0:00 Welcome to Data Integrity 4:22 Why Data Integrity is so Important * Data integrity: accuracy, completeness, consistency, and trustworthiness of data throughout its lifecycle * Data can be compromised: Data replication, Data transfer, Data manipulation,... 7:15 Balancing Objective and Integrity 10:31 Dealing with Insufficient Data Types of Insufficient Data: * Only one source >> missing the overall, also not enough data. * Data keeps updating. * Outdated data. * Geographically-limited data. Dealing: * Find more data sources. * Collect more data if time allows. * Talk to stakeholders, and adjust the objective. * Look for new data set. 14:22 The Importance of Sample Size * If collecting the whole population is too time-consuming and expensive. * So collecting a sample size of the population could represent the whole: effectively time and cost. 17:51 Using Statistical Power * Perform on a "larger" sample size * Hypothesis testing: survey/experiment to get the meaningful results * And using "Confidence level" to determine the results of an experiment from hypothesis testing. * At least 0.8 or 80% confidence level proven results the hypothesis testing. 22:51 Determine Sample Sizes Through Population and Purpose * Focus on the big picture: get a proper sample size make the sense, and lead valid and useful. * To find a sample size, need to know: the population size, confidence level, and margin of error. >> Note: confidence level and margin of error do have to not add up to 100%, they are not dependent on each other. 27:40 Reliable Data

Thank you. This was insightful.

So valuable tutorial I belive i will a master in data analysis

Excellent video. Using this to help clean up a massive sales lead list.

Great video and information.

Thank you for this awesome tut. Could you please have another dedicated video for Sampling - detailed? If you've such a tut already, can you please share the link? Thanks in advance.

I just love her. The best explanation!

Thank you so much ❤️

Thanks for this insight

when it comes to margin of error isn't it that when you are doing two way testing as in the case of the 4 day work week the error is split and not 50% or 70% margin? so margin of error OR alpha = 0.1 then 0.05 would be for the left side of the confidence interval and 0.05 for the right side? this would make the margin actually 55% or 65% right?

How to clean my data

I'm a recent graduate Mechatronics engineer. I'm interested to work with Google. I applied so many jobs at Google. But I didn't get even a single opportunity.. I'm looking for a opportunity.

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