How to test hypothesis for discrete data?
I have observed (experimental) data categorized in seven categories. This has 50 samples and gives frequencies for these categories. Moreover, I have a model which predicts the discrete probability distribution of these categories. My hypothesis is that my model models the observed data successfully (in other words, observation follows the distribution given by my model). How can I test my hypothesis? I have tried the chi-square test but my model consists zero probabilities in some cases, so it is not applicable.
Example model prediction and observation:
c1. c2. c3. c4. c5. c6. c7. (categories)
observed: 15 25 7 3 0 0 0 (sample size is 50)
prediction: 0.5 0.1 0 0 0.3 0 0.1 (probabilities)
hypothesis-test goodness-of-fit
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I have observed (experimental) data categorized in seven categories. This has 50 samples and gives frequencies for these categories. Moreover, I have a model which predicts the discrete probability distribution of these categories. My hypothesis is that my model models the observed data successfully (in other words, observation follows the distribution given by my model). How can I test my hypothesis? I have tried the chi-square test but my model consists zero probabilities in some cases, so it is not applicable.
Example model prediction and observation:
c1. c2. c3. c4. c5. c6. c7. (categories)
observed: 15 25 7 3 0 0 0 (sample size is 50)
prediction: 0.5 0.1 0 0 0.3 0 0.1 (probabilities)
hypothesis-test goodness-of-fit
add a comment |
I have observed (experimental) data categorized in seven categories. This has 50 samples and gives frequencies for these categories. Moreover, I have a model which predicts the discrete probability distribution of these categories. My hypothesis is that my model models the observed data successfully (in other words, observation follows the distribution given by my model). How can I test my hypothesis? I have tried the chi-square test but my model consists zero probabilities in some cases, so it is not applicable.
Example model prediction and observation:
c1. c2. c3. c4. c5. c6. c7. (categories)
observed: 15 25 7 3 0 0 0 (sample size is 50)
prediction: 0.5 0.1 0 0 0.3 0 0.1 (probabilities)
hypothesis-test goodness-of-fit
I have observed (experimental) data categorized in seven categories. This has 50 samples and gives frequencies for these categories. Moreover, I have a model which predicts the discrete probability distribution of these categories. My hypothesis is that my model models the observed data successfully (in other words, observation follows the distribution given by my model). How can I test my hypothesis? I have tried the chi-square test but my model consists zero probabilities in some cases, so it is not applicable.
Example model prediction and observation:
c1. c2. c3. c4. c5. c6. c7. (categories)
observed: 15 25 7 3 0 0 0 (sample size is 50)
prediction: 0.5 0.1 0 0 0.3 0 0.1 (probabilities)
hypothesis-test goodness-of-fit
hypothesis-test goodness-of-fit
asked Nov 15 '18 at 21:51
Mert AlbabaMert Albaba
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add a comment |
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