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kjetil b halvorsen ♦
kjetil b halvorsen ♦
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formatted; light editing
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gung - Reinstate Monica
gung - Reinstate Monica
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I have a dummy variable for health (0 or 1), and for each observation a treatment (one of three possible treatments for each observation). I want to test the null hypothesis that the proportion (mean) healthy within each treatment group is not significantly different than any other treatment group's proportion. \begin{align} &H_0: P_j = P_{j'}\quad\quad\text{ for some } j \ne j' \\ &H_A: P_j\ne P_{j'} \end{align}\begin{align} H_0\!: P_j = P_{j'}\quad &\text{for some } j \ne j' \\ H_A\!\!: P_j\ne P_{j'}\quad &\text{for all } j \ne j' \end{align} That is, my alternative hypothesis is that every proportion (mean) is different than every other proportion. My data looks something like this:

treatment, health
1,         1
1,         0
2,         0
2,         0
3,         1
3,         1
...

I have a dummy variable for health (0 or 1), and for each observation a treatment (one of three possible treatments for each observation). I want to test the null hypothesis that the proportion (mean) healthy within each treatment group is not significantly different than any other treatment group's proportion. \begin{align} &H_0: P_j = P_{j'}\quad\quad\text{ for some } j \ne j' \\ &H_A: P_j\ne P_{j'} \end{align} That is, my alternative hypothesis is that every proportion (mean) is different than every other proportion. My data looks something like this:

treatment, health
1,         1
1,         0
2,         0
2,         0
3,         1
3,         1
...

I have a dummy variable for health (0 or 1), and for each observation a treatment (one of three possible treatments for each observation). I want to test the null hypothesis that the proportion (mean) healthy within each treatment group is not significantly different than any other treatment group's proportion. \begin{align} H_0\!: P_j = P_{j'}\quad &\text{for some } j \ne j' \\ H_A\!\!: P_j\ne P_{j'}\quad &\text{for all } j \ne j' \end{align} That is, my alternative hypothesis is that every proportion (mean) is different than every other proportion. My data looks something like this:

treatment, health
1,         1
1,         0
2,         0
2,         0
3,         1
3,         1
...
formatted; light editing
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gung - Reinstate Monica
gung - Reinstate Monica
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Three Binomial Random Variablesbinomial random variables: Test Null That No Two Have Equal Meantest null that no two have equal mean

I have a dummy variable for health (0 or 1), and for each observation a treatment (one of three possible treatments for each observation). I want to test the null hypothesis that the proportion (mean) healthy within each treatment group is not significantly different than any other treatment group's proportion.

H_0: P_1 = P_2 OR P_1 = P_3 OR P_2 = P_3 H_A:\begin{align} &H_0: P_j = P_{j'}\quad\quad\text{ for some } j \ne j' \\ &H_A: P_j\ne P_{j'} \end{align} That is, my alternative hypothesis is that every proportion (mean) is different than every other proportion

So my. My data looks something like this: (treatment, health)

(1,1) (1,0) (2,0) (2,0) (3,1) (3,1) ...

treatment, health
1,         1
1,         0
2,         0
2,         0
3,         1
3,         1
...

Three Binomial Random Variables: Test Null That No Two Have Equal Mean

I have a dummy variable for health (0 or 1), and for each observation a treatment (one of three possible treatments for each observation). I want to test the null hypothesis that the proportion (mean) healthy within each treatment group is not significantly different than any other treatment group's proportion.

H_0: P_1 = P_2 OR P_1 = P_3 OR P_2 = P_3 H_A: every proportion (mean) is different than every other proportion

So my data looks something like this: (treatment, health)

(1,1) (1,0) (2,0) (2,0) (3,1) (3,1) ...

Three binomial random variables: test null that no two have equal mean

I have a dummy variable for health (0 or 1), and for each observation a treatment (one of three possible treatments for each observation). I want to test the null hypothesis that the proportion (mean) healthy within each treatment group is not significantly different than any other treatment group's proportion. \begin{align} &H_0: P_j = P_{j'}\quad\quad\text{ for some } j \ne j' \\ &H_A: P_j\ne P_{j'} \end{align} That is, my alternative hypothesis is that every proportion (mean) is different than every other proportion. My data looks something like this:

treatment, health
1,         1
1,         0
2,         0
2,         0
3,         1
3,         1
...
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user44138
user44138
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