Hi everybody,

I'm really new on this topic of statistical testing and I hope to find some help here.:wave:

I was trying to figure out which test I need for analyzing my data. However, I guess by reading that much I confused myself.

This is my data:

I analyzed two different retailers with respect to the avialbility of their products for 3 months. I would now like to test, if the difference in availability is statistically significant. First I thought I would use a independant sample t-test... But now I'm confused.

Because: I think it does not make sense to compare the average number of available products, as the number of total products at a retailer are different.

Let's say:

Retailer A: day 1: 12 of 14 products available, day 2: 15 of 18 products available, ..

Retailer B: day 1: 36 of 40 products available, day 2: 38 of 41 products available, ..

First I thought I could test the average of available products, so summing up 12+15+ ... /90 for retailer A and 36+38+.../90 for retailer B.

But as the total number of products differs each day, I think I better use percentages?

Because I think just comparing the average number of available products does not make a lot of sense as one retailer in general offers more products than the other.

So,

Retailer A: day 1: 85% available, day 2: 83% available , ...

Retailer B: day 1: 90% available, day 2 92% available, ...

Can I compare the means of these percentages with a t-test? Because I saw people also used Chi-Square, but this is only for non-metric data ...

And I think I can't use a "normal" mean, but a weighted one, right?

As you see, I'm really new to the topic! Therefore, I'm thankful for any comment!!

Thank you very much!!

I'm really new on this topic of statistical testing and I hope to find some help here.:wave:

I was trying to figure out which test I need for analyzing my data. However, I guess by reading that much I confused myself.

This is my data:

I analyzed two different retailers with respect to the avialbility of their products for 3 months. I would now like to test, if the difference in availability is statistically significant. First I thought I would use a independant sample t-test... But now I'm confused.

Because: I think it does not make sense to compare the average number of available products, as the number of total products at a retailer are different.

Let's say:

Retailer A: day 1: 12 of 14 products available, day 2: 15 of 18 products available, ..

Retailer B: day 1: 36 of 40 products available, day 2: 38 of 41 products available, ..

First I thought I could test the average of available products, so summing up 12+15+ ... /90 for retailer A and 36+38+.../90 for retailer B.

But as the total number of products differs each day, I think I better use percentages?

Because I think just comparing the average number of available products does not make a lot of sense as one retailer in general offers more products than the other.

So,

Retailer A: day 1: 85% available, day 2: 83% available , ...

Retailer B: day 1: 90% available, day 2 92% available, ...

Can I compare the means of these percentages with a t-test? Because I saw people also used Chi-Square, but this is only for non-metric data ...

And I think I can't use a "normal" mean, but a weighted one, right?

As you see, I'm really new to the topic! Therefore, I'm thankful for any comment!!

Thank you very much!!

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