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In: Math

(I need your Reference URL LINK, please) ( i need Unique answer, don't copy and paste,...

(I need your Reference URL LINK, please)

( i need Unique answer, don't copy and paste, please) (dont' use handwriting, please)

Q1. Define the following terms:
A. Contingency table (Introduction to Biostatistics)
B. Chi-square test (Introduction to Biostatistics)
Q2. List the assumptions required to perform a chi-square test? (Introduction to Biostatistics)

( i need Unique answer, don't copy and paste, please) (dont' use handwriting, please)

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Expert Solution

Hi,

I'll try to keep it as unique as your question description states so I'll write in my own words being a Statistician what I've learned in the past 5-6 years.

Q1. A. A contingency table is an interesting way to calculate Probabilities in a general sense had it followed a Normal Distribution. Since we derive the table from a given set of data, it helps in determining conditional probabilities quite easily. The table displays sample values in relation to two different variables that may be dependent or contingent on one another (I'm hoping you'll understand then why we're using the general term of contingent comes from).

B. As we mentioned above, we are creating our contingency table to find our expected values had it followed the general norms of Normal distribution. Now, of course, real life is harder and much more unpredictable, and therefore after we've found out the table we try to compare the two different tables as to actually how different is it from the original values. So basically, Chi-square is a statistical test which we commonly use to compare observed data with data we would expect to obtain according to a specific hypothesis. That is, chi-square is the sum of the squared difference between observed (o) and the expected (e) data, divided by the expected data in all possible categories. You'll find the formula here as you expected some formula: https://en.wikipedia.org/wiki/Chi-squared_test

Q2. The two biggest assumptions are :

  1. Two variables should be measured at an ordinal or nominal level. That is they must be categorical data.
  2. Two variable should consist of two or more categorical independent groups. If anyone of them has less than two categories you can’t do chi-square test.

Hope it helps. Happy learning :)


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