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Study about the effect of fungi, cultivars, and countries on seed .docx
- 1. Study about the effect of fungi, cultivars, and countries on seed germination and number of days it took the seeds from plant them until the shooting system appear in the soil surface. All of that was done by SAS Table of Country by Cultivar Country(Country) Cultivar(Cultivar) ba ha th Total sa 100 100 100 300 us 100 100 100 300
- 2. Total 200 200 200 600 Fungi Fungi Frequency Percent 0 238 39.67 1 362 60.33 Germination Germination Frequency Percent 0 231 38.50 1 369 61.50 Table of Fungi by Germination Fungi(Fungi)
- 5. Unknow 1 0.17 We have two countries: sa and us 3 Cultivar: ba, ha, th Fungi: 0 means absent of fungi, 1 means present of fungi Here we tested the germination GERMINATION Model Information Data Set WORK.GERMINATION Response Variable (Events) COUNT Response Variable (Trials) total Response Distribution Binomial Link Function Logit Variance Function Default Variance Matrix Diagonal Estimation Technique Maximum Likelihood Degrees of Freedom Method Residual Class Level Information Class Levels Values Country
- 6. 2 sa us Cultivar 3 ba ha th Fungi 2 0 1 Type III Tests of Fixed Effects Effect Num DF Den DF F Value Pr > F Country 1 146 14.40 0.0002 Cultivar 2 146 26.83 <.0001 Fungi 1 146 3.01 0.0851 Country*Cultivar 2 146 4.39 0.0141 Country*Fungi
- 7. 1 146 14.79 0.0002 Cultivar*Fungi 2 146 22.14 <.0001 Cultivar*Fungi Least Squares Means Cultivar Fungi Estimate Standard Error DF t Value Pr > |t| Alpha Lower Upper Mean Standard Error Mean ba 0 -5.1080 0.2532 146 -20.17
- 10. Fungi Estimate Standard Error DF t Value Pr > |t| Alpha Lower Upper Mean Standard Error Mean Lower Mean Upper Mean sa 0 -4.0783 0.1378 146 -29.60 <.0001 0.05 -4.3505 -3.8060 0.01665 0.002256 0.01274 0.02175 sa 1 -4.3071 0.1446 146
- 12. 0.03942 Fungi Least Squares Means Fungi Estimate Standard Error DF t Value Pr > |t| Alpha Lower Upper Mean Standard Error Mean Lower Mean Upper Mean 0 -4.0710 0.1013 146 -40.20 <.0001 0.05 -4.2711 -3.8709 0.01677 0.001670 0.01377 0.02041
- 13. 1 -3.8413 0.08793 146 -43.69 <.0001 0.05 -4.0151 -3.6676 0.02101 0.001809 0.01772 0.02490 Country Least Squares Means Country Estimate Standard Error DF t Value Pr > |t| Alpha Lower Upper Mean Standard Error Mean Lower Mean Upper Mean
- 14. sa -4.1927 0.1029 146 -40.76 <.0001 0.05 -4.3960 -3.9894 0.01488 0.001508 0.01218 0.01818 us -3.7197 0.07996 146 -46.52 <.0001 0.05 -3.8777 -3.5617 0.02367 0.001848 0.02028 0.02761 Cultivar Least Squares Means Cultivar Estimate
- 15. Standard Error DF t Value Pr > |t| Alpha Lower Upper Mean Standard Error Mean Lower Mean Upper Mean ba -4.5653 0.1527 146 -29.90 <.0001 0.05 -4.8670 -4.2635 0.01030 0.001556 0.007637 0.01388 ha -3.9262 0.1064 146 -36.89 <.0001 0.05 -4.1365
- 16. -3.7159 0.01934 0.002018 0.01573 0.02376 th -3.3771 0.07918 146 -42.65 <.0001 0.05 -3.5335 -3.2206 0.03302 0.002528 0.02837 0.03840 And here we tested the days Days Model Information Data Set WORK.DAYS Response Variable Days Response Distribution Poisson Link Function Log Variance Function Default Variance Matrix
- 17. Diagonal Estimation Technique Maximum Likelihood Degrees of Freedom Method Residual Class Level Information Class Levels Values Country 2 sa us Cultivar 3 ba ha th Fungi 2 0 1 Type III Tests of Fixed Effects Effect Num DF Den DF F Value Pr > F Country 1 359 8.18 0.0045 Cultivar 2 359 1.50 0.2236
- 18. Fungi 1 359 14.08 0.0002 Country*Cultivar 2 359 3.06 0.0482 Country*Fungi 1 359 1.28 0.2592 Cultivar*Fungi 2 359 1.92 0.1487 Cultivar*Fungi Least Squares Means Cultivar Fungi Estimate Standard Error DF t Value Pr > |t| Alpha Lower Upper Mean Standard Error Mean Lower
- 21. 63.5134 th 1 4.2219 0.01311 359 322.05 <.0001 0.05 4.1961 4.2477 68.1649 0.8936 66.4300 69.9451 Country*Fungi Least Squares Means Country Fungi Estimate Standard Error DF t Value Pr > |t| Alpha Lower Upper Mean Standard Error Mean Lower Mean
- 23. <.0001 0.05 4.0709 4.1559 61.1548 1.3220 58.6094 63.8107 us 1 4.1645 0.01710 359 243.60 <.0001 0.05 4.1309 4.1982 64.3635 1.1003 62.2356 66.5643 Fungi Least Squares Means Fungi Estimate Standard Error DF t Value Pr > |t| Alpha Lower
- 25. Country Least Squares Means Country Estimate Standard Error DF t Value Pr > |t| Alpha Lower Upper Mean Standard Error Mean Lower Mean Upper Mean sa 4.1894 0.01226 359 341.77 <.0001 0.05 4.1652 4.2135 65.9801 0.8088 64.4086 67.5899 us 4.1390 0.01175 359
- 26. 352.16 <.0001 0.05 4.1159 4.1621 62.7386 0.7374 61.3052 64.2056 Cultivar Least Squares Means Cultivar Estimate Standard Error DF t Value Pr > |t| Alpha Lower Upper Mean Standard Error Mean Lower Mean Upper Mean ba 4.1846 0.01849 359 226.31 <.0001
- 28. Here we tested each fungus separately Aspergillus Model Information Data Set WORK.DAYS Response Variable Days Response Distribution Poisson Link Function Log Variance Function Default Variance Matrix Diagonal Estimation Technique Maximum Likelihood Degrees of Freedom Method Residual Class Level Information Class Levels Values Country 2 sa us Cultivar 3 ba ha th Fungi 1 1
- 29. Fit Statistics -2 Log Likelihood 219.37 AIC (smaller is better) 231.37 AICC (smaller is better) 234.87 BIC (smaller is better) 239.98 CAIC (smaller is better) 245.98 HQIC (smaller is better) 234.18 Pearson Chi-Square 29.86 Pearson Chi-Square / DF 1.19 Type III Tests of Fixed Effects Effect Num DF Den DF F Value Pr > F Country 1 25 1.78 0.1940 Cultivar 2 25 2.04 0.1513 Country*Cultivar
- 30. 2 25 2.10 0.1436 Country*Cultivar Least Squares Means Country Cultivar Estimate Standard Error DF t Value Pr > |t| Alpha Lower Upper Mean Standard Error Mean Lower Mean Upper Mean sa ba 4.2965 0.03890 25 110.46 <.0001 0.05 4.2164 4.3766 73.4444
- 33. 89.5971 Cultivar Least Squares Means Cultivar Estimate Standard Error DF t Value Pr > |t| Alpha Lower Upper Mean Standard Error Mean Lower Mean Upper Mean ba 4.2251 0.04107 25 102.86 <.0001 0.05 4.1405 4.3097 68.3810 2.8087 62.8343 74.4174
- 34. ha 4.1817 0.06697 25 62.44 <.0001 0.05 4.0438 4.3196 65.4773 4.3849 57.0415 75.1606 th 4.3223 0.04389 25 98.49 <.0001 0.05 4.2319 4.4127 75.3602 3.3072 68.8477 82.4888 Country Least Squares Means Country Estimate Standard Error DF t Value
- 36. 59.8572 74.7407 Model Information Data Set WORK.DAYS Response Variable Days Response Distribution Poisson Link Function Log Variance Function Default Variance Matrix Diagonal Estimation Technique Maximum Likelihood Degrees of Freedom Method Residual Chaetomium Class Level Information Class Levels Values Country 2 sa us Cultivar 3 ba ha th
- 37. Fungi 1 1 Fit Statistics -2 Log Likelihood 299.61 AIC (smaller is better) 309.61 AICC (smaller is better) 311.19 BIC (smaller is better) 318.54 CAIC (smaller is better) 323.54 HQIC (smaller is better) 312.92 Pearson Chi-Square 32.80 Pearson Chi-Square / DF 0.84 Type III Tests of Fixed Effects Effect Num DF Den DF F Value Pr > F Country 1 39 2.49 0.1225 Cultivar 2 39
- 38. 1.53 0.2289 Country*Cultivar 1 39 1.16 0.2881 Country*Cultivar Least Squares Means Country Cultivar Estimate Standard Error DF t Value Pr > |t| Alpha Lower Upper Mean Standard Error Mean Lower Mean Upper Mean sa ha 4.1301 0.03824 39 108.02 <.0001 0.05 4.0527
- 40. 0.1291 39 31.71 <.0001 0.05 3.8332 4.3555 60.0000 7.7460 46.2109 77.9037 us th 4.1386 0.03375 39 122.63 <.0001 0.05 4.0703 4.2069 62.7143 2.1165 58.5761 67.1448 Cultivar Least Squares Means Cultivar Estimate Standard Error DF t Value Pr > |t|
- 42. 69.9915 th 4.2331 0.02321 39 182.41 <.0001 0.05 4.1862 4.2801 68.9334 1.5997 65.7724 72.2463 Country Least Squares Means Country Estimate Standard Error DF t Value Pr > |t| Alpha Lower Upper Mean Standard Error Mean Lower Mean Upper Mean sa
- 43. Non-est . . . . . . . Non-est . . . us 4.1566 0.04795 39 86.68 <.0001 0.05 4.0596 4.2536 63.8569 3.0622 57.9540 70.3611 Model Information Data Set WORK.DAYS Response Variable Days Response Distribution Poisson
- 44. Link Function Log Variance Function Default Variance Matrix Diagonal Estimation Technique Maximum Likelihood Degrees of Freedom Method Residual None Class Level Information Class Levels Values Country 2 sa us Cultivar 3 ba ha th Fungi 2 0 1 Fit Statistics -2 Log Likelihood 1110.17 AIC (smaller is better) 1122.17 AICC (smaller is better) 1122.71 BIC (smaller is better) 1140.74
- 45. CAIC (smaller is better) 1146.74 HQIC (smaller is better) 1129.71 Pearson Chi-Square 136.20 Pearson Chi-Square / DF 0.87 Type III Tests of Fixed Effects Effect Num DF Den DF F Value Pr > F Country 1 157 0.61 0.4370 Cultivar 2 157 1.03 0.3602 Country*Cultivar 2 157 2.22 0.1116 Country*Cultivar Least Squares Means
- 46. Country Cultivar Estimate Standard Error DF t Value Pr > |t| Alpha Lower Upper Mean Standard Error Mean Lower Mean Upper Mean sa ba 4.1589 0.04167 157 99.81 <.0001 0.05 4.0766 4.2412 64.0000 2.6667 58.9437 69.4900 sa ha 4.1100 0.02939
- 49. Cultivar Estimate Standard Error DF t Value Pr > |t| Alpha Lower Upper Mean Standard Error Mean Lower Mean Upper Mean ba 4.1521 0.03162 157 131.33 <.0001 0.05 4.0897 4.2146 63.5700 2.0099 59.7215 67.6665 ha 4.1279 0.01673 157 246.81 <.0001
- 50. 0.05 4.0948 4.1609 62.0445 1.0377 60.0283 64.1283 th 4.0968 0.02474 157 165.60 <.0001 0.05 4.0479 4.1456 60.1460 1.4879 57.2777 63.1579 Country Least Squares Means Country Estimate Standard Error DF t Value Pr > |t| Alpha Lower Upper Mean
- 52. Penicillium Model Information Data Set WORK.DAYS Response Variable Days Response Distribution Poisson Link Function Log Variance Function Default Variance Matrix Diagonal Estimation Technique Maximum Likelihood
- 53. Degrees of Freedom Method Residual Class Level Information Class Levels Values Country 2 sa us Cultivar 3 ba ha th Fungi 2 0 1 Fit Statistics -2 Log Likelihood 640.80 AIC (smaller is better) 650.80 AICC (smaller is better) 651.55 BIC (smaller is better) 663.13 CAIC (smaller is better) 668.13 HQIC (smaller is better) 655.77 Pearson Chi-Square 120.36 Pearson Chi-Square / DF
- 54. 1.47 Type III Tests of Fixed Effects Effect Num DF Den DF F Value Pr > F Country 1 82 2.62 0.1093 Cultivar 2 82 0.50 0.6082 Country*Cultivar 1 82 2.48 0.1191 Country*Cultivar Least Squares Means Country Cultivar Estimate Standard Error DF t Value Pr > |t| Alpha Lower
- 57. 0.05 4.1251 4.1905 63.9310 1.0499 61.8762 66.0541 Cultivar Least Squares Means Cultivar Estimate Standard Error DF t Value Pr > |t| Alpha Lower Upper Mean Standard Error Mean Lower Mean Upper Mean ba Non-est . . . . .
- 59. Country Least Squares Means Country Estimate Standard Error DF t Value Pr > |t| Alpha Lower Upper Mean Standard Error Mean Lower Mean Upper Mean sa Non-est . . . . . . . Non-est . . . us 4.1792 0.03169 82
- 60. 131.86 <.0001 0.05 4.1162 4.2423 65.3139 2.0701 61.3229 69.5646 Here is the Survival Analysis by using R studio- for each fungus Study about the effect of fungi, cultivars, and countries on seed germination and number of days it took the seeds from plant them until the shooting
- 61. system appear in the soil surface. A ll of that was done by SAS Table of Country by Cultivar Country(Country) Cultivar(Cultivar) ba ha th Total sa
- 65. 75 163 238 24 Hour Library Project – Team 2 November 24, 2016 Project Proposal The following proposal consists of research and surveys conducted for the purpose of gathering information about opening the library for twenty four hours. Initially, we as a group brainstormed the advantages and disadvantages of having the library open for twenty four hours. While brainstorming, we found that opening the library all day provides students with a quiet place to study, conduct research, and write papers that could potentially be away from a loud dorm room or noisy roommates at odd hours of the night. Most people know that there are some students that like to stay up late and party. This can sometimes be bothersome to the students that are trying to study and write papers beyond the hours of eleven pm. A library that is open for twenty four hours can fix that. On the other hand, the largest disadvantage we came up with is trying to staff the library all day. Finding people or students that are available and willing to working overnight are hard to come by. In addition to the brainstorming, we conducted surveys and research on the idea of opening the library for twenty four hours. First, we sent out surveys to students, teachers and
- 66. library staff that attend or work for CWU. After that, we conducted internet research on universities and colleges in Washington that have their libraries open for twenty four hours. Those universities and colleges are (Insert school names here). Next, we surveyed the library staff. Initially, there was some trouble acquiring staff that were able and willing to take the survey. But, with a little time and some asking around we were able to find 9 staff that were able to take the survey. Here are the positions of some of the people who took the survey. As you can see, there are a variety of staff that were willing to take a survey. After that, we asked four questions; how difficult would it be to staff the library overnight, how many students do you assist in a given day, are there a large number of students in the late evening and night hours, and are you interested in opening the library for 24-hours? The results have been put into charts. In conclusion and based on the results of surveying the library staff, having a library open for 24 hours a day could potentially be very difficult. This is because most of the responses were that it was extremely difficult to staff the library overnight. On the other hand, there could be some benefits. There are potentially a lot of students that are in the library during the closing hours. But, with all the data in mind, I think it is safe to say that maybe opening the library for 24 hours is not in CWU’s best interest. Sheet1Weighted Decision Matrix for Green Computing Research Project Created by:Date:CandidatesCriteriaWeightCandidate 1Candidate 2Candidate 3Candidate 4Replace Criteria 1, 2, 3, 4, and 5 with actual criteriaData Center management Capacity25%90509020On a scale of 1 - 100, provide a rating for each candidate for each criteriaResearch, writing, and editing efficiency25%90605020Virtualization of server resources Capacity20%40806020Efficiency in using open source
- 67. software10%25609070Capability to facilitate thin client solutions10%80704050 Weighted Project Scores90%63.556.56025 Weighted Score by Project Candidate 1 Candidate 2 Candidate 3 Candidate 4 63.5 56.5 60.0 25.0