Question

In: Statistics and Probability

This exercise must be completed on the four subscales below, and you should, therefore, produce four...

This exercise must be completed on the four subscales below, and you should, therefore, produce four reliability analyses.

  • Subscale 1 (Fearof statistics): items 1, 3, 4, 5, 12, 16, 20, 21
  • Subscale 2 (Peerevaluation): items 2, 9, 19, 22, 23
  • Subscale 3 (Fearof computers): items 6, 7, 10, 13, 14, 15, 18
  • Subscale 4 (Fear of mathematics): items 8, 11, 17

Solutions

Expert Solution

For Subscale 1 (Fear of statistics):

Distribution Analysis: Subscale 1

Variable: Subscale 1

Censoring

Censoring Information Count
Uncensored value 8

Estimation Method: Maximum Likelihood

Distribution: Weibull

Parameter Estimates

Standard
Error
95.0% Normal CI
Parameter Estimate Lower Upper
Shape 1.27001 0.372059 0.715218 2.25514
Scale 11.0216 3.22897 6.20681 19.5712

Log-Likelihood = -26.314

Goodness-of-Fit

Anderson-Darling
(Adjusted)
1.847

Characteristics of Distribution

Standard
Error
95.0% Normal CI
Estimate Lower Upper
Mean(MTTF) 10.2291 2.86170 5.91160 17.6999
Standard Deviation 8.11159 3.03114 3.89968 16.8727
Median 8.25866 2.71924 4.33155 15.7462
First Quartile(Q1) 4.13230 1.94215 1.64488 10.3812
Third Quartile(Q3) 14.2541 3.97465 8.25256 24.6202
Interquartile Range(IQR) 10.1218 3.11921 5.53280 18.5170

Table of Percentiles

Standard
Error
95.0% Normal CI
Percent Percentile Lower Upper
1 0.294553 0.349211 0.0288411 3.00827
2 0.510418 0.525577 0.0678333 3.84068
3 0.705222 0.662110 0.111985 4.44111
4 0.888104 0.776723 0.159961 4.93074
5 1.06303 0.876815 0.211084 5.35350
6 1.23222 0.966343 0.264940 5.73094
7 1.39704 1.04773 0.321247 6.07544
8 1.55846 1.12258 0.379806 6.39485
9 1.71717 1.19206 0.440464 6.69449
10 1.87371 1.25700 0.503107 6.97819
20 3.38314 1.75371 1.22485 9.34451
30 4.89444 2.10970 2.10282 11.3921
40 6.49438 2.41365 3.13463 13.4552
50 8.25866 2.71924 4.33155 15.7462
60 10.2884 3.08512 5.71615 18.5179
70 12.7562 3.60455 7.33153 22.1946
80 16.0316 4.47285 9.27880 27.6990
90 21.2545 6.29522 11.8943 37.9806
91 22.0166 6.60198 12.2323 39.6274
92 22.8603 6.95248 12.5952 41.4913
93 23.8067 7.35878 12.9894 43.6325
94 24.8868 7.83865 13.4234 46.1396
95 26.1481 8.41976 13.9108 49.1507
96 27.6700 9.14884 14.4732 52.8994
97 29.5993 10.1141 15.1505 57.8279
98 32.2626 11.5154 16.0280 64.9408
99 36.6844 13.9991 17.3642 77.5011

Probability Plot for Subscale 1

The plot is:

For Subscale 2 (Peer evaluation):

Distribution Analysis: Subscale 2

Variable: Subscale 2

Censoring

Censoring Information Count
Uncensored value 5

Estimation Method: Maximum Likelihood

Distribution: Weibull

Parameter Estimates

Standard
Error
95.0% Normal CI
Parameter Estimate Lower Upper
Shape 1.71706 0.688381 0.782589 3.76737
Scale 16.6180 4.49877 9.77564 28.2497

Log-Likelihood = -17.777

Goodness-of-Fit

Anderson-Darling
(Adjusted)
2.757

Characteristics of Distribution

Standard
Error
95.0% Normal CI
Estimate Lower Upper
Mean(MTTF) 14.8175 3.92415 8.81760 24.9001
Standard Deviation 8.89061 3.64348 3.98198 19.8502
Median 13.4239 4.09917 7.37821 24.4233
First Quartile(Q1) 8.04369 3.60503 3.34167 19.3619
Third Quartile(Q3) 20.0999 5.23531 12.0639 33.4890
Interquartile Range(IQR) 12.0562 4.33083 5.96272 24.3770

Table of Percentiles

Standard
Error
95.0% Normal CI
Percent Percentile Lower Upper
1 1.14043 1.34237 0.113538 11.4550
2 1.71264 1.74472 0.232552 12.6129
3 2.17526 2.01512 0.353977 13.3675
4 2.57975 2.22112 0.477209 13.9459
5 2.94667 2.38776 0.601977 14.4239
6 3.28679 2.52749 0.728130 14.8366
7 3.60660 2.64749 0.855574 15.2033
8 3.91040 2.75233 0.984247 15.5360
9 4.20120 2.84512 1.11411 15.8424
10 4.48122 2.92809 1.24512 16.1281
20 6.93747 3.45241 2.61580 18.3992
30 9.11648 3.72296 4.09464 20.2973
40 11.2378 3.90981 5.68242 22.2243
50 13.4239 4.09917 7.37821 24.4233
60 15.7931 4.37439 9.17702 27.1790
70 18.5153 4.85529 11.0743 30.9558
80 21.9252 5.76868 13.0914 36.7199
90 27.0104 7.75587 15.3855 47.4185
91 27.7234 8.08683 15.6514 49.1065
92 28.5053 8.46277 15.9300 51.0075
93 29.3735 8.89552 16.2247 53.1784
94 30.3535 9.40234 16.5401 55.7029
95 31.4840 10.0099 16.8835 58.7108
96 32.8293 10.7629 17.2663 62.4200
97 34.5074 11.7448 17.7093 67.2393
98 36.7780 13.1421 18.2567 74.0889
99 40.4434 15.5471 19.0385 85.9137

Probability Plot for Subscale 2

The plot is:

For Subscale 3 (Fear of computers):

Distribution Analysis: Subscale 3

Variable: Subscale 3

Censoring

Censoring Information Count
Uncensored value 7

Estimation Method: Maximum Likelihood

Distribution: Weibull

Parameter Estimates

Standard
Error
95.0% Normal CI
Parameter Estimate Lower Upper
Shape 3.34627 1.03486 1.82524 6.13482
Scale 13.2622 1.57679 10.5054 16.7424

Log-Likelihood = -19.576

Goodness-of-Fit

Anderson-Darling
(Adjusted)
1.916

Characteristics of Distribution

Standard
Error
95.0% Normal CI
Estimate Lower Upper
Mean(MTTF) 11.9048 1.48470 9.32316 15.2012
Standard Deviation 3.92268 0.987858 2.39454 6.42603
Median 11.8863 1.58573 9.15145 15.4385
First Quartile(Q1) 9.13936 1.73267 6.30293 13.2523
Third Quartile(Q3) 14.6220 1.65468 11.7134 18.2529
Interquartile Range(IQR) 5.48264 1.43116 3.28698 9.14499

Table of Percentiles

Standard
Error
95.0% Normal CI
Percent Percentile Lower Upper
1 3.35417 1.59611 1.31988 8.52387
2 4.13240 1.70858 1.83766 9.29264
3 4.67184 1.76175 2.23100 9.78310
4 5.09910 1.79168 2.56097 10.1527
5 5.45919 1.80950 2.85095 10.4536
6 5.77393 1.82004 3.11284 10.7099
7 6.05570 1.82584 3.35367 10.9347
8 6.31229 1.82834 3.57798 11.1362
9 6.54895 1.82848 3.78892 11.3195
10 6.76942 1.82686 3.98876 11.4885
20 8.47121 1.76971 5.62499 12.7576
30 9.74576 1.69606 6.92916 13.7073
40 10.8501 1.63107 8.08121 14.5678
50 11.8863 1.58573 9.15145 15.4385
60 12.9202 1.57185 10.1792 16.3993
70 14.0187 1.60796 11.1962 17.5526
80 15.2889 1.73009 12.2477 19.0853
90 17.0161 2.03873 13.4547 21.5201
91 17.2451 2.09104 13.5974 21.8715
92 17.4930 2.15038 13.7476 22.2587
93 17.7644 2.21848 13.9075 22.6909
94 18.0661 2.29787 14.0798 23.1809
95 18.4083 2.39239 14.2688 23.7486
96 18.8078 2.50843 14.4814 24.4266
97 19.2951 2.65774 14.7300 25.2751
98 19.9365 2.86624 15.0408 26.4256
99 20.9324 3.21425 15.4923 28.2829

Probability Plot for Subscale 3

The plot is:

For Subscale 4 (Fear of mathematics):

Distribution Analysis: Subscale 4

Variable: Subscale 4

Censoring

Censoring Information Count
Uncensored value 3

Estimation Method: Maximum Likelihood

Distribution: Weibull

Parameter Estimates

Standard
Error
95.0% Normal CI
Parameter Estimate Lower Upper
Shape 3.53609 1.60425 1.45329 8.60388
Scale 13.3731 2.31424 9.52640 18.7730

Log-Likelihood = -8.181

Goodness-of-Fit

Anderson-Darling
(Adjusted)
3.658

Characteristics of Distribution

Standard
Error
95.0% Normal CI
Estimate Lower Upper
Mean(MTTF) 12.0390 2.19736 8.41835 17.2167
Standard Deviation 3.77481 1.37924 1.84452 7.72516
Median 12.0564 2.33631 8.24648 17.6264
First Quartile(Q1) 9.40183 2.55468 5.51980 16.0141
Third Quartile(Q3) 14.6672 2.40546 10.6353 20.2277
Interquartile Range(IQR) 5.26538 2.00882 2.49278 11.1218

Table of Percentiles

Standard
Error
95.0% Normal CI
Percent Percentile Lower Upper
1 3.64125 2.43167 0.983577 13.4801
2 4.43612 2.57900 1.41954 13.8631
3 4.98229 2.64566 1.75966 14.1068
4 5.41245 2.68131 2.04980 14.2915
5 5.77349 2.70106 2.30788 14.4432
6 6.08799 2.71139 2.54318 14.5737
7 6.36878 2.71565 2.76124 14.6896
8 6.62386 2.71577 2.96565 14.7946
9 6.85865 2.71296 3.15895 14.8913
10 7.07694 2.70800 3.34297 14.9816
20 8.75007 2.61117 4.87527 15.7045
30 9.99113 2.50003 6.11819 16.3157
40 11.0594 2.40422 7.22249 16.9346
50 12.0564 2.33631 8.24648 17.6264
60 13.0465 2.31035 9.22059 18.4599
70 14.0938 2.34918 10.1660 19.5393
80 15.2995 2.49866 11.1087 21.0714
90 16.9303 2.88930 12.1171 23.6554
91 17.1459 2.95623 12.2292 24.0393
92 17.3790 3.03232 12.3454 24.4650
93 17.6341 3.11983 12.4669 24.9429
94 17.9173 3.22205 12.5952 25.4885
95 18.2383 3.34401 12.7326 26.1249
96 18.6127 3.49405 12.8830 26.8906
97 19.0688 3.68752 13.0532 27.8566
98 19.6681 3.95823 13.2573 29.1788
99 20.5966 4.41101 13.5363 31.3394

Probability Plot for Subscale 4

The plot is:


Related Solutions

This exercise must be completed on the four subscales below, and you should, therefore, produce four...
This exercise must be completed on the four subscales below, and you should, therefore, produce four reliability analyses. o Subscale 1 (Fearof statistics): items 1, 3, 4, 5, 12, 16, 20, 21 o Subscale 2 (Peerevaluation): items 2, 9, 19, 22, 23 o Subscale 3 (Fearof computers): items 6, 7, 10, 13, 14, 15, 18 o Subscale 4 (Fear of mathematics): items 8, 11, 17
You are skeptical of the prospects of a particular technology stock. Therefore, you buy four put...
You are skeptical of the prospects of a particular technology stock. Therefore, you buy four put option contracts on the stock. You pay a premium of $3 per share, and each contract involves 100shares. The option’s strike price is $40. It has a maturity of three months. The firm is currently trading at $39. If your intuition is correct, and the market price of the stock falls to $30, how much have you made?
Plan production for a four-month period: February through May. For February and March, you should produce...
Plan production for a four-month period: February through May. For February and March, you should produce to exact demand forecast. For April and May, you should use overtime and inventory with a stable workforce; stable means that the number of workers needed for March will be held constant through May. However, government constraints put a maximum of 5,000 hours of overtime labor per month in April and May (zero overtime in February and March). If demand exceeds supply, then backorders...
Plan production for a four-month period: February through May. For February and March, you should produce...
Plan production for a four-month period: February through May. For February and March, you should produce to exact demand forecast. For April and May, you should use overtime and inventory with a stable workforce; stable means that the number of workers needed for March will be held constant through May. However, government constraints put a maximum of 5,000 hours of overtime labor per month in April and May (zero overtime in February and March). If demand exceeds supply, then backorders...
Plan production for a four-month period: February through May. For February and March, you should produce...
Plan production for a four-month period: February through May. For February and March, you should produce to exact demand forecast. For April and May, you should use overtime and inventory with a stable workforce; stable means that the number of workers needed for March will be held constant through May. However, government constraints put a maximum of 5,000 hours of overtime labor per month in April and May (zero overtime in February and March). If demand exceeds supply, then backorders...
Plan production for a four-month period: February through May. For February and March, you should produce...
Plan production for a four-month period: February through May. For February and March, you should produce to exact demand forecast. For April and May, you should use overtime and inventory with a stable workforce; stable means that the number of workers needed for March will be held constant through May. However, government constraints put a maximum of 5,000 hours of overtime labor per month in April and May (zero overtime in February and March). If demand exceeds supply, then backorders...
Exercise 6: Determination of growth of E.coli At the conclusion of this exercise you should be...
Exercise 6: Determination of growth of E.coli At the conclusion of this exercise you should be able to: determine the growth of an E.coli suspension over time using turbidometric analysis and viable count method. determine the generation time of the growth of E.coli. understand the phases of growth of E.coli over a period of time. Description of the experiments This experiment will determine the growth of E.coli over a four hour time period. In order to record this growth, we...
A producer is deciding whether they should produce corn or not. Based on the budget below,...
A producer is deciding whether they should produce corn or not. Based on the budget below, what should the producer do? Calculate TR, TVC, TFC, TC, AVC, AFC, ATC below for one acre of corn. Put final answers in the following boxes, then submit your work in the space provided below by either typing or uploading. Corn budget, one acre Yield per acre 228 Price per bushel $3.20 Total revenue per acre BLANK A Variable Costs Fertilizer $              140.00 Pesticides...
This assignment is to be completed in Excel. When completed, submit the exercise by the due...
This assignment is to be completed in Excel. When completed, submit the exercise by the due date in Blackboard (BB) and Attach a copy of the excel spreadsheet. Case Narrative: Ann E. Belle is age 42 and plans to retire in 25 years (at age 67). She has retirement savings in a mutual fund account, which has a current balance of $100,000 (Ann does not plan to add any additional money to this account). Also, Ann opened a 401K retirement...
This assignment is to be completed in Excel. When completed, submit the exercise by the due...
This assignment is to be completed in Excel. When completed, submit the exercise by the due date in Blackboard (BB) and Attach a copy of the excel spreadsheet. Case Narrative: Susan Smith is age 45 and plans to retire in 15 years (at age 60). She has retirement savings in a mutual fund account, which has a current balance of $250,000 (Susan does not plan to add any additional money to this account).  Also, Susan opened a 401K retirement account with...
ADVERTISEMENT
ADVERTISEMENT
ADVERTISEMENT