Question : By using Python Google Colab Programming Language, Experiment trials input text file is given below from which you have to answer. Calculate the median reaction time of all 75 trials. Calculate the % of ‘match’ trials in the first half of trials with reaction time less than or equal to the median reaction time. Next, calculate the % of ‘match’ trials in the second half of trials with reaction time greater than the median reaction time. Report both percentages. Based on a comparison of the two ‘match’ percentages what can be concluded about the relationship between the ‘match’ % and reaction time in your experimental data? Please share screenshot of code as well Output. Text.txt File Data is given Below. Please save it as Text.txt file name or You can Download it from this link sendanywhe.re/XXJ3M068 : 1 1 0 1 0 0 0 3000 3 8 8 0 1 2 0 1 0 0 0 3000 2 2 2 8 1 3 0 1 0 0 0 3000 3 3 3 2 1 4 0 1 0 0 0 3000 2 1 1 3 1 5 0 1 0 0 0 3000 2 11 11 1 1 6 1 1 1 0 0 469 1 1 1 11 1 7 0 1 0 0 0 3000 2 2 2 1 1 8 0 1 0 0 0 3000 2 14 14 2 1 9 0 1 0 0 0 3000 3 8 8 14 1 10 1 1 1 0 0 610 1 14 14 8 1 11 0 1 0 0 0 3000 3 4 4 14 1 12 0 1 0 0 0 3000 2 15 15 4 1 13 1 1 1 0 0 520 1 4 4 15 1 14 1 1 1 0 0 1723 1 15 15 4 1 15 0 1 0 0 0 3000 2 8 8 15 1 16 1 1 1 0 0 983 1 15 15 8 1 17 0 1 0 0 0 3000 2 11 11 15 1 18 0 1 0 0 0 3000 2 1 1 11 1 19 1 1 1 0 0 613 1 11 11 1 1 20 1 1 1 0 0 885 1 1 1 11 1 21 0 1 0 0 0 3000 2 8 8 1 1 22 0 1 0 0 0 3000 2 8 8 8 1 23 0 1 0 0 0 3000 3 10 10 8 1 24 0 1 0 0 0 3000 2 9 9 10 1 25 0 1 0 0 0 3000 2 5 5 9 2 1 0 1 0 0 0 3000 2 12 12 5 2 2 0 1 0 0 0 3000 3 12 12 12 2 3 1 1 1 0 0 671 1 12 12 12 2 4 0 1 0 0 0 3000 2 1 1 12 2 5 0 1 0 0 0 3000 3 15 15 1 2 6 0 1 0 0 0 3000 2 4 4 15 2 7 0 1 0 0 0 3000 2 4 4 4 2 8 0 1 0 0 0 3000 3 12 12 4 2 9 0 1 0 0 0 3000 2 1 1 12 2 10 0 1 0 0 0 3000 2 1 1 1 2 11 0 1 0 0 0 3000 2 15 15 1 2 12 1 1 1 0 0 608 1 1 1 15 2 13 0 1 0 0 0 3000 3 7 7 1 2 14 0 1 0 0 0 3000 3 7 7 7 2 15 1 1 1 0 0 432 1 7 7 7 2 16 0 1 0 0 0 3000 3 1 1 7 2 17 0 1 0 0 0 3000 2 6 6 1 2 18 1 1 1 0 0 442 1 1 1 6 2 19 1 1 1 0 0 710 1 6 6 1 2 20 0 0 0 0 1 2166 2 6 6 6 2 21 0 1 0 0 0 3000 2 13 13 6 2 22 0 1 0 0 0 3000 2 7 7 13 2 23 0 1 0 0 0 3000 3 1 1 7 2 24 0 1 0 0 0 3000 3 13 13 1 2 25 1 1 1 0 0 574 1 1 1 13 3 1 0 1 0 0 0 3000 2 4 4 1 3 2 0 1 0 0 0 3000 1 13 13 4 3 3 0 1 0 0 0 3000 2 6 6 13 3 4 1 0 0 1 0 3000 1 13 13 6 3 5 1 1 1 0 0 411 1 6 6 13 3 6 0 1 0 0 0 3000 2 4 4 6 3 7 0 1 0 0 0 3000 3 15 15 4 3 8 0 1 0 0 0 3000 2 15 15 15 3 9 0 1 0 0 0 3000 2 12 12 15 3 10 0 1 0 0 0 3000 2 2 2 12 3 11 0 1 0 0 0 3000 3 13 13 2 3 12 0 1 0 0 0 3000 3 6 6 13 3 13 1 1 1 0 0 437 1 13 13 6 3 14 0 1 0 0 0 3000 2 9 9 13 3 15 0 1 0 0 0 3000 3 15 15 9 3 16 1 1 1 0 0 1030 1 9 9 15 3 17 0 1 0 0 0 3000 2 6 6 9 3 18 0 1 0 0 0 3000 2 8 8 6 3 19 0 1 0 0 0 3000 3 11 11 8 3 20 1 1 1 0 0 1252 1 8 8 11 3 21 0 1 0 0 0 3000 3 8 8 8 3 22 0 1 0 0 0 3000 3 14 14 8 3 23 0 1 0 0 0 3000 2 6 6 14 3 24 0 1 0 0 0 3000 2 7 7 6 3 25 0 1 0 0 0 3000 2 9 9 7 Information about Data given above : Colum Meaning 1 Blocknumber (the number of the block, there are 3 blocks) 2 Trial number (the number of the trial) 3 Type of trial (1=a matching stimulus ; 0=a non-matching stimulus) 4 Score (1 means correct, 0 means incorrect) 5 Match (1 means participants matched correctly, 0 otherwise; only meaningful on match trials) 6 Miss (1 means participants missed, 0 otherwise; only meaningful on non-matching trials) 7 False Alarm (1 means participants wrongly pressed button, 0 otherwise; only meaningful on non-matching trials) 8 Reaction Time 9 Memory (a variable used internally) 10 Current letter (the current letter, a number between 1 and 15, representing letterA, etc) 11 nback1 (the letter 1 trial ago, a number between 1 and 15, representing with letterA, etc) 12 nback2 (the letter 2 trials ago, a number between 1 and 15, representing with letterA, etc)
Question : By using Python Google Colab Programming Language, Experiment trials input text file is given below from which you have to answer.
Calculate the median reaction time of all 75 trials. Calculate the % of ‘match’ trials in the first half of trials with reaction time less than or equal to the median reaction time. Next, calculate the % of ‘match’ trials in the second half of trials with reaction time greater than the median reaction time. Report both percentages.
Based on a comparison of the two ‘match’ percentages what can be concluded about the relationship between the ‘match’ % and reaction time in your experimental data?
Please share screenshot of code as well Output.
Text.txt File Data is given Below. Please save it as Text.txt file name or You can Download it from this link sendanywhe.re/XXJ3M068 :
1 1 0 1 0 0 0 3000 3 8 8 0
1 2 0 1 0 0 0 3000 2 2 2 8
1 3 0 1 0 0 0 3000 3 3 3 2
1 4 0 1 0 0 0 3000 2 1 1 3
1 5 0 1 0 0 0 3000 2 11 11 1
1 6 1 1 1 0 0 469 1 1 1 11
1 7 0 1 0 0 0 3000 2 2 2 1
1 8 0 1 0 0 0 3000 2 14 14 2
1 9 0 1 0 0 0 3000 3 8 8 14
1 10 1 1 1 0 0 610 1 14 14 8
1 11 0 1 0 0 0 3000 3 4 4 14
1 12 0 1 0 0 0 3000 2 15 15 4
1 13 1 1 1 0 0 520 1 4 4 15
1 14 1 1 1 0 0 1723 1 15 15 4
1 15 0 1 0 0 0 3000 2 8 8 15
1 16 1 1 1 0 0 983 1 15 15 8
1 17 0 1 0 0 0 3000 2 11 11 15
1 18 0 1 0 0 0 3000 2 1 1 11
1 19 1 1 1 0 0 613 1 11 11 1
1 20 1 1 1 0 0 885 1 1 1 11
1 21 0 1 0 0 0 3000 2 8 8 1
1 22 0 1 0 0 0 3000 2 8 8 8
1 23 0 1 0 0 0 3000 3 10 10 8
1 24 0 1 0 0 0 3000 2 9 9 10
1 25 0 1 0 0 0 3000 2 5 5 9
2 1 0 1 0 0 0 3000 2 12 12 5
2 2 0 1 0 0 0 3000 3 12 12 12
2 3 1 1 1 0 0 671 1 12 12 12
2 4 0 1 0 0 0 3000 2 1 1 12
2 5 0 1 0 0 0 3000 3 15 15 1
2 6 0 1 0 0 0 3000 2 4 4 15
2 7 0 1 0 0 0 3000 2 4 4 4
2 8 0 1 0 0 0 3000 3 12 12 4
2 9 0 1 0 0 0 3000 2 1 1 12
2 10 0 1 0 0 0 3000 2 1 1 1
2 11 0 1 0 0 0 3000 2 15 15 1
2 12 1 1 1 0 0 608 1 1 1 15
2 13 0 1 0 0 0 3000 3 7 7 1
2 14 0 1 0 0 0 3000 3 7 7 7
2 15 1 1 1 0 0 432 1 7 7 7
2 16 0 1 0 0 0 3000 3 1 1 7
2 17 0 1 0 0 0 3000 2 6 6 1
2 18 1 1 1 0 0 442 1 1 1 6
2 19 1 1 1 0 0 710 1 6 6 1
2 20 0 0 0 0 1 2166 2 6 6 6
2 21 0 1 0 0 0 3000 2 13 13 6
2 22 0 1 0 0 0 3000 2 7 7 13
2 23 0 1 0 0 0 3000 3 1 1 7
2 24 0 1 0 0 0 3000 3 13 13 1
2 25 1 1 1 0 0 574 1 1 1 13
3 1 0 1 0 0 0 3000 2 4 4 1
3 2 0 1 0 0 0 3000 1 13 13 4
3 3 0 1 0 0 0 3000 2 6 6 13
3 4 1 0 0 1 0 3000 1 13 13 6
3 5 1 1 1 0 0 411 1 6 6 13
3 6 0 1 0 0 0 3000 2 4 4 6
3 7 0 1 0 0 0 3000 3 15 15 4
3 8 0 1 0 0 0 3000 2 15 15 15
3 9 0 1 0 0 0 3000 2 12 12 15
3 10 0 1 0 0 0 3000 2 2 2 12
3 11 0 1 0 0 0 3000 3 13 13 2
3 12 0 1 0 0 0 3000 3 6 6 13
3 13 1 1 1 0 0 437 1 13 13 6
3 14 0 1 0 0 0 3000 2 9 9 13
3 15 0 1 0 0 0 3000 3 15 15 9
3 16 1 1 1 0 0 1030 1 9 9 15
3 17 0 1 0 0 0 3000 2 6 6 9
3 18 0 1 0 0 0 3000 2 8 8 6
3 19 0 1 0 0 0 3000 3 11 11 8
3 20 1 1 1 0 0 1252 1 8 8 11
3 21 0 1 0 0 0 3000 3 8 8 8
3 22 0 1 0 0 0 3000 3 14 14 8
3 23 0 1 0 0 0 3000 2 6 6 14
3 24 0 1 0 0 0 3000 2 7 7 6
3 25 0 1 0 0 0 3000 2 9 9 7
Information about Data given above :
| Colum | Meaning |
|---|---|
|
1 |
Blocknumber (the number of the block, there are 3 blocks) |
|
2 |
Trial number (the number of the trial) |
|
3 |
Type of trial (1=a matching stimulus ; 0=a non-matching stimulus) |
|
4 |
Score (1 means correct, 0 means incorrect) |
|
5 |
Match (1 means participants matched correctly, 0 otherwise; only meaningful on match trials) |
|
6 |
Miss (1 means participants missed, 0 otherwise; only meaningful on non-matching trials) |
|
7 |
False Alarm (1 means participants wrongly pressed button, 0 otherwise; only meaningful on non-matching trials) |
|
8 |
Reaction Time |
|
9 |
Memory (a variable used internally) |
|
10 |
Current letter (the current letter, a number between 1 and 15, representing letterA, etc) |
|
11 |
nback1 (the letter 1 trial ago, a number between 1 and 15, representing with letterA, etc) |
|
12 |
nback2 (the letter 2 trials ago, a number between 1 and 15, representing with letterA, etc) |
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