Mixing
What is the alternative hypothesis?
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Consider a national survey that 37% of people name soccer as their favorite sport. My personal survey says that out of 400 people, 168 say soccer is their favorite.
I'm having trouble deciding if the alternative hypothesis is:
H1 ≠ .37 or H1 > .37
statistics hypothesis-testing
asked Oct 27 '18 at 0:06
user9430840user9430840
1
$endgroup$
add a comment |
$begingroup$
Consider a national survey that 37% of people name soccer as their favorite sport. My personal survey says that out of 400 people, 168 say soccer is their favorite.
I'm having trouble deciding if the alternative hypothesis is:
H1 ≠ .37 or H1 > .37
statistics hypothesis-testing
asked Oct 27 '18 at 0:06
user9430840user9430840
1
$endgroup$
$begingroup$
It is unlikely that "exactly 37 % of people name soccer as their favourite sport" works. This statement depends on an exact value and hence every small deviation would conflict with it. On the other hand, inclusion of an error margin, say 37 % +/- 3 % might make it work. Often used is "at least 37 %" or "no more than 37 %". Each of these statements is realistic, and each can be confirmed or contradicted by statistical facts.
$endgroup$
– M. Wind
Oct 27 '18 at 0:24
add a comment |
$begingroup$
Consider a national survey that 37% of people name soccer as their favorite sport. My personal survey says that out of 400 people, 168 say soccer is their favorite.
I'm having trouble deciding if the alternative hypothesis is:
H1 ≠ .37 or H1 > .37
statistics hypothesis-testing
asked Oct 27 '18 at 0:06
user9430840user9430840
1
$endgroup$
Consider a national survey that 37% of people name soccer as their favorite sport. My personal survey says that out of 400 people, 168 say soccer is their favorite.
I'm having trouble deciding if the alternative hypothesis is:
H1 ≠ .37 or H1 > .37
statistics hypothesis-testing
statistics hypothesis-testing
asked Oct 27 '18 at 0:06
user9430840user9430840
1
asked Oct 27 '18 at 0:06
user9430840user9430840
1
asked Oct 27 '18 at 0:06
user9430840user9430840
1
asked Oct 27 '18 at 0:06
user9430840user9430840
1
asked Oct 27 '18 at 0:06
user9430840user9430840
1
1
$begingroup$
It is unlikely that "exactly 37 % of people name soccer as their favourite sport" works. This statement depends on an exact value and hence every small deviation would conflict with it. On the other hand, inclusion of an error margin, say 37 % +/- 3 % might make it work. Often used is "at least 37 %" or "no more than 37 %". Each of these statements is realistic, and each can be confirmed or contradicted by statistical facts.
$endgroup$
– M. Wind
Oct 27 '18 at 0:24
add a comment |
$begingroup$
It is unlikely that "exactly 37 % of people name soccer as their favourite sport" works. This statement depends on an exact value and hence every small deviation would conflict with it. On the other hand, inclusion of an error margin, say 37 % +/- 3 % might make it work. Often used is "at least 37 %" or "no more than 37 %". Each of these statements is realistic, and each can be confirmed or contradicted by statistical facts.
$endgroup$
– M. Wind
Oct 27 '18 at 0:24
$begingroup$
It is unlikely that "exactly 37 % of people name soccer as their favourite sport" works. This statement depends on an exact value and hence every small deviation would conflict with it. On the other hand, inclusion of an error margin, say 37 % +/- 3 % might make it work. Often used is "at least 37 %" or "no more than 37 %". Each of these statements is realistic, and each can be confirmed or contradicted by statistical facts.
$endgroup$
– M. Wind
Oct 27 '18 at 0:24
$begingroup$
It is unlikely that "exactly 37 % of people name soccer as their favourite sport" works. This statement depends on an exact value and hence every small deviation would conflict with it. On the other hand, inclusion of an error margin, say 37 % +/- 3 % might make it work. Often used is "at least 37 %" or "no more than 37 %". Each of these statements is realistic, and each can be confirmed or contradicted by statistical facts.
$endgroup$
– M. Wind
Oct 27 '18 at 0:24
add a comment |
1 Answer
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$begingroup$
The alternative hypothesis helps you think about what counts as extreme results under the null hypothesis.
If the national survey gave a correct result you might have expected about $148$ soccer responses to your personal survey. Would you regard $300$ as an extreme result? What about $30$?
If you care both about extremely high and extremely low, then this might suggest $H_1: ,not = 0.37$ is the more appropriate alternative hypothesis
answered Jan 28 at 22:57
HenryHenry
101k482169
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1 Answer
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1 Answer
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$begingroup$
The alternative hypothesis helps you think about what counts as extreme results under the null hypothesis.
If the national survey gave a correct result you might have expected about $148$ soccer responses to your personal survey. Would you regard $300$ as an extreme result? What about $30$?
If you care both about extremely high and extremely low, then this might suggest $H_1: ,not = 0.37$ is the more appropriate alternative hypothesis
answered Jan 28 at 22:57
HenryHenry
101k482169
$endgroup$
add a comment |
$begingroup$
The alternative hypothesis helps you think about what counts as extreme results under the null hypothesis.
If the national survey gave a correct result you might have expected about $148$ soccer responses to your personal survey. Would you regard $300$ as an extreme result? What about $30$?
If you care both about extremely high and extremely low, then this might suggest $H_1: ,not = 0.37$ is the more appropriate alternative hypothesis
answered Jan 28 at 22:57
HenryHenry
101k482169
$endgroup$
add a comment |
$begingroup$
The alternative hypothesis helps you think about what counts as extreme results under the null hypothesis.
If the national survey gave a correct result you might have expected about $148$ soccer responses to your personal survey. Would you regard $300$ as an extreme result? What about $30$?
If you care both about extremely high and extremely low, then this might suggest $H_1: ,not = 0.37$ is the more appropriate alternative hypothesis
answered Jan 28 at 22:57
HenryHenry
101k482169
$endgroup$
The alternative hypothesis helps you think about what counts as extreme results under the null hypothesis.
If the national survey gave a correct result you might have expected about $148$ soccer responses to your personal survey. Would you regard $300$ as an extreme result? What about $30$?
If you care both about extremely high and extremely low, then this might suggest $H_1: ,not = 0.37$ is the more appropriate alternative hypothesis
answered Jan 28 at 22:57
HenryHenry
101k482169
answered Jan 28 at 22:57
HenryHenry
101k482169
answered Jan 28 at 22:57
HenryHenry
101k482169
answered Jan 28 at 22:57
HenryHenry
101k482169
101k482169
add a comment |
add a comment |
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$begingroup$
It is unlikely that "exactly 37 % of people name soccer as their favourite sport" works. This statement depends on an exact value and hence every small deviation would conflict with it. On the other hand, inclusion of an error margin, say 37 % +/- 3 % might make it work. Often used is "at least 37 %" or "no more than 37 %". Each of these statements is realistic, and each can be confirmed or contradicted by statistical facts.
$endgroup$
– M. Wind
Oct 27 '18 at 0:24