- #1
Equate
- 78
- 0
What's the missing number and why?
http://img18.imageshack.us/img18/2408/a89raetsel.png
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drizzle said:5 [and this just to submit the post, damn 4 characters! :grumpy:]
ƒ(x) said:why?
revelations said:What about 4?
Look at the total for each column and each row.
Column 1: 24
Column 2: 23
Column 3: ?
Column 4: 27
Row 1: 21
Row 2: 23
Row 3: ?
Row 4: 27
If you use 4, that means the 3rd row is 24 and the 3rd column is 21. Therefore there is a 1:1 ratio of the frequency of column sums to row sums.
..right?
"Missing #" refers to a missing data point or value in a dataset, where the value was expected to be present but is not recorded or available.
Missing data can impact the accuracy and reliability of research findings, as it can lead to biased results and inaccurate conclusions if not addressed properly.
There can be various reasons for missing data, including human error in data collection, equipment malfunction, and data loss during storage or transfer. It can also result from participants dropping out of a study or not responding to certain questions.
There are various methods for handling missing data, such as imputation (replacing missing values with estimated values), deletion (removing the entire data point with missing values), or using statistical techniques such as mean substitution. The appropriate method will depend on the type of data and the research question.
The method used to handle missing data can introduce bias or affect the validity of the results. Additionally, if a large amount of data is missing, it can impact the power and generalizability of the study. It is crucial to carefully consider and report the approach used to handle missing data in any scientific research.