Examine your ANOVA table to see if there is a significant difference between cannabis use and social network size, anxiety levels and social network size, and the interaction between cannabis use and anxiety levels. Look at your p value to determine whether there is a significant difference. Remember, if your p value is less than 0.05, there is a significant difference. State in the appropriate question blank on your worksheet whether there was a significant relationship in the following way. In each parentheses, select the word or symbol in red that best fits your data. Replace “df anxiety levels”, “df residual”, and “F value” with the corresponding value from your ANOVA table: “A two-way ANOVA was used to examine the effect of anxiety level and cannabis use on social network size. There (was/was not) a significant main effect of the level of anxiety on social network size, (F (df anxiety levels, df residuals) = F value, p(</>).05., and (was/was not) a significant main effect of cannabis use status on social network size (F (df for cannabis use, df residuals) = F value, p(</>).05.). There (was/was not) a statistically significant interaction between the effects of cannabis use and anxiety levels on social network size, (F (df for interaction, df residuals) = F value, p(</>).05)
Examine your ANOVA table to see if there is a significant difference between cannabis use and social network size, anxiety levels and social network size, and the interaction between cannabis use and anxiety levels. Look at your p value to determine whether there is a significant difference. Remember, if your p value is less than 0.05, there is a significant difference. State in the appropriate question blank on your worksheet whether there was a significant relationship in the following way. In each parentheses, select the word or symbol in red that best fits your data. Replace “df anxiety levels”, “df residual”, and “F value” with the corresponding value from your ANOVA table: “A two-way ANOVA was used to examine the effect of anxiety level and cannabis use on social network size. There (was/was not) a significant main effect of the level of anxiety on social network size, (F (df anxiety levels, df residuals) = F value, p(</>).05., and (was/was not) a significant main effect of cannabis use status on social network size (F (df for cannabis use, df residuals) = F value, p(</>).05.). There (was/was not) a statistically significant interaction between the effects of cannabis use and anxiety levels on social network size, (F (df for interaction, df residuals) = F value, p(</>).05)
Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018
18th Edition
ISBN:9780079039897
Author:Carter
Publisher:Carter
Chapter10: Statistics
Section10.5: Comparing Sets Of Data
Problem 2CYU
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- Examine your ANOVA table to see if there is a significant difference between cannabis use and social network size, anxiety levels and social network size, and the interaction between cannabis use and anxiety levels. Look at your p value to determine whether there is a significant difference. Remember, if your p value is less than 0.05, there is a significant difference.
- State in the appropriate question blank on your worksheet whether there was a significant relationship in the following way. In each parentheses, select the word or symbol in red that best fits your data. Replace “df anxiety levels”, “df residual”, and “F value” with the corresponding value from your ANOVA table:
- “A two-way ANOVA was used to examine the effect of anxiety level and cannabis use on social network size. There (was/was not) a significant main effect of the level of anxiety on social network size, (F (df anxiety levels, df residuals) = F value, p(</>).05., and (was/was not) a significant main effect of cannabis use status on social network size (F (df for cannabis use, df residuals) = F value, p(</>).05.). There (was/was not) a statistically significant interaction between the effects of cannabis use and anxiety levels on social network size, (F (df for interaction, df residuals) = F value, p(</>).05)”.
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