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Oct 13, 2017 9:27 AM
(437 views)

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Oct 13, 2017 9:39 AM
(520 views)

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Hi @LucasOpt,

Your approach will depend on what level of measurement you consider your 1-5 ratings to be. If you consider them ordinal measurements, as some regard Likert scales, you will be in the domain of contingency analysis and a chi-square test of independence. If you consider the measurements to be interval scaled (in JMP's terminology, continuous measurements), you're in the domain of tests of means, and specifically here, an independent-samples (aka two-sample) t-test. To carry out either of these analyses (and my preference is for the latter) you'll be using Analyze > Fit Y by X. To see how to perform these analyses I would recommend looking through the materials in the JMP Learning Library in the section "Basic Inference - Proportions and Means." You will find guides and videos for each of these analyses and will see how JMP needs the data to be arranged.

I hope this helps!

1 REPLY

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Oct 13, 2017 9:39 AM
(521 views)

Hi @LucasOpt,

Your approach will depend on what level of measurement you consider your 1-5 ratings to be. If you consider them ordinal measurements, as some regard Likert scales, you will be in the domain of contingency analysis and a chi-square test of independence. If you consider the measurements to be interval scaled (in JMP's terminology, continuous measurements), you're in the domain of tests of means, and specifically here, an independent-samples (aka two-sample) t-test. To carry out either of these analyses (and my preference is for the latter) you'll be using Analyze > Fit Y by X. To see how to perform these analyses I would recommend looking through the materials in the JMP Learning Library in the section "Basic Inference - Proportions and Means." You will find guides and videos for each of these analyses and will see how JMP needs the data to be arranged.

I hope this helps!