Spotting Patterns

mathisfunn

New member
Joined
Mar 26, 2017
Messages
1
Hey guys! I´ve been trying to spot a pattern in this data for some time now and I haven´t had any luck whatsoever. I was wondering if any of you fine individuals could take a look.
143
235
312
445
524
642
744
813
943
1052
1132
1235
1332
1426
1565
1604
1745
1842
1946
2022
2173
2280
2344
2442
2533
2684
2722
2854
2955
3003
3165
3221
3375
3441
3563
3662
3713
3846
3912
4057
4124
4246
4326
4444
4507
4642
4719
4821
4964
5044
5125
5236
5330
5456
5532
5626
5748
5824
5971
6013
6155
6233
6335
6417
6571
6653
6726
6861
6905
7064
7132

Cheers!
 

ksdhart2

Senior Member
Joined
Mar 25, 2016
Messages
1,194
Well, I've run the numbers and found that your two data sets have a Pearson's Correlation Coefficient of -0.1815. This means there's a small negative correlation between them, and as one decreases the other increases. That's a small enough correlation that it's unlikely there's any pattern to be found. For reference, the sets of {x} and {x^2}, using 71 data points, have a Pearson's Correlation Coefficient of 0.9691, a very strong positive correlation.

If we plot the two data sets on an xy-plane, with the first set being the x-values and the second set being the y-values, then the linear regression line, sometimes called the "line of best fit," is y = -0.1778x + 4.4083. However, the y-values predicted by this line will differ from the actual values by approximately 1.8977. In general, given an x-value not present in the list, the predicted y-value will be only 3.29% accurate.

Additionally, I inputted both sets of numbers into the Online Encyclopedia of Integer Sequences and got no results for either set. All of this is not to say there is no pattern, just that it's unlikely.
 
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