Additive property of independent chi-squares
$begingroup$
in a user study the participants were shown 9 different visual representations of data and they had to answer (a) if they do understand the presented data and (b) if they think it is helpful.
The questions were answered on a 5 point Likert scale from (1) "Strongly Agree" to (5) "Strongly Disagree". The sample size is $n=50$ for each profile.
I wanted to use the $X^2$ test to compute if there is a statistical significance between these two statements.
I tested this for each profile individually and got p-values between .5 and .8 (no statistical significance).
However, if I combine (add) the results of all nine profiles and run the test again I get statistical significance (p-value.002).
I know about the additive property of independent chi-squares which confuses me even more. Is there an explanation that I am missing right now?
Cheers
chi-squared
asked Jan 8 at 15:41
alive-and-wellalive-and-well
12
$endgroup$
add a comment |
$begingroup$
in a user study the participants were shown 9 different visual representations of data and they had to answer (a) if they do understand the presented data and (b) if they think it is helpful.
The questions were answered on a 5 point Likert scale from (1) "Strongly Agree" to (5) "Strongly Disagree". The sample size is $n=50$ for each profile.
I wanted to use the $X^2$ test to compute if there is a statistical significance between these two statements.
I tested this for each profile individually and got p-values between .5 and .8 (no statistical significance).
However, if I combine (add) the results of all nine profiles and run the test again I get statistical significance (p-value.002).
I know about the additive property of independent chi-squares which confuses me even more. Is there an explanation that I am missing right now?
Cheers
chi-squared
asked Jan 8 at 15:41
alive-and-wellalive-and-well
12
$endgroup$
add a comment |
$begingroup$
in a user study the participants were shown 9 different visual representations of data and they had to answer (a) if they do understand the presented data and (b) if they think it is helpful.
The questions were answered on a 5 point Likert scale from (1) "Strongly Agree" to (5) "Strongly Disagree". The sample size is $n=50$ for each profile.
I wanted to use the $X^2$ test to compute if there is a statistical significance between these two statements.
I tested this for each profile individually and got p-values between .5 and .8 (no statistical significance).
However, if I combine (add) the results of all nine profiles and run the test again I get statistical significance (p-value.002).
I know about the additive property of independent chi-squares which confuses me even more. Is there an explanation that I am missing right now?
Cheers
chi-squared
asked Jan 8 at 15:41
alive-and-wellalive-and-well
12
$endgroup$
in a user study the participants were shown 9 different visual representations of data and they had to answer (a) if they do understand the presented data and (b) if they think it is helpful.
The questions were answered on a 5 point Likert scale from (1) "Strongly Agree" to (5) "Strongly Disagree". The sample size is $n=50$ for each profile.
I wanted to use the $X^2$ test to compute if there is a statistical significance between these two statements.
I tested this for each profile individually and got p-values between .5 and .8 (no statistical significance).
However, if I combine (add) the results of all nine profiles and run the test again I get statistical significance (p-value.002).
I know about the additive property of independent chi-squares which confuses me even more. Is there an explanation that I am missing right now?
Cheers
chi-squared
chi-squared
asked Jan 8 at 15:41
alive-and-wellalive-and-well
12
asked Jan 8 at 15:41
alive-and-wellalive-and-well
12
asked Jan 8 at 15:41
alive-and-wellalive-and-well
12
asked Jan 8 at 15:41
alive-and-wellalive-and-well
12
asked Jan 8 at 15:41
alive-and-wellalive-and-well
12
12
add a comment |
add a comment |
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