reporting chi square test of independence in apa
DESCRIPTION
Reporting Chi Square Test of Independence in APATRANSCRIPT
Reporting a Chi-SquareTest of Independence
in APA
Reporting a Chi-SquareTest of Independence
in APA
Note – that the reporting format shown in this learning module is for APA. For other formats
consult specific format guides. It is also recommended to consult the latest APA manual to compare what is described in this learning module with the most updated
formats for APA
Reporting a Chi-SquareTest of Independence
in APA
Note – that the reporting format shown in this learning module is for APA. For other formats
consult specific format guides. It is also recommended to consult the latest APA manual to compare what is described in this learning module with the most updated
formats for APA
• In this short tutorial you will see a problem that can be investigated using a Chi-Square Test of Independence.
• In this short tutorial you will see a problem that can be investigated using a Chi-Square Test of Independence.
• You will then see how the results of the analysis can be reported using APA style.
Problem:
Problem:We analyzed whether heart disease (no=1 and yes =2) and gender (male = 1 and female = 2) are independent of one another.
• Here is one general template for reporting a Chi-Square Test of Independence:
A Chi-square test of independence was calculated comparing the frequency of heart disease in men and women. A significant interaction was found (2 (1) = 23.80, p < .05). Men were more likely to get heart dease (68% than women (40%)
Problem:We analyzed whether heart disease (no=1 and yes =2) and gender (male = 1 and female = 2) are independent of one another.
• Here is one general template for reporting a Chi-Square Test of Independence:
A Chi-square test of independence was calculated comparing the frequency of heart disease in men and women. A significant interaction was found (2 (1) = 23.80, p < .05). Men were more likely to get heart dease (68% than women (40%)
Problem:We analyzed whether heart disease (no=1 and yes =2) and gender (male = 1 and female = 2) are independent of one another.
• Here is one general template for reporting a Chi-Square Test of Independence:
A Chi-square test of independence was calculated comparing the frequency of heart disease in men and women. A significant interaction was found (2 (1) = 23.80, p < .05). Men were more likely to get heart dease (68%) than women (40%)
Problem:We analyzed whether heart disease (no=1 and yes =2) and gender (male = 1 and female = 2) are independent of one another.
• Here is one general template for reporting a Chi-Square Test of Independence:
A Chi-square test of independence was calculated comparing the frequency of heart disease in men and women. A significant interaction was found (2 (1) = 23.80, p < .05). Men were more likely to get heart dease (68%) than women (40%)
Problem:We analyzed whether heart disease (no=1 and yes =2) and gender (male = 1 and female = 2) are independent of one another.
• Here is one general template for reporting a Chi-Square Test of Independence:
A Chi-square test of independence was calculated comparing the frequency of heart disease in men and women. A significant interaction was found (2 (1) = 23.80, p < .05). Men were more likely to get heart dease (68%) than women (40%) Chi-
Square
Problem:We analyzed whether heart disease (no=1 and yes =2) and gender (male = 1 and female = 2) are independent of one another.
• Here is one general template for reporting a Chi-Square Test of Independence:
A Chi-square test of independence was calculated comparing the frequency of heart disease in men and women. A significant interaction was found (2 (1) = 23.80, p < .05). Men were more likely to get heart dease (68%) than women (40%) Degrees of
Freedom
Problem:We analyzed whether heart disease (no=1 and yes =2) and gender (male = 1 and female = 2) are independent of one another.
• Here is one general template for reporting a Chi-Square Test of Independence:
A Chi-square test of independence was calculated comparing the frequency of heart disease in men and women. A significant interaction was found (2 (1) = 23.80, p < .05). Men were more likely to get heart dease (68%) than women (40%)
Statistical Significance