nickymobydicky
Badges: 0
Rep:
?
#1
Report Thread starter 5 years ago
#1
guys deadline is tomorrow and i have no clue how to evaluate spearmans rank and error bars any help PLEASEEEE!!!!
0
reply
Flying Cookie
Badges: 19
Rep:
?
#2
Report 5 years ago
#2
(Original post by nickymobydicky)
guys deadline is tomorrow and i have no clue how to evaluate spearmans rank and error bars any help PLEASEEEE!!!!
Chillax....!!!!

Spearman's rank:

1. It goes from -1 to +1

2. Zero means there is no correlation between two variables I.e. On a graph, the line of best fit is flat; the data points are scattered without a trend

3. A value close to -1 means a negative correlation, so as a variable goes up, the other goes down; on a graph, a line of best fit goes down from left to right; the closer to -1 the value, for example -0.8, the steeper the line and the stronger the correlation; -0.6 is a stronger correlation than -0.3

4. Same goes for +1 which is a positive correlation; as one variable goes up, so does the other; the line on a graph goes up from left to right

5. Error bars represent the range of values that must be considered as potentially true. For example you measure a pear as 9 cm but the ruler's error is 0.1 cm; the error would mean the "real" size could be anything in the 8.9-9.1 cm range.

6. When comparing two data sets with error bars, you want the error bars to be non-overlapping for the data sets to be considered truly different. If they overlap, there isn't a significant difference in values.
0
reply
nickymobydicky
Badges: 0
Rep:
?
#3
Report Thread starter 5 years ago
#3
(Original post by Flying Cookie)
Chillax....!!!!

Spearman's rank:

1. It goes from -1 to +1

2. Zero means there is no correlation between two variables I.e. On a graph, the line of best fit is flat; the data points are scattered without a trend

3. A value close to -1 means a negative correlation, so as a variable goes up, the other goes down; on a graph, a line of best fit goes down from left to right; the closer to -1 the value, for example -0.8, the steeper the line and the stronger the correlation; -0.6 is a stronger correlation than -0.3

4. Same goes for +1 which is a positive correlation; as one variable goes up, so does the other; the line on a graph goes up from left to right

5. Error bars represent the range of values that must be considered as potentially true. For example you measure a pear as 9 cm but the ruler's error is 0.1 cm; the error would mean the "real" size could be anything in the 8.9-9.1 cm range.

6. When comparing two data sets with error bars, you want the error bars to be non-overlapping for the data sets to be considered truly different. If they overlap, there isn't a significant difference in values.
Thanks for replying helped me a bit though i am still quite confused
0
reply
Flying Cookie
Badges: 19
Rep:
?
#4
Report 5 years ago
#4
(Original post by nickymobydicky)
Thanks for replying helped me a bit though i am still quite confused
You shouldn't leave revision till the last minute dear chap!
0
reply
numanali
Badges: 3
Rep:
?
#5
Report 5 years ago
#5
Check youtube. You'll definitely find help there!


Posted from TSR Mobile
0
reply
X

Quick Reply

Attached files
Write a reply...
Reply
new posts
Back
to top
Latest
My Feed

See more of what you like on
The Student Room

You can personalise what you see on TSR. Tell us a little about yourself to get started.

Personalise

Do you have the space and resources you need to succeed in home learning?

Yes I have everything I need (398)
56.37%
I don't have everything I need (308)
43.63%

Watched Threads

View All