Home › Forums › Methodspace discussion › Help needed on team survey analysis
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Berlin Asong.
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14th July 2011 at 7:47 pm #3344
lanre
MemberI am working on an undergrad thesis with the topic IMPACT OF SHARED-LEADERSHIP ON PERFORMANCE OF SELF MANAGED STUDENT TEAMS.I am now at analysis stage and 1 of my research question was to check the impact of share-leadership on performance.I have 10 leadership variables on my questionnaire and 8 performance variables and I am working with 7 teams in total.could anyone help me on how to go on with the analysis?
15th July 2011 at 12:44 am #3348Berlin Asong
ParticipantCould you identify the research method you are using? By research method, I mean—is it quantitative, qualitative or mixed method? Though questionnaire is traditionally associated with quantitative research, it’s also applicable in qualitative studies. As a result, I can’t determine which research method you are using. Why I want you to identify for us your choice of research method because the latter influences the data analysis.
Assuming your research is a quantitative study, you may use simple statistical analysis such as frequency and proportion tabulation. Let say your leadership variables are “empathy”, “intelligent”, “assertive”, “inspiring”, and your team performance variables are “goals attainment”, “new ideas”, “speed”, “active participation”. You could analyse the data by looking at the frequency of the leadership variables on the performance variables. In other words, which leadership variable was most or least cited by the team members as having a positive or negative impact on each performance variable.
Be also critical to identify mediating variables that may have influenced the causal relationships between the leadership variables and performance variables. Gender, age, ethnicity, size of teams, etc may mediate the causal links between leadership and performance. Also, look at the distribution of the leadership variables across the seven teams. That’s, compare the teams on the leadership variables on the performance variables.
Dave mentioned one-way ANOVA (hope the jargon isn’t intimidating), which is also helpful.
However, you could save yourself the headache by using SPSS, a statistical data analysis software, to generate your analysis.
15th July 2011 at 6:51 am #3347lanre
MemberThanks dave …I am trying to play around using ANOVA on the SPSS.I haven’t get hold of it though but I will put more effort.
15th July 2011 at 6:59 am #3346lanre
MemberThanks Berlin..I am using a quantitative method.In fact my questionnaire is divided into three segment and 1st segment measure leadership, 2nd measures performance while the 3rd measures demographic profile of the respondents as u have mentioned above such as size of teams, gender. etc.Also, I am using SPSS for the analysis and because I am new to it I have to play around stuffs to get hold of it…
But could you please shed more light on what you meant in the following sentence “You could analyse the data by looking at the frequency of the leadership variables on the performance variables. In other words, which leadership variable was most or least cited by the team members as having a positive or negative impact on each performance variable.”
20th July 2011 at 9:24 am #3345Berlin Asong
ParticipantLanre, am sorry for the late reply. I hope my response is still valuable to you.
In response to your question, frequency analysis works thus.
Once again your leadership variables are “empathy”, “intelligent”, “assertive”, “inspiring”, “clear direction” and your team performance variables are “goals attainment”, “new ideas”, “speed”, “active participation”.
Assuming that 100 team-members participated in your study.
Let say you had a question on your questionnaire thus: which of the leadership variables has/had the most influence on your team performance?
15 respondents said “empathy”, 30 respondents said “intelligent”, 10 said “assertive”, 20 said “inspiring” and 25 said “clear direction”.
A frequency table looks like this:
Intelligent—30
Clear direction—25
Inspiring—20
Empathy—15
Assertive—10
Total: 100
See this link for a clear illustrative explanation of analyzing quantitative data. Any problems, report back to the forum.
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