Homework Answers
Solution:
conclusion
ACL MCL PCL
185 85 95 85
211 71 102 93
192 45 125 78
215 93 123 81
255 65 98 65
246 60 130 102
203 58 145 96
199 55 137 105
205 62 125 83
241 48 122 75
295 71 108 78
200 66 99 88
245 55 115 92
261 62 131 101
229 61 134 84
206 49 140 91
275 59 160 77
243 56 126 79
281 54 144 83
214 57 132 80
224 47 109 87
Mean n Std.Dev
229.8 21 31.10 Concus
60.9 21 11.80 ACL
123.8 21 17.33 MCL
85.9 21 9.90 PCL
125.1 84 67.58 Total
Add Answer to:
3- Test to check whether the concussion injuries in 2007 are greater than 40% of the...
A sample of number of NFL injuries including Concussion, ACL tears, MCL tears and PCL tears...
A sample of number of NFL injuries including Concussion, ACL
tears, MCL tears and PCL tears from 1999 to 2019 are as follows 1
:
4- Conduct an Analysis of Variance for the four groups
concussion, ACL, MCL and PCL. (alpha=1%)
PCL Year 1999 2000 2001 2002 2003 2004 2005 2006 MCL 95 102 125 123 98 130 85 93 78 81 145 137 65 102 96 105 83 75 78 2007 2008 2009 2010 NFL Injuries Concussion ACL 185...
A sample of number of NFL injuries including Concussion, ACL tears, MCL tears and PCL tears...
A sample of number of NFL injuries including Concussion, ACL
tears, MCL tears and PCL tears from 1999 to 2019 are as follows 1
:
3- Test to check whether the concussion injuries in 2007 are
greater than 40% of the total injuries in 2007 or not?
(alpha=1%)
PCL Year 1999 2000 2001 2002 2003 2004 2005 2006 MCL 95 102 125 123 98 130 85 93 78 81 145 137 65 102 96 105 83 75 78 2007 2008...
A sample of number of NFL injuries including Concussion, ACL tears, MCL tears and PCL tears...
A sample of number of NFL injuries including Concussion, ACL
tears, MCL tears and PCL tears from 1999 to 2019 are as follows 1
:
2- Develop one hypothesis test on variances (As an example:
compare variance of Concussion and MCL from 1999 to 2019). You may
compare other two variances. (alpha=5%)
PCL Year 1999 2000 2001 2002 2003 2004 2005 2006 MCL 95 102 125 123 98 130 85 93 78 81 145 137 65 102 96 105 83...
A sample of number of NFL injuries including Concussion, ACL tears, MCL tears and PCL tears...
A sample of number of NFL injuries including Concussion, ACL
tears, MCL tears and PCL tears from 1999 to 2019 are as follows 1
:
1- Develop one hypothesis test on means (Two examples could be:
(1) Compare mean of ACL and PCL from 1999 to 2019, or (2)
you can compare the concussion injuries from 1999 to 2008 with
concussion injuries from 2009 to 2019). You may compare
other two means. (alpha=5%)
Please answer the comparison for concussions. Thanks....
Please help with the Bonus portion. I already have 1 to 4 done (But your welcome...
Please help with the Bonus portion. I already
have 1 to 4 done (But your welcome on giving me input on those).
Thank you
A sample of number of NFL injuries including Concussion, ACL tears, MCL tears and PCL tears from 1999 to 2019 are as follows: 1- Develop one hypothesis test on means (Two examples could be: (1) Compare mean of ACL and PCL from 1999 to 2019, or (2) you can compare the concussion injuries from 1999 to...
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33 On May 6, Jim Ryan borrowed $14,000 from Lane Bank at 7 % interest. Jim...
33 On May 6, Jim Ryan borrowed $14,000 from Lane Bank at 7 % interest. Jim plans to repay the loan on March 11. Assume the loan is on ordinary interest. How much will Jim repay on March 11? (Use Days in a year table) (Round your answer to the nearest cent.) Jm repay etbook 7-1 TABLE Exact days-in-a-year calendar (excluding leap year)" Day of month 30 31 30 31 28 31 30 31 31 30 31 31 Dec Mar...
Hi it's python I imported a data which are so many words in txt and I arranged and reshaped with ...
Hi it's python I imported a data which are so many words in txt
and I arranged and reshaped with alphabetically both rows and
columns
I was successful with these steps but I am stuck with next
step
below is my code and screenshot
import numpy as np
import pandas as pd
data=pd.read_csv("/Users/superman/Downloads/words_file2.txt",header=None)
df_input=pd.DataFrame(data)
df_output=pd.DataFrame(np.arange(676).reshape((26,26)),
index =
['a','b','c','d','e','f','g','h','i','j','k','l','m','n','o','p','q','r','s','t','u','v','w','x','y','z'],
columns =
['a','b','c','d','e','f','g','h','i','j','k','l','m','n','o','p','q','r','s','t','u','v','w','x','y','z'])
df_output.index.name="Start"
df_output.columns.name="End"
df_output
This below screen shot is what I have to find
I have to find each word...
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indicate. Thank you very much! (The GCMS data is just a long set of
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IR of unknown:
NMR unknown Proton Graphs (first is overall graph,
others that follow are zoomed in sections):
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others that follow...
If the two signal handling functions in 3000pc were replaced by one function, would there be...
If the two signal handling functions in 3000pc were replaced by one function, would there be any significant loss of functionality? Briefly explain /* 3000pc.c */ 2 3 4 5 6 7 8 #include <stdio.h> 9 #include <stdlib.h> 10 #include <unistd.h> 11 #include <sys/mman.h> 12 #include <errno.h> 13 #include <string.h> 14 #include <sys/types.h> 15 #include <sys/wait.h> 16 #include <semaphore.h> 17 #include <string.h> 18 #include <time.h> 19 20 #define QUEUESIZE 32 21 #define WORDSIZE 16 22 23 const int wordlist_size =...
A sample of number of NFL injuries including Concussion, ACL
tears, MCL tears and PCL tears from 1999 to 2019 are as follows 1
:
4- Conduct an Analysis of Variance for the four groups
concussion, ACL, MCL and PCL. (alpha=1%)
PCL Year 1999 2000 2001 2002 2003 2004 2005 2006 MCL 95 102 125 123 98 130 85 93 78 81 145 137 65 102 96 105 83 75 78 2007 2008 2009 2010 NFL Injuries Concussion ACL 185...
A sample of number of NFL injuries including Concussion, ACL
tears, MCL tears and PCL tears from 1999 to 2019 are as follows 1
:
3- Test to check whether the concussion injuries in 2007 are
greater than 40% of the total injuries in 2007 or not?
(alpha=1%)
PCL Year 1999 2000 2001 2002 2003 2004 2005 2006 MCL 95 102 125 123 98 130 85 93 78 81 145 137 65 102 96 105 83 75 78 2007 2008...
A sample of number of NFL injuries including Concussion, ACL
tears, MCL tears and PCL tears from 1999 to 2019 are as follows 1
:
2- Develop one hypothesis test on variances (As an example:
compare variance of Concussion and MCL from 1999 to 2019). You may
compare other two variances. (alpha=5%)
PCL Year 1999 2000 2001 2002 2003 2004 2005 2006 MCL 95 102 125 123 98 130 85 93 78 81 145 137 65 102 96 105 83...
A sample of number of NFL injuries including Concussion, ACL
tears, MCL tears and PCL tears from 1999 to 2019 are as follows 1
:
1- Develop one hypothesis test on means (Two examples could be:
(1) Compare mean of ACL and PCL from 1999 to 2019, or (2)
you can compare the concussion injuries from 1999 to 2008 with
concussion injuries from 2009 to 2019). You may compare
other two means. (alpha=5%)
Please answer the comparison for concussions. Thanks....
Please help with the Bonus portion. I already
have 1 to 4 done (But your welcome on giving me input on those).
Thank you
A sample of number of NFL injuries including Concussion, ACL tears, MCL tears and PCL tears from 1999 to 2019 are as follows: 1- Develop one hypothesis test on means (Two examples could be: (1) Compare mean of ACL and PCL from 1999 to 2019, or (2) you can compare the concussion injuries from 1999 to...
33 On May 6, Jim Ryan borrowed $14,000 from Lane Bank at 7 % interest. Jim plans to repay the loan on March 11. Assume the loan is on ordinary interest. How much will Jim repay on March 11? (Use Days in a year table) (Round your answer to the nearest cent.) Jm repay etbook 7-1 TABLE Exact days-in-a-year calendar (excluding leap year)" Day of month 30 31 30 31 28 31 30 31 31 30 31 31 Dec Mar...
Hi it's python I imported a data which are so many words in txt
and I arranged and reshaped with alphabetically both rows and
columns
I was successful with these steps but I am stuck with next
step
below is my code and screenshot
import numpy as np
import pandas as pd
data=pd.read_csv("/Users/superman/Downloads/words_file2.txt",header=None)
df_input=pd.DataFrame(data)
df_output=pd.DataFrame(np.arange(676).reshape((26,26)),
index =
['a','b','c','d','e','f','g','h','i','j','k','l','m','n','o','p','q','r','s','t','u','v','w','x','y','z'],
columns =
['a','b','c','d','e','f','g','h','i','j','k','l','m','n','o','p','q','r','s','t','u','v','w','x','y','z'])
df_output.index.name="Start"
df_output.columns.name="End"
df_output
This below screen shot is what I have to find
I have to find each word...
Please determine the IDENTITY of the unknown
compound and explain how each peak / data point from the following
instruments led to that identification. What does the gcms
indicate. Thank you very much! (The GCMS data is just a long set of
numbers which is why the question appears so long).
IR of unknown:
NMR unknown Proton Graphs (first is overall graph,
others that follow are zoomed in sections):
NMR unknown Carbon Graphs (first is overall graph,
others that follow...
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