX.NO:09 QUEUING PROBLEMDATE:13.5.10Problem: A television repairman finds that the time spent on his jobs has anexponential distribution with a mean of 30 minutes. If he repairs sets in the order inwhich they came in, and if the arrival of sets follows a Poisson distributionapproximately with an average rate of 10 per 8-hour day, what is the repairman‟sexpected idle time each day? How many jobs are ahead of the average set justbrought in?Aim: To solve the Queuing Problem using the TORA software.Steps to be followed:STEP1: Open the TORA softwareSTEP2: Choose the type of problem to be solvedSTEP3: Enter the problemSTEP4: Save the problem using F8 keySTEP5: View the given data to ensure the correctness of given dataSTEP6: Solve the problem either by automated procedure or user guided ProcedureSTEP7: view the solution and print the solution 38
- 39. OUTPUT: 39
- 40. RESULT: Thus the Queuing problem is solved and output is verified usingTORA software. 40
- 41. EX.NO:10 INTEGER LINEAR PROGRAMMINGDATE19.5.10Problem: Solve the following integer linear programming using Gomory‟s cuttingplane algorithm. Max Z=x1+2x2. Subject to the constraints, 2x2 ≤ 7 x1+x2 ≥ 7 2x1 ≥ 11 x1,x2 ≥ 0Aim: To solve the Integer Linear Programming Problem using the TORA software.ALGORITHM:STEP1: Open the TORA softwareSTEP2: Choose the type of problem to be solvedSTEP3: Enter the problemSTEP4: Save the problem using F8 keySTEP5: View the given data to ensure the correctness of given problemSTEP6: Solve the problem either by automated procedure or user guided ProcedureSTEP7: view the solution and print the solution 41
- 42. OUTPUT: 42
- 43. RESULT: Thus, the Integer Linear Programming Problem is solved andoutput is verified using TORA software. 43
- 44. EX.NO:11 NETWORK MODELSDATE:20.5.10Problem: Consider the details of a distance network as shown below. Arc Distance 1-2 3 1-3 8 1-4 10 2-3 4 2-4 7 3-4 2 3-5 8 4-5 6 Apply Floyd‟s algorithm and obtain the final matrices using TORA.Aim: To solve the Network models Programming Problem using the TORASoftware.ALGORITHM:STEP1: Open the TORA softwareSTEP2: Choose the type of problem to be solvedSTEP3: Enter the problemSTEP4: Save the problem using F8 keySTEP5: View the given data to ensure the correctness of given problemSTEP6: Solve the problem either by automated procedure or user guided ProcedureSTEP7: view the solution and print the solution 44
- 45. OUTPUT: 45
- 46. 46
- 47. RESULT: Thus, the Integer Linear Programming Problem is solved andoutput is verified using TORA software. 47

No public clipboards found for this slide

Be the first to comment