Correct reporting of percentages comparisons - Cross Validated

So, when we have two percentage values, what are correct ways to compare these and formulate the comparison in a report? A = 75% B = 50% For the absolute difference of A and B (75% - …

CouponFollow Extension

75%
OFF

Correct Reporting Of Percentages Comparisons - Cross Validated

3 weeks from now

So, when we have two percentage values, what are correct ways to compare these and formulate the comparison in a report? A = 75% B = 50% For the absolute difference of A and B (75% - …

stackexchange.com

10%
OFF

How To Report Percentage Change In Proportions? - Cross Validated

3 weeks from now

Nov 15, 2018 · I want to compare changes in the proportion of fruit purchases over time for a household. For example, in year 1, 4/40 (10%) fruit were apples, in year 2, 12/80 (15%) fruit …

stackexchange.com

100%
OFF

Best Way To Compare Changes In Proportions - Cross Validated

3 weeks from now

Apr 2, 2019 · In this case it is correct, although misleading to report the "percentage change" (being a change-as-a-percent) as 100% meaning a doubling. You could ask that they report …

stackexchange.com

10%
OFF

Statistical Significance - Comparing Two Percentages - Cross …

3 weeks from now

Mar 8, 2017 · How would I go about comparing two percentage figures from two different sample sizes? For example: Sample 1 - 10% (220,510 out of 2,205,100) of respondents answered …

stackexchange.com

FAQs about Correct reporting of percentages comparisons - Cross Validated Coupon?

Is it inappropriate to report a percentage change in a proportion?

When reporting this in a paper, it feels inappropriate to report the percentage change in a proportion (i.e. "there was a 50% increase in the proportion of apples), but the alternative ("there was a 5 percentage point increase in the proportion of apples") ignores the underlying magnitude. ...

How many possible combinations are there in a cross-validation model?

The number of possible combinations is equal to the number of data points in the original sample or n. Cross Validation is a very useful technique for assessing the effectiveness of your model, particularly in cases where you need to mitigate over-fitting. ...

Why does a cross-validation test have a high variance?

However, its evaluation can have high variance since evaluation may depend on which data points end up in the training sample and which end up in the test sample. When K = n, this is called leave-one-out cross-validation. ...

What are the different types of cross validation techniques?

There are different types of Cross Validation Techniques but the overall concept remains the same, • To partition the data into a number of subsets • Hold out a set at a time and train the model on remaining set • Test model on hold out set ...

Are percent differences a problem?

Phrases like "percent differences" or "percent improvements" are a big problem. It's often not clear whether those who use that phrase are talking about percent differences from a pre-treatment condition, as in your example, or percentage-point differences. ...

Do I need to call the FIT method separately while using cross validation?

We do not need to call the fit method separately while using cross validation, the cross_val_score method fits the data itself while implementing the cross-validation on data. Below is the example for using k-fold cross validation. The Accuracy of the model is the average of the accuracy of each fold. ...