Mam you are a very good teacher, specially i like that smiling face of yours, gives a positive mindset for learning. And yes i am implementing these function now.
@4:24 Q1 is not equal to the average (mean) of 1+2+3+4+5, Q1 is the median of (1,2,3,4,5), which is 3 in both cases. I think that the mean will always be equal to the median for any set of numbers incremented by 1. So for (11, 10) the mean and median are both 10.5. If your set of numbers was (2,2,2,4,5,5,7,8,9,10,11), then Q1 would be 2, but your way the mean would be (2+2+2+4+5)/5=3. Why would Q2 be the median of the entire set and Q1 be the mean of the the first half? It does not follow intuitively (statistics is frequently counter intuitive, but in this case it is intuitive).
nice video about the percentiles, I have a query here that can we make a percentile meter or filter for a column in the dataset, which includes all percentiles from 1 to 100.
Thank you for this video! However, can someone help me understand the following? In the video (e.g. 1.29 and 4.00) she uses median and average as two interchangeable terms (in my perception), saying that the q2 is the average of the data. and the q1 is the average of the data to the left of q2.. I was under the impression that this is about the 'place' in the data, and 'average' is not correct for this. Can someone help me by clarifying? Thanks!
Yes, you're absolutely right. The terms median and average are not interchangeable. In some datasets they might happen to be the same number, but their definition definitely isn't the same. The quartiles and median are about the location of the numbers in the dataset. Q1 is the median (the middle) of the lower half of the data. Q2 is the median (the middle) of the total list of numbers. Q3 is the median (the middle) of the upper half of the data. So let's say you have this list of numbers: 3, 5, 7, 8, 9, 11, 15, 16, 20, 21 Q1 = 7 (the median of the lower half of the data >>> the lower half being: 3, 5, 7, 8, 9) Q2 = 10 (the median of the total list of numbers >>> this list consists of 10 numbers, so the median falls right in between 9 en 11) Q3 = 16 (the median of the upper half of the data >>> the upper half being: 11, 15, 16, 20, 21) The average is the sum of all these numbers divided by 10 >>> 11,5
Another statistic lesson using Power BI, explained in a way that you do not need to be a statistician to understand. Few people explore this area, congratulations!
Thanks for another great video Ruth! I really appreciate your videos and I'm always trying to share them around the office. As a possible future video idea, I would really appreciate if one day you could do a video on "regular expression style problems" in Power BI. For example, I haven't found an elegant solution to a problem like "filter for cases where column y has the format '99XX99'". Thanks again for all the content!!
Hi, i have a measure that calculates the SUMX of seveal columns. Now i just want to create a new measure to calculate the % of the previous one. somehow i cant load the previous measure, it only let me use the Sum function with columns...any tip? thanks
Ok so I know what the values are for Q1,Q2,Q3,Q4. What I want to do is rank my managers based on a score, and put them in a quartile.... and then someone will come along and remove the heads of everyone in the bottom quartile.
