text: Title: The correlation criteria for test pass/fail is inconsistent
  Body: **Which version are you running? The lastest version is on Github. Pip is for major releases.**
  ```python
  import pandas_ta as ta
  print(ta.version)
  0.3.45b0
  ```
  **Do you have _TA Lib_ also installed in your environment?**
  No
  
  **Did you upgrade? Did the upgrade resolve the issue?**
  Yes, force an re-install. Issue remains.
  
  **Describe the bug**
  During my adhoc tests, I realized that test compares the result with other lib (ta-lib), which is fine. It also compares value by value through 
  ```python
  pdt.assert_series_equal(result, expected, check_names=False)
  ```
  But, the code makes a correlation with the 2 results which is not correct. 
  ```python
  corr = pandas_ta.utils.df_error_analysis(result, expected, col=CORRELATION)
  self.assertGreater(corr, CORRELATION_THRESHOLD)
  ```
  
  Correlation is not a good critera because results may have correlation somehow. 
  The test that I did was to change the results of ta-lib to the candle high values for sma function. The test result is PASS, why? Because the result has correlation with high values.
  
  > Example:
  > For a correct PASS:
  > test_sma(), correlation = 1.0
  > AssertionError: Series are different
  > Series values are different (0.01908 %)
  > :. series are a bit different, and correlation is 1.
  > 
  > For a incorrect PASS (positive-false):
  > test_sma(), correlation = 0.9991919523534346
  > AssertionError: Series are different
  > Series values are different (99.96184 %)
  > :. series are completely different, but correlation is almost 1 !
  > The test result is a Positive-False, because correlation criteria is not wise.
  
  **To Reproduce**
  get the demo code at:
  https://github.com/ffhirata/pandas-ta/tree/testCorrelationFailure
  Run:
  > python -m unittest -v tests.test_indicator_overlap.main
  or Check the report output in attachment, issue_report.pdf.
  [issue_report.pdf](https://github.com/twopirllc/pandas-ta/files/7990009/issue_report.pdf)
  
  **Expected behavior**
  The criteria should be in comparison of value by value, if a row is not equal than a justification should be provide, ie, line by line.
  The test results could be organized in campaigns with static reports, because of manual justification.
  or
  The criteria should be based on assertion output of Series values are different (xxx %).
  
  **Screenshots**
  none
  
  **Additional context**
  The confidence of lib has to be reviewed.
  
  Thanks for using Pandas TA!
  