For each analysis, use the following steps to write a complete description of re
ID: 3223686 • Letter: F
Question
For each analysis, use the following steps to write a complete description of results in proper APA format. 1. State what hypothesis was tested. 2. State what test was used. 3. What decision did you make? Reject the null or retain (fail to reject) the null. 4. Were the groups significantly different from each other? 5. Report the means and standard deviations for each group. 6. Put numbers in APA format: a. General Format: symbol for the test (df)= obtained value, p> or < significance level 7. Report Effect Size (if known)Example Write-up: It was expected that number of days absent from work in a year (M=9.65, SD=1.59) would predict the amount of salary (M=39847.65, SD=4598.43). A simple linear regression was run. The scatterplot showed a negative relationship between days absent from work and salary. The overall regression equation was significant, F(1, 148)=3.51, p<.05. The slope for days absent from work was significant, =-.49, t(148)=2.54, p<.05. For every one day people miss from work, their salary decreases by .49.
Please complete the following for Assignment 12
Answer the following questions for each hypothesis: 1. Emotional support with closest female friends will predict the reported level of satisfaction with their closest female friends. a. Write up the results for the regression procedures below:
2. Female’s age in months will predict the reported level of loyalty with closest female friends. a. Write up the results for the regression procedures below:
For each analysis, use the following steps to write a complete description of results in proper APA format. 1. State what hypothesis was tested. 2. State what test was used. 3. What decision did you make? Reject the null or retain (fail to reject) the null. 4. Were the groups significantly different from each other? 5. Report the means and standard deviations for each group. 6. Put numbers in APA format: a. General Format: symbol for the test (df)= obtained value, p> or < significance level 7. Report Effect Size (if known)
Example Write-up: It was expected that number of days absent from work in a year (M=9.65, SD=1.59) would predict the amount of salary (M=39847.65, SD=4598.43). A simple linear regression was run. The scatterplot showed a negative relationship between days absent from work and salary. The overall regression equation was significant, F(1, 148)=3.51, p<.05. The slope for days absent from work was significant, =-.49, t(148)=2.54, p<.05. For every one day people miss from work, their salary decreases by .49.
Please complete the following for Assignment 12
Answer the following questions for each hypothesis: 1. Emotional support with closest female friends will predict the reported level of satisfaction with their closest female friends. a. Write up the results for the regression procedures below:
2. Female’s age in months will predict the reported level of loyalty with closest female friends. a. Write up the results for the regression procedures below:
Participant's Age in Months Overall satisfacson with 800 Closest Female Friend Valid N Mistwisel Variables Entered Removed Model Summa ANOVA Variables Entered Removed Adjusted R Std Emor of the ANOVA 56.44 7.12e 13
Explanation / Answer
Question-1
1-Null hypothesis H0: =0 versus alternative Ha: 0
2-We will use OLS regression analysis.
3-We reject the null hypothesis as =0.098, t(98)=7.49, p<.05.
4-There is significant impact of Emotional support with closest female friends on the reported level of satisfaction with their closest female friends
5- Emotional support with closest female friends has mean and standard deviations as 56.44 and SD=8.27 respectively while for the reported level of satisfaction with their closest female friends these are 7.12 and 1.34
6-This is as follows:
It was expected that Emotional support with closest female friends (M=56.44, SD=8.27) would predict the reported level of satisfaction with their closest female friends (M=7.12, SD=1.34). A simple linear regression was run. The overall regression equation was significant, F(1, 98)=56.08, p<.05. The slope for Emotional support with closest female friends was significant, =0.098, t(98)=7.49, p<.05. For unit increase in Emotional support with closest female friends, the reported level of satisfaction with their closest female friends increases by 0.098.
7-Effect size R2=0.36 which means that 36% of the variations in reported level of satisfaction with their closest female friends is explained by Emotional support with closest female friends.
Question-2
1-Null hypothesis H0: =0 versus alternative Ha: 0
2-We will use OLS regression analysis.
3-We reject the null hypothesis as =0.184, t(98)=1.74, p=0.084>0.05.
4-There is not a significant impact of Female’s age in months on the reported level of loyalty with closest female friends
5- Female’s age in months has mean and standard deviations as 225.90 months and SD=5.55 months respectively while for the reported level of loyalty with closest female friends these are 60.55 and 5.88
6-This is as follows:
It was expected that Female’s age in months (M=225.90, SD=5.55) would predict the reported level of loyalty with closest female friends (M=60.55, SD=5.88). A simple linear regression was run. The overall regression equation was not significant, F(1, 98)=3.04, p>.05. The slope for Female’s age in months was significant, =0.18, t(98)=1.74, p>.05. For unit increase in Female’s age in months, the reported level of loyalty with closest female friends increases by 0.184.
7-Effect size R2=0.03 which means that 3% of the variations in the reported level of loyalty with closest female friends is explained by Female’s age in months.
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