How do I know if my results are right?

  • Are the average and median pretty close? Good, that indicates your data is not heavily skewed.
  • Is your range small? Okay, these data points are grouped together.
  • Are your median or average pretty close to the middle or your range? Great, another indicator your data is not skewed.
  • Modes are generally more helpful with integers, but your mode being close to your average and median is another good indicator of data consistency.
Finding trends with STD
  • If it is not centered and symmetrical, that indicates skew. Curves should have a smooth bell shape.
  • If it is flat, the data has a large relative standard deviation.
  • If it is tall, the data has a small standard deviation.
  1. Make a quantifiable hypothesis about your data set. ie — My sample average is greater than the population average (µ>X).
  2. Make a null hypothesis, that is essentially the opposite of your hypothesis. ie — My sample average is less than or equal to the population average(µ≤X).
  3. Calculate your Z-score. Example here for single sample Z-score. For comparing a sample set, just add sqrt(number of samples) to the denominator.
  4. Look up Z-score on a table to get your P-score. This is the probability that your hypothesis is supported. Depending on your hypothesis (greater than or less than) you will need to use the left or the right table.

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Eric Lani

Eric Lani

Analyst, engineer and data nerd writing about my favorite parts of my job and industry